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Table 3 Correlation between number of vape advertisements within 800 m of a secondary school and proportion of students per school residing in the most deprived quintile of the CIMD dimensions (N = 18), rΤ (p value)

From: Examining how changes in provincial policy on vape marketing impacted the distribution of vaping advertisements near secondary schools in London, Ontario

  Residential instability Economic dependency Ethno-cultural composition Situational vulnerability
Unadjusted
  Pre-ban Count (unweighted) 0.51 (< 0.01) 0.03 (0.88) − 0.11 (0.54) 0.36 (0.04)
Count (weighted) 0.52 (< 0.01) 0.04 (0.82) − 0.11 (0.54) 0.36 (0.04)
Density 0.51 (< 0.01) 0.01 (0.94) − 0.13 (0.45) 0.36 (0.04)
  Post-ban Count (unweighted) 0.27 (0.15) − 0.02 (0.90) − 0.30 (0.11) 0.19 (0.31)
Count (weighted) 0.24 (0.19) − 0.06 (0.75) − 0.30 (0.10) 0.17 (0.37)
Density 0.26 (0.15) − 0.05 (0.78) − 0.32 (0.08) 0.17 (0.35)
  Difference (counts pre- to post-ban) 0.52 (< 0.01) 0.01 (0.94) − 0.09 (0.59) 0.39 (0.03)
Adjusted*
  Pre-ban Count (unweighted) 0.42 (0.02) − 0.13 (0.48) − 0.07 (0.68) 0.31 (0.09)
Count (weighted) 0.41 (0.02) − 0.11 (0.54) − 0.07 (0.68) 0.30 (0.09)
Density 0.41 (0.02) − 0.14 (0.42) − 0.11 (0.55) 0.30 (0.09)
  Post-ban Count (unweighted) 0.12 (0.49) − 0.14 (0.42) − 0.30 (0.10) 0.11 (0.53)
Count (weighted) 0.11 (0.52) − 0.17 (0.33) − 0.30 (0.10) 0.09 (0.62)
Density 0.13 (0.48) − 0.17 (0.33) − 0.32 (0.07) 0.09 (0.60)
  Difference (counts pre- to post-ban) 0.42 (0.02) − 0.14 (0.45) − 0.06 (0.74) 0.34 (0.06)
  1. Italicized values indicate p < 0.05. Correlations analyses were only done for the 800-m measure because of the large number of 0 counts for schools at 400 m
  2. *Adjusted for commercial land area using partial correlation