Table 2.
Binary logistic regression of peripheral neuropathy a
| Model 1 b | Model 2 c | |||||||
|---|---|---|---|---|---|---|---|---|
| OR | 95% CI | P value | OR | 95% CI | P value | |||
| Lower | Upper | Lower | Upper | |||||
| Age | 1.1 | 1.1 | 1.1 | 0.000* | 1.1 | 1.1 | 1.1 | 0.000* |
| Gender | 1.6 | 0.9 | 2.7 | 0.125 | 1.6 | 0.9 | 2.8 | 0.122 |
| Smoking history | 0.7 | 0.3 | 1.9 | 0.522 | 0.8 | 0.3 | 2.0 | 0.588 |
| MetS-IDF d | 2.0 | 1.2 | 3.2 | 0.006* | 1.5 | 0.9 | 2.5 | 0.110 |
| HOMA-IR | / | / | / | / | 1.2 | 1.1 | 1.4 | 0.000* |
aTable 2 showed the binary logistic regression results of peripheral neuropathy. bAge, gender, smoking history and MetS-IDF were taken into the logistic regression equation in model 1.c And in model 2, HOMA-IR was added to the equation based on model 1. dMetS-IDF, metabolic syndrome was defined using the new International Diabetes Federation. e*significantly different in the model (p value < 0.05).