A study to estimate and correlate cigarette smoke exposure in smokers in Germany as determined by filter analysis and biomarkers of exposure.

A clinical study, conducted in Germany, compared two methods of estimating exposure to cigarette smoke. Estimates of mouth level exposure (MLE) to nicotine, 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK), pyrene and acrolein were obtained by chemical analysis of spent cigarette filters for nicotine content. Estimates of smoke constituent uptake were achieved by analysis of corresponding urinary biomarkers: for nicotine; total nicotine equivalents (nicotine, cotinine, trans-3'-hydroxycotinine plus their glucuronide conjugates), for NNK; (4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (NNAL) plus glucuronide, for pyrene; 1-hydroxy pyrene (1-OHP) plus glucuronide and for acrolein; 3-hydroxylpropyl-mercapturic acid (3-HPMA) plus the nicotine metabolite cotinine in plasma and saliva. Two hundred healthy volunteer subjects were recruited; 50 smokers of each of 1-2 mg, 4-6 mg and 9-10 mg ISO tar yield cigarettes and 50 non-smokers (NS). Smokers underwent two periods of home smoking, each followed by residence in a clinic. Smoking was permitted ad libitum, and spent cigarette filters, cigarette consumption data, 24h urine, as well as plasma and saliva samples were collected. Significant correlations (p<0.001) were found between MLE and the relevant biomarker for each smoke constituent. The Pearson correlation coefficients (r) were 0.83 (nicotine), 0.76 (NNK), 0.82 (acrolein) and 0.63 (pyrene). Mean MLE estimates for nicotine, NNK and pyrene showed a dose response in line with ISO tar yield smoked, with 10 mg > 4 mg >1 mg, and for acrolein 10 mg> 4 mg > *1mg (where * indicates not significant at 95% confidence level). The mean exposure estimates from biomarkers for nicotine, NNK and acrolein also showed a dose response in line with ISO tar yield with 10 mg > 4 mg > 1 mg > NS, and for pyrene 10 mg > *4 mg> 1 mg> NS. This study shows that estimates of exposure obtained by filter analysis and biomarkers of exposure correlate significantly over a wide range of smoke exposures and that filter analysis may provide a simple and effective alternative to biomarkers for estimating smokers' exposure.