Table 2

Univariable and multivariable associations for presence of retailer and retailer density by sociodemographic indicators

	Model 1			Model 2				Model 3			Model 4
	Univariable logistic regression for presence of retailer			Univariable linear regression for log of retailer density				Multivariable logistic regression for presence of retailer			Multivariable linear regression for log of retailer density
Variable	Estimate	95% CI	P value	Estimate	95% CI	P value	Cohens f	Estimate	95% CI	P value	Estimate	95% CI	P value	Cohens f
Median income, €1000	0.866	0.834 to 0.9	<0.001	0.907	0.896 to 0.918	<0.001	0.496	0.542	0.481 to 0.608	<0.001	0.956	0.929 to 0.984	0.002	0.506
% in lowest income category	1.071	1.041 to 1.103	<0.001	1.059	1.051 to 1.068	<0.001	0.422	0.884	0.836 to 0.933	<0.001	1.028	1.014 to 1.042	<0.001	0.068
% unemployed	1.186	1.142 to 1.234	<0.001	1.037	1.027 to 1.047	<0.001	0.214	1.063	1.01 to 1.12	0.020	0.976	0.964 to 0.987	<0.001	0.117
% with higher education	1.020	1.007 to 1.033	0.002	0.974	0.971 to 0.978	<0.001	0.433	1.139	1.102 to 1.178	<0.001	0.982	0.976 to 0.989	<0.001	0.144
Population density, 1000 s per square kilometre								2.903	1.843 to 4.909	<0.001	1.033	1.004 to 1.063	0.023	0.068

Estimates are exponentiated and can be interpreted as multiplicative differences in OR and density, given 1 unit change in predictor.