I'm not exactly sure what you are asking, but a logistic regression slope coefficient of 0 (corresponding to an OR of 1) indicates no relationship. Your regression slope is not significantly different from zero at the .05 level (p = .13), and your 95% CI for the OR therefore includes 1.0. Both these values thus indicate that the relationship is not statistically significantly different from zero.

If your regression slope coefficient were significant at the .05 level (i.e., p < .05), you would expect to see a 95% CI for the OR that does not include 1.0.

Christian is exactly right. Also, your p-value is .130 and not above 1.00. (A p-value above 1.00 would be impossible and would indicate something wrong with the model or the data.)

Thank you for your answer. Just to clarify:

The individual commenting on my model said that since my OR and the upper limits were greater than 1.0 (1.031 and 1.073 respectively), my variable should be statistically significant. According to the p-value (p < 0.5), the issue was that the variable in question was not significant.

Are you staying that since my OR and upper limit include 1.0, albeit 1.031 and 1.073, that indicates the variable is not statistically significant to the model, thus completing the p-value?

Also, I may have to argue with the individual. Do you have any recommended text you can provide me with?

It's not that the upper limit is greater than 1.00, it's that the upper limit is greater than 1.00 and the lower limit is less than 1.00. In other words, the confidence interval contains 1.00, which means you cannot reasonably rule out the possibility that the OR = 1.00. If the p-value was < .05, the 95% CI would exclude 1.00 (i.e., both the upper and lower limits would be above 1.00, or both would be below 1.00). This is fundamental to logistic regression and doesn't need a citation, but if you have to have one, you can use An Introduction to Categorical Analysis by Alan Agresti.

Thank you for your answers! This has been very valuable, I have one more question. While building a logistic regression model, I have a variable whose p-value is < 0.05 (0.047 to be specific) which indicates the variable is a statistically significant addition to the model. However, the Odds ratio and CI(95%) are 0.985 (0.970- 0.999), indicating the variable is not significant. How would you interpret these findings? It seems like one metric contradicts the other.

Actually, the 95% CI confirms statistical significance, because it excludes an OR of 1.000. ORs are interesting both when they exceed 1.000 and when they are less than 1.000, because when they do, they indicate that the odds of one outcome are different than the odds of another outcome. When an OR equals 1.000, the odds of both outcomes are the same.

Keith, FYI your questions can be answered either googling or opening any statistics books: please read the rules of this forum.