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Table 3 Remoteness and patients’ socio-economic characteristics: univariate and multilevel logistic regression analysis as predictive factors of being operated on by a high-volume breast cancer surgeon

From: For patients with breast cancer, geographic and social disparities are independent determinants of access to specialized surgeons. A eleven-year population-based multilevel analysis

  Univariate logistic regression analysis Multilevel logistic regression analysis
  Odds ratio (95 % CI*) p-value Odds ratio (95 % CI*) p-value
Individual data     
Age     
< 50 years old 0.90 (0.76; 1.07) <0.001   0.179
50 to 74 years old 1  
> 74 years old 0.68 (0.55; 0.83)  
T Stage - size     
T1 1 <0.001   0.189
T2 0.79 (0.66-0.95)  
T3 and T4 0.58 (0.41-0.81)  
Circumstances of diagnosis     
Screening 1 <0.001 1 0.005
Not screening 0.72 (0.62; 0.83) 0.78 (0.66-0.93)
Time to go to the nearest reference cancer care centre     
< 10 minutes 1 <0.001 1 <0.001
10 to 20 minutes 0.98 (0.80; 1.21) 0.86 (0.68-1.07)
20 to 35 minutes 0.70 (0.56; 0.88) 0.56 (0.43-0.73)
> 35 minutes 0.50 (0.42; 0.61) 0.38 (0.29-0.50)
Aggregate data     
Place of residence     
Rural 0.72 (0.62; 0.84) <0.001 0.68 (0.53-0.87) 0.002
Urban 1 1
Townsend index     
Quintile 1 (most affluent) 1 <0.001 1 0.013
Quintile 2 0.84 (0.60; 1.18) 0.84 (0.58-1.21)
Quintile 3 0.73 (0.52; 1.03) 0.74 (0.52-1.08)
Quintile 4 0.67 (0.49; 0.93) 0.69 (0.48-0.97)
Quintile 5 (most deprived) 0.65 (0.49; 0.88) 0.61 (0.44-0.85)
  1. * CI: Confidence Interval.