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Table 3 Adjusteda cross-sectional estimates of alcohol consumption with density of off-premise outlets and distance to outlets. N = 772

From: Alcohol outlets and alcohol consumption in changing environments: prevalence and changes over time

  Number of drinking days per weekb Number of drinks per week   High number of drinks per week relative to others in cohortc Binge at least once in past 30 daysc
(continuous counts) (continuous counts) (binary variable) (binary variable)
Exp 95% CI P Exp 95% CI P Odds 95% CI P Odds 95% CI P
Exposure   (Beta)c low high value (Beta)c low high value ratio low high value ratio low high value
Alcohol outlet density in 1.6 km buffer, per 10,000 population
 Quartilesd
  Q1. Lowest 0.0–0.99 Referent Referent Referent Referent
  Q2.   1.0–1.70 0.98 0.82 1.19 0.864 1.02 0.91 1.14 0.728 1.22 0.65 2.32 0.536 1.03 0.64 1.66 0.905
  Q3.   1.71–2.8 1.11 0.93 1.33 0.253 1.21 1.09 1.35 0.001 1.97 1.08 3.62 0.028 0.90 0.56 1.45 0.662
  Q4. Highest 2.9–10.7 1.28 1.08 1.52 0.005 1.34 1.21 1.49 <.0001 1.59 0.87 2.92 0.135 1.19 0.75 1.89 0.464
Distance from participant to nearest off-premise outlet
 Tertiles, kilometerse
  T1. Nearest 0.021–0.622 Referent Referent Referent Referent
  T2.   0.623–1.26 1.00 0.86 1.16 0.993 0.96 0.88 1.05 0.386 0.92 0.56 1.51 0.737 1.09 0.72 1.65 0.674
  T3. Farthest 1.27–10.16 0.81 0.67 0.99 0.038 0.79 0.70 0.88 <.0001 0.58 0.30 1.11 0.100 1.28 0.77 2.12 0.346
  1. Abbreviations: CI confidence interval
  2. aCross-sectional results follow-up, adjusted for age, gender, race/ethnicity, per capita income, educational attainment, history of chronic disease (binary), state. When per-population was not part of the exposure measure, then the model also adjusted for population density within a 1.6 km area (operationalized into quartiles)
  3. bPoisson regression was used to derive these estimates. Beta coefficients represents the difference in the logs of expected drinking days (per week) for discrete exposure category vs. referent category. Exponentiated beta coefficient represents a relative value. Thus, in cross-sectional data the exp.(beta) 1.28 can be interpreted as 28% higher drinking days per month when living in the highest quartile of outlet density (0.29–1.7 per 10,000 population) relative to the lowest quartile (the referent group)
  4. cLogistic regression was used to derived these estimates. High number of drinks refers to high consumption relative to others in cohort (top quintile > = 8 drinks per week). Binge in the past 30 days refers to > = 1 time in past 30 days consumed a large volume of alcohol during a single occasion (> = 5 drinks for males, > = 4 drinks for females). For 5 participants, their baseline binge value was used because their follow-up value was missing
  5. dThe following information attempts to aide interpretation of the quartile groups for alcohol outlet density in a 1.6 km buffer, per 10,000 population. Within each quartile of the standardized count, the median (and P25, P75) of the unstandardized 1.6 km density is as follows: Quartile 1: median 0 outlets (0–1); Quartile 2: median 6 outletS (2, 8), Quartile 3: median 7 outlets (3, 13); Quartile 4: median 11 outlets (4, 25)
  6. eTertitle distances in miles: T1. 0.01–0.386 miles, T2. 0.387–0.78 miles, T3. 0.79–6.31 miles