Factors contributing to the variability observed in duplicate forensic breath alcohol measurement

Abstract

Several factors contribute to the variability observed among repeated measurements of breath alcohol concentration. Identifying these factors and the magnitude of their contribution is the focus of this study. Large breath alcohol data sets consisting of duplicate test results from drivers arrested for driving while intoxicated were obtained from four jurisdictions: Sweden, Alabama, New Jersey and Washington State. The absolute difference between duplicate results were fitted to a multivariate linear regression model which included the following predictor variables: mean breath alcohol concentration, absolute exhalation time difference between repeated measurements, absolute exhalation volume difference, gender and age. In all data sets considered here, the breath alcohol concentration was the most statistically and practically significant predictor of absolute difference between the duplicate results. The next two most important predictors to enter models for all jurisdictions were exhalation volume difference and exhalation time difference. The maximum multivariate R2 for any jurisdiction, however, was only 0.24, suggesting that other factors not considered here may be of importance. Two predictors over which the subject would have some influence included exhalation time and volume. When these were set at values expected to have maximum impact, the effect on duplicate test differences was very small, 0.008 g/210 L or less in all jurisdictions, indicating that subject manipulation of exhalation time and volume would have at most a very small systematic effect on estimated breath alcohol concentration. This study presents multivariate models useful for identifying the impact of five variables that may influence breath test variability.