Table 2.

Logistic regression model

	Model 1*			Model 2†
	OR	95% CI	p Value	OR	95% CI	p Value
Urban status
Suburban	Ref	–	–	Ref	–	–
Urban	1.027	0.925 to 1.142	0.6142	1.116	0.995 to 1.142	0.0610
Rural	0.567	0.477 to 0.673	<0.0001	0.488	0.398 to 0.598	<0.0001
Insurance coverage
Yes	Ref	–	–	Ref	–	–
No	1.231	1.102 to 1.371	0.0002	1.319	1.160 to 1.500	<0.0001
Age group
Under 40	0.330	0.151 to 0.721	0.0054	0.335	0.149 to 0.752	0.0080
40–50	Ref	–	–	Ref	–	–
50–65	1.118	1.007 to 1.240	0.0364	1.150	1.026 to 1.289	0.0163
Over 65	1.124	0.932 to 1.355	<0.0001	1.160	0.925 to 1.454	0.1980
Race
Caucasian	Ref	–	–	Ref	–	–
African-American	1.545	1.390 to 1.717	<0.0001	1.261	1.108 to 1.436	0.0005
Marital status
Married	Ref	–	–	Ref	–	–
Not currently married	1.300	1.154 to 1.465	<0.0001	1.105	0.968 to 1.262	0.1379
Baseline mammography experience
Very bad	2.171	1.085 to 4.343	0.0284	1.544	0.739 to 3.224	0.2475
Okay	1.107	0.923 to 1.327	0.2723	0.948	0.780 to 1.152	0.5907
Good	Ref	–	–	Ref	–	–
Great	0.879	0.789 to 0.987	0.0207	0.974	0.866 to 1.096	0.6652
Employed
Yes	Ref	–	–	Ref	–	–
No	0.828	0.747 to 0.918	0.0003	0.857	0.765 to 0.961	0.0084
Year at first screening	0.681	0.661 to 0.703	<0.0001	0.664	0.643 to 0.687	<0.0001

*Unadjusted Model.

†Adjusted Model.