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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