Table 2.

Relationship of retail policy adoption to tobacco use, sociodemographic, policy context, and program characteristics.

Predictor	Odds ratio	95% CI
Demography
Adult smoking rate (%)	0.707	[0.551; 0.908]
African American pop. (%)	0.917	[0.843; 0.996]
Median household income ($10,000s)	0.647	[0.328; 1.277]
Policy & program context
Excise tax, weighted ($)	5.977	[1.383; 25.826]
Licensing preemption: Yes	0.007	[0.000; 0.146]
Smoke-free air preemption: Yes	0.081	[0.009; 0.714]
Majority Party 2012: Republican	0.030	[0.003; 0.341]
Limited program capacity: Yes	0.021	[0.002; 0.295]
Performed store assessments: Yes	6.667	[1.113; 39.931]
Log-likelihood (df = 10)	−23.728
Observations correctly predicted (%)	81.250
Observations	80

Notes: Odds ratio estimates and intervals that did not include 1.0 are in bold. Odds ratios for binary variables (the bottom 5 variables) indicate the predicted difference in the odds of policy adoption for the absence of the condition vs its presence. For example, localities with tobacco retailer licensing preemptions in place were 143 times less likely (1/0.007) than those without licensing preemptions to adopt a policy, while localities that had performed store assessments were over 6 times more likely (6.667/1) to adopt a policy than those who had not. The odds ratios for smoking rate and African American population indicate the predicted difference or increase in odds when either percentage increases by one; the odds ratio for weighted excise tax is for a difference or increase of one dollar; odds ratio for median household income if for a difference or increase of $10,000.