We consider nonparametric estimation of some regression curves when the data are observed with additive distortion which depends on an observed confounding variable. The unobservable response variable and covariates are both distorted in a additive fashion by unknown distorting functions. We study the estimates of nonparametric mean function and its first derivative, the variance function, the Sharpe ratio function and correlation curve function. We obtain asymptotic normality results for the proposed nonparametric estimators. Monte Carlo simulation experiments are conducted to examine the performance of the proposed estimators. The proposed estimators are applied to analyze a QSAR fish toxicity dataset for an illustration.