Caleb J Banta-Green1, Alex J Brewer2, Christoph Ort3, Dennis R Helsel4, Jason R Williams5, Jennifer A Field6. 1. Alcohol and Drug Abuse Institute, University of Washington, Seattle, WA 98105, United States. Electronic address: calebbg@uw.edu. 2. Department of Environmental Toxicology, Oregon State University, Corvallis, OR 97331, United States; Department of Chemistry, Central Washington University, Ellensburg, WA 98926, United States. 3. Eawag, Swiss Federal Institute of Aquatic Science and Technology, CH-8600 Dübendorf, Switzerland. 4. Practical Stats, Castle Rock, CO 80109, United States. 5. Alcohol and Drug Abuse Institute, University of Washington, Seattle, WA 98105, United States. 6. Department of Environmental Toxicology, Oregon State University, Corvallis, OR 97331, United States.
Abstract
AIM: Analysis of wastewater samples can be used to assess population drug use, but reporting and statistical issues have limited the utility of the approach for epidemiology due to analytical results that are below the limit of quantification or detection. Unobserved or non-quantifiable-censored-data are common and likely to persist as the methodology is applied to more municipalities and a broader array of substances. We demonstrate the use of censored data techniques and account for measurement errors to explore distributions and annual estimates of the daily mean level of drugs excreted per capita. MEASUREMENTS: Daily 24-hour composite wastewater samples for 56days in 2009 were obtained using a random sample stratified by day of week and season for 19 municipalities in the Northwest region of the U.S. METHODS: Methamphetamine, benzoylecgonine (cocaine metabolite), 3,4 methylenedioxymethamphetamine (MDMA), methadone, oxycodone and hydrocodone were identified and quantified in wastewater samples. Four statistical approaches (reporting censoring, Maximum Likelihood Estimation, Kaplan-Meier estimates, or complete data calculations) were used to estimate an annual average, including confidence bounds where appropriate, dependent upon the amount of censoring in the data. FINDINGS: The proportion of days within a year with censored data varied greatly by drug across the 19 municipalities, with MDMA varying the most (4% to 94% of observations censored). The different statistical approaches each needed to be used given the levels of censoring of measured drug concentrations. Figures incorporating confidence bounds allow visualization of the data that facilitates appropriate comparisons across municipalities. CONCLUSIONS: Results from wastewater sampling that are below detection or quantification limits contain important information and can be incorporated to create a more complete and valid estimate of drug excretion.
AIM: Analysis of wastewater samples can be used to assess population drug use, but reporting and statistical issues have limited the utility of the approach for epidemiology due to analytical results that are below the limit of quantification or detection. Unobserved or non-quantifiable-censored-data are common and likely to persist as the methodology is applied to more municipalities and a broader array of substances. We demonstrate the use of censored data techniques and account for measurement errors to explore distributions and annual estimates of the daily mean level of drugs excreted per capita. MEASUREMENTS: Daily 24-hour composite wastewater samples for 56days in 2009 were obtained using a random sample stratified by day of week and season for 19 municipalities in the Northwest region of the U.S. METHODS:Methamphetamine, benzoylecgonine (cocaine metabolite), 3,4 methylenedioxymethamphetamine (MDMA), methadone, oxycodone and hydrocodone were identified and quantified in wastewater samples. Four statistical approaches (reporting censoring, Maximum Likelihood Estimation, Kaplan-Meier estimates, or complete data calculations) were used to estimate an annual average, including confidence bounds where appropriate, dependent upon the amount of censoring in the data. FINDINGS: The proportion of days within a year with censored data varied greatly by drug across the 19 municipalities, with MDMA varying the most (4% to 94% of observations censored). The different statistical approaches each needed to be used given the levels of censoring of measured drug concentrations. Figures incorporating confidence bounds allow visualization of the data that facilitates appropriate comparisons across municipalities. CONCLUSIONS: Results from wastewater sampling that are below detection or quantification limits contain important information and can be incorporated to create a more complete and valid estimate of drug excretion.