# Table 3 Hierarchical Logistic regression analysis of Health Belief Model factors for predicting BSE practice

VariablesModel 1aModel 2b
B (S.E)WalddfOROR 95% CIpB (S.E)WalddfOROR 95% CIp
Sociodemographic
Age > 40 (ref = age ≤ 40)      .27 (.12)5.4411.321.05–1.65.02
Married (ref = single, widow/divorced)      −.06 (.13).211.95.74–1.20.65
University, high school (ref = primary, secondary school)      .90 (.14)43.612.451.88–3.20<.001
Having history of breast affliction (ref = no)      .60 (.34)3.0611.82.93–3.56.08
Having family with cancer (ref = no)      .49 (.15)10.411.631.21–2.20<.001
HBM constructs
Susceptibility.02(.01)1.8711.02.99–1.04.17.01(.01).7811.01.99–1.04.38
Severity−.01 (.01).771.99.98–1.01.38.00 (.01).00111.99–1.01.98
Benefits.09 (.02)20.2811.11.05–1.14<.001.08 (.02)16.211.091.04–1.13<.001
Barriers−.08 (.01)42.361.93.91–.95<.001−.08 (.01)40.101.93.90–.95<.001
Cues to action−.06 (.01)22.311.94.92–.97<.001−.06 (.01)26.311.94.91–.96<.001
Self-efficacy.36 (.03)176.8911.441.36–1.51<.001.36 (.03)163.9311.431.35–1.51<.001
1. aLogistic regression with HBM constructs, Model χ2 (6) =485.92, p < .001, R2 = .293 (Nagelkerke)
2. bLogistic regression with sociodemographic characteristics + HBM constructs, Model χ2 (11) =553.35, p < .0001, R2 = .328 (Nagelkerke)