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Table 5 Logistic regression main effects and interactions of neighborhood poverty and primary payer on breast cancer stage at diagnosis

From: Mediation of the effects of living in extremely poor neighborhoods by health insurance: breast cancer care and survival in California, 1996 to 2011

 

Node negative disease

Tumor < 20 mm

Predictor Variables

Sample

OR

(95% CI)

Sample

OR

(95% CI)

Single predictor models

Neighborhood poverty

  < 5% poor

1,833 

1.00

 

1,704 

1.00

 

  5-29% poor

1,760 

0.94

(0.81, 1.08)

1,639 

0.88*

(0.75, 1.02)

  ≥ 30% poor

1,723 

0.75

(0.65, 0.88)

1,575 

0.61

(0.52, 0.71)

Primary payer

  Uninsured or Medicaid

888 

1.00

 

796 

1.00

 

  Medicare or private

4,428 

1.42

(1.21, 1.65)

4,122 

1.37

(1.16, 1.61)

Full models

Neighborhood poverty

  < 5% poor

1,833 

1.00

 

1,704 

1.00

 

  5-29% poor

1,760 

1.27

(0.88, 1.84)

1,639 

0.89

(0.76, 1.04)

  ≥ 30% poor

1,723 

1.06

(0.74, 1.52)

1,575 

0.63

(0.54, 0.73)

Primary payer

  Uninsured or Medicaid

888 

1.00

 

796 

1.00

 

  Medicare or private

4,428 

1.73

(1.23, 2.44)

4,122 

1.23

(1.04, 1.45)

  Poverty by payer

5,316 

0.72*

(0.49, 1.06)

4,918 

1.16a

(0.93, 1.45)

Poverty by payer interaction on node negative disease at diagnosis

 

> 5% poor

< 5% poor

Predictor Variables

Sample

OR

(95% CI)

Sample

OR

(95% CI)

Primary payer

  Uninsured or Medicaid

730 

1.00

 

158 

1.00

 

  Medicare or private

2,753 

1.28

(1.07, 1.53)

1,675 

1.76

(1.25, 2.48)

  1. Notes. OR = odds ratio, CI = confidence interval. All effects were age and grade-adjusted across these categories: 25–44, 45–54, 55–64, 65–74 and 75 or older; and well, moderately or poorly differentiated. Bolded ORs were statistically significant at p < .05.
  2. a Null interaction was removed from the full model. *p < .10.