i made different models . in first I took a dependent variable and four independent variables . in second model I took different dependent variable and similar independent variable like wise I made four models but when I ran binary logistic regression I found similar p values in all models despite of different dependent variables could this happen or am I making any mistake actually I code the dependent variable as 0 and 1 in all models and independent variables in all models are same as bmi, whr, age and % body fat then p values in binary logistic regression become similar I am confused here rather the dependent variables are also linked with each other but in original test results they have different values
"Similar" p values can certainly happen, especially if the dependent variables are related to each other.
However, without seeing your code it's not possible to say for sure what you did or whether it was a mistake.
E.g. suppose one DV was "Voted for McCain" and another was "Voted for Romney" and another was "Voted for Obama in 2008". Those would give very similar p values.
I don't think you're necessarily making a mistake. One possibility is that the different sets of independent variables that you're choosing are heavily correlated to each other (across different sets).