Trying to understand and correlate the meaning of OR and p value in the univariate logistic regression

Dear members,
Just a newbie to statistics. Request your help with understanding this table below


I have serious doubt in the results of statistics that I have done with regard to the odds ratio and p value that I obtained. My question is that how come that when the OR
is low the p value is significant. For example, take the tablet above, when the OR for age is 0.99, the p value is 0.050 whereas when the OR for Albumin in 2.094 the p is 0.171 ie not significant

These figures conflict with my understanding of OR and p value. How can an event with high OR have low p value and vice versa. Which should I give more importance to OR or p value?

Thanks a lot


Less is more. Stay pure. Stay poor.
It would greatly help if you put confidence intervals on your estimates. Correct, intuitively one would assume estimates larger in magnitude would be more likely beyond chance, but without seeing your data or CI's that may not hold for this sample if say you had sparsity (e.g., imbalanced data in regards to a covariate) or collinearity, etc.


Less is more. Stay pure. Stay poor.
What is the prevalence of the outcome. Six predictors is a crap load for a n=110, that is also part of your problem. Do you see how when the CIs cross one, the pvalues > 0.05, that is what you aren't suppose to use pvalues, they miss the point.