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Table 3 Backward logistic regression models for prediction of good sleepers divided by age group, and their performance of prediction

From: Prevalence and impacts of poor sleep on quality of life and associated factors of good sleepers in a sample of older Chinese adults

  All participants Age 60-69 Age 70-79 Age 80+
  (  n = 301) (  n = 58) (  n = 135) (  n = 108)
Constant (Odds ratio) 0.015 0.0002 0.0008 0.029
Dependent variable Bodily Pain Vitality Physical Functioning Bodily Pain
(Odds ratio, 95% confidence interval) (1.019** (1.007, 1.032)) (1.051* (1.004, 1.099)) (1.046* (1.000, 1.097)) (1.033** (1.012, 1.054))
  Vitality Role-Emotional Vitality  
  (1.025** (1.009, 1.041)) (1..046 (0.995, 1.099)) (1.037* (1.007, 1.067))  
Classification rate 0.71 0.74 0.73 0.69
Sensitivity 0.51 0.64 0.48 0.54
Specificity 0.77 0.77 0.79 0.74
AUC 0.72### 0.79## 0.77### 0.72##
  1. Variables that show significant association with good sleepers were included in the backward logistic regression model.
  2. The dependent variables were sorted according to ascending level of significance.
  3. AUC: area under the receiver operating characteristic curve (≥0.7: good prediction).
  4. */**/*** significant at the 5%, 1%, and 0.1% level respectively.
  5. #/##/### significantly different from 0.5 at the 5%, 1%, and 0.1% level respectively.
  6. Dependent variable: good sleeper = 1; poor sleeper = 0.