Place-Based Inequities in E-cigarette/Vape and Cannabis Retail Density in Massachusetts: The Role of Child Opportunity and Social Vulnerability.
cross_sectional · Level IV
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- Record sourced from PubMed, PMID 42066895.
- Also identified by DOI 10.1016/j.chest.2026.04.026.
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Abstract
As the legalized markets for cannabis and electronic nicotine delivery systems (ENDS; e-cigarettes/vapes) expand, there are growing concerns about increased youth exposure through retail accessibility. However, the extent to which retail placement align with structural neighborhood conditions remains unclear. How do neighborhood-level opportunity and vulnerability, measured through the Child Opportunity Index (COI) and Social Vulnerability Index (SVI), relate to e-cigarette/vape and cannabis retail density in Massachusetts? Using an ecological cross-sectional design, 5,034 licensed e-cigarette/vape (2022-2024) and 483 licensed cannabis (2024) retail locations in Massachusetts were geocoded to census tracts. Spatial analysis identified hot spots (high density clusters) and cold spots (low density clusters). Neighborhood characteristics were captured through the COI and SVI, which encompass a range of demographic, socioeconomic, and household indicators. Descriptive statistics and negative binomial regression models assessed associations between COI, SVI, and retail density. Retailers were concentrated in census tracts with lower COI scores across all domains, indicating lower child opportunity, and higher SVI scores, indicating greater social vulnerability, with largest differences observed in socioeconomic status and household composition. Higher levels of COI were associated with fewer retailers (CR 0.9; 95% CI 0.89-0.93), while greater SVI was associated with more retailers (CR 1.1; 95% CI 1.06-1.11). However, SVI themes of Housing Type/Transportation and Minority Status/Language themes showed minimal variation across retail hot and cold spots. E-cigarette/vape and cannabis retailers were disproportionately clustered in areas of high social vulnerability and low child opportunity in Massachusetts. Clustering aligned most closely with measures of socioeconomic disadvantage, rather than housing structure or racial/ethnic composition, diverging from historical tobacco retail patterns. Monitoring retail density may provide valuable insight into evolving industry strategies, state-specific factors, and the role of neighborhood-level policies in shaping exposure risk in vulnerable communities.