We propose some reasonable approximation methods of substitution and bootstrapping which provide "quick and easy" ways of obtaining confidence intervals of population attributable risk estimates in a case-control study, with or without adjustment for covariates. We compare our proposed methods with previously published standard methods, and demonstrate implementation rising popular statistical software. Simulation results show that the difference in confidence interval width and the coverage probability appeared to be comparable of even greater (better) for some of the proposed methods than for the standard method. In conclusion, the proposed procedures provide useful alternative to the existing maximum likelihood estimator, especially when proportion and odds ratio estimates are obtained from separate sources of data.