Table 2 Predictors associated with the logistic regression model
From: Predictive models for diabetes mellitus using machine learning techniques
Variables | Estimated coefficient | Odds ratio | 95% CI for odds ratio | P Value |
|---|---|---|---|---|
Intercept | −11.816 | < 0.0001 | ||
Age | ||||
Middle-Aged (40–64) | (Reference) | 1.000 | ||
Elderly (85–90) | −0.829 | 0.436 | (0.31, 0.61) | < 0.0001 |
Senior (65–84) | −0.127 | 0.881 | (0.78, 0.99) | 0.036 |
Young (< 40) | 0.238 | 1.269 | (0.90, 1.79) | 0.170 |
Male | −0.250 | 0.779 | (0.69, 0.88) | < 0.0001 |
FBS | 1.963 | 7.122 | (6.45, 7.87) | < 0.0001 |
BMI | 0.023 | 1.024 | (1.01, 1.03) | < 0.0001 |
HDL | −0.894 | 0.409 | (0.34, 0.49) | < 0.0001 |
TG | 0.158 | 1.171 | (1.09, 1.26) | < 0.0001 |
sBP | −0.001 | 0.999 | (0.96, 1.00) | 0.560 |
LDL | −0.011 | 0.990 | (0.93, 1.05) | 0.740 |