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Table 2 Results of logistic regression models for total participant

From: Why is misdiagnosis more likely among some people with rare diseases than others? Insights from a population-based cross-sectional study in China

 

Model 1a

Model 2

Model 3

Model 4

Model 5

OR

95% CIb

OR

95% CI

OR

95% CI

OR

95% CI

OR

95% CI

Rarity-moderate

0.764

(0.503,1.137)

0.857

(0.561,1.286)

1.162

(0.667,1.983)

0.853

(0.555,1.649)

1.329

(0.758,2.289)

Rarity-mild

0.766

(0.487,1.185)

0.901

(0.568,1.411)

0.909

(0.492,2.280)

0.839

(0.531,2.930)

1.110

(0.712,2.2)

Female

  

0.862

(0.721,1.067)

    

0.838

(0.613,1.074)

Non-adult

  

0.503***

(0.414,0.610)

    

0.615**

(0.442,0.852)

Rural Hukou

  

1.059

(0.875,1.287)

    

0.972

(0.73,1.294)

Underdeveloped area

  

1.130

(0.922,1.355)

    

1.043

(0.867,1.503)

Some difficult to access RD information

    

2.543***

(1.679,2.707)

  

2.709***

(1.821,3.997)

Very difficult to access RD information

    

3.915***

(2.852,4.732)

  

4.459***

(3.283,5.615)

No complication

    

0.445***

(0.335,0.590)

  

0.420***

(0.312,0.563)

Close to average local economic level

      

0.887

(0.719,1.092)

1.001

(0.756,1.411)

Above average local economic level

      

0.778*

(0.605,0.999)

1.016

(0.537,2.904)

Family size

      

1.167**

(1.040,1.230)

1.161

(0.999,1.334)

  1. Bold value indicates significant results
  2. Reference groups are Rarity-extremely rare, male, adult, urban hukou, developed area, a little difficult to access RD information, yes complication, below average local economic level
  3. aModel 1 = level of rarity model; Model 2 = demographic model, Model 3 = Healthcare management model; Model 4 = social support model; and Model 5 = Full model
  4. b95% CI 95% confidence interval, OR odds ratio
  5. c*p < 0.05; **p < 0.01; ***p < 0.001