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Table 5 Logistic regression model: influencing factors on the utilisation of clinical cancer prevention screenings among women with and without obesity

From: Cancer prevention in females with and without obesity: Does perceived and internalised weight bias determine cancer prevention behaviour?

 

Pap smear (women aged ≥ 20

Clinical breast examination (women aged ≥ 30)

Mammography* (women aged ≥ 50)

Faecal occult blood test* (women aged ≥ 50)

Colonoscopy* (women aged ≥ 55)

OR

p

[95% CI]

OR

p

[95% CI]

OR

p

[95% CI

OR

p

[95% CI

OR

p

95% CI

Weight Status1

0.63**

.004

(0.46–0.86)

0.61**

.003

(0.44–0.85)

1.11

.564

(0.78–1.58)

1.28

.189

(0.89–1.85)

0.67

.056

(0.44–1.01)

Cancer awareness

 Current/previous (other) cancer diagnosis in participants2

2.34**

.008

(1.24–4.39)

2.20*

.017

(1.15–4.21)

3.84***

 < .001

(2.09–7.05)

0.78

.402

(0.43–1.40)

2.83**

0.003

(1.41–5.66)

 Current/previous (other) cancer in participant’s environment3

1.19

.336

(0.83–1.71)

1.35

.109

(0.94–1.95)

1.36

.134

(0.91–2.04)

1.25

.325

(0.80–1.93)

1.64*

.039

(1.03–2.63)

 CPS knowledge4

2.26***

 < .001

(1.65–3.10)

2.35***

.001

(1.44–3.85)

1.39

.066

(0.98–1.97)

1.55*

.023

(1.06–2.27)

4.05***

 < .001

(2.68–6.13)

Confounding variables

 Health Insurance5

1.86*

.043

(1.02–3.41)

2.06*

.035

(1.05–4.04)

0.72

.259

(0.41–1.27)

2.10**

.010

(1.20–3.70)

2.27*

.018

(1.15–4.49)

 Age

0.97***

 < .001

(0.95–0.99)

0.98**

.009

(0.96–0.99)

0.84***

 < .001

(0.81–0.88)

0.87***

 < .001

(0.84–0.91)

1.14***

 < .001

(1.07–1.22)

 Educational Level6

0.81

.256

(0.58–1.12)

0.81

.222

(0.58–1.13)

.82

.280

(0.57–1.18)

1.01

.964

(0.69–1.47)

0.98

.945

(0.64–1.51)

 Marital status7

1.48*

.013

(1.09–2.02)

1.55

.002

(1.13–2.13)

1.13

.476

(0.80–1.61)

1.15

.441

(0.80–1.66)

1.24

.301

(0.82–1.86)

 Household income8

  2. Quartile

1.27

.186

(0.84–1.93)

1.55*

.039

(1.08–2.47)

1.19

.481

(0.73–1.95)

1.25

.409

(0.74–2.12)

1.12

.713

(0.62–2.01)

  3. Quartile

1.25

.264

(0.80–1.95)

1.53

.063

(1.02–2.48)

0.98

.921

(0.59–1.60)

1.62

.074

(0.95–2.76)

1.27

.419

(0.71–2.29)

  4. Quartile

1.14

.546

(0.73–1.78)

1.94**

.006

(1.21–3.09)

1.12

.660

(0.68–1.82)

1.55

.104

(0.91–2.61)

1.02

.947

(0.58–1.79)

n

910

  

891

  

642

  

638

  

475

  

Prob > chi2

 < 0.001

  

 < 0.001

  

 < 0.001

  

 < 0.001

  

 < 0.001

  

Pseudo R2

0.07

  

0.06

  

0.13

  

0.09

  

0.15

  
  1. Bold indiciates the siginnificant values: ***p ≤ 0.001, **p ≤ 0.01, *p ≤ 0.05
  2. *Women who reported a current breast (n = 5) or colorectal (n = 1) cancer diagnosis were excluded in the corresponding models since diagnostic procedures or interventions could have been misclassified as CPS behaviour. Outcome variable sufficient utilisation cancer screenings (0 = not sufficient, 1 = sufficient); OR Odds ratios
  3. 10 = not obese, 1 = obese
  4. 2–40 = no, 1 = yes
  5. 50 = statutory health insurance, 1 = private health insurance
  6. 60 = less than 12 years of education
  7. 70 = not married or not living together, 1 = married and living together
  8. 8Reference category (= 0): first quartile
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