Table 5 The predictors of MMG performance.

From: Knowledge and beliefs on breast cancer screening and uptake among Yemeni female school teachers in Malaysia

Variables

COR (95% CI)

P-value

AOR (95% CI)

P-value

Age

1.309 (1.137–1.507)

< 0.001**

1.418 (1.116–1.801)

0.004*

Income

1.002 (1.000–1.003)

0.031**

1.001(0.999–1.003)

0.280

Marital status

Married

1.231 (0.251–6.032)

0.798

  

Single

1.00 (ref)

   

Education

Undergraduate and diploma

0.242 (0.057–1.031)

0.055**

0.397 (0.041–3.821)

0.424

Postgraduate

1.00 (ref)

   

Family history

Yes

2.000 (0.489–8.182)

0.335

  

No

1.00 (ref)

   

Knowledge

1.375 (1.167–1.620)

< 0.001**

1.478 (1.144–1.910)

0.003*

CHBMS subscale

Susceptibility

1.135 (0.921–1.399)

0.233

  

Seriousness

1.076 (0.929–1.246)

0.327

  

Benefit of MMG

1.133 (0.979–1.311)

0.093**

0.892 (0.663–1.201)

0.453

Barriers of MMG

0.639 (0.460–0.887)

0.008**

0.524 (0.263–1.043)

0.066

Motivation

1.063 (0.904–1.250)

0.459

  
  1. *Significant for multiple logistic regression model (p < 0.05), ** Significant for simple logistic regression model (p ≤ 0.25). COR, Crude odds ratio; AOR, adjusted odds ratio; Assumptions of logistic regression have been met and the Hosmer–Lemeshow goodness-of-fit test indicated good fit (X2 = 12.0, p = 0.150); Negelkerke R2 = 0.223, variance inflation factors (VIF) are less than five for all variables included in this model.
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