Identifying saddle points of a constrained nonlinear function with three variables

Question

I know that if the Hessian matrix of a multivariable function at a given stationary point has both positive and negative eigenvalues then that stationary point must be a saddle point. Does the same hold with multivariable optimization problems with only a single linear equality constraint where a reduced Hessian matrix has been calculated?