Development of the Canadian Substance Use Exposure Database (CanSUED): Modeling the prevalence of substance use in Canadian Jurisdictions, 2006 to 2017
Authors: Zhao Jinhui , Stockwell Tim , Sorge Justin , Sherk Adam , Dorocicz John , Fairbank Jill , Hall Bridget , Kent Pam , Macdonald Scott , Wallingford Sarah , Young Matthew 
Published: February 2020

Background Small area and regional estimates of substance use (SU) exposures are increasingly needed to support estimation of the burden of SU-attributable morbidity and mortality. There is also a need to assess SU prevalence for subgroups by place, time and sociodemographic characteristics to plan the efficient delivery of treatment and harm reduction services. However, the data available from national surveys are often insufficient to produce reliable estimates for subgroups because of small sample sizes. There are also often missing estimates for some jurisdictions and some years when no surveys were conducted. We describe new methods which utilize Canadian national survey data of SU, sales, SU attributable hospitalisations and demographic data to develop the Canadian Substance Use Exposure Database (CanSUED). Estimates from this database have been used in the study of Canadian Substance Use Costs and Harm (CSUCH). Methods Exposures were estimated for eight substance categories: alcohol, tobacco, opioids, cannabis, cocaine, other central nervous system (CNS) stimulants, other CNS depressants and other psychoactive substances. The design-based direct estimates of SU were based on the Canadian Alcohol and Drug Monitoring Survey (CADUMS) in 2008-2012, the Canadian Tobacco, Alcohol and Drug Survey (CTADS) in 2013, 2015 and 2017, per capita alcohol and tobacco sales, and rates of wholly SU-attributable hospitalisations for all Canadian jurisdictions by age and gender. Multilevel models were used to model the design-based estimates of SU to produce reliable estimates for subgroups when the coefficient of variation (CV) of the estimates were > 33.3% and to predict SU exposure in ten provinces in 2006, 2007, 2014 and 2016 and in the three territories for 2006-2017 by using empirical best linear unbiased prediction (EBLUP). Results Direct design-based estimates were based on the surveys from a total of 107,750 Canadians aged 15+. The analyses produced reliable estimates of SU prevalence by year-province-gender-age using mixed models with the EBLUP method. Correlational analyses show that the model-based estimates were significantly related to the design-based estimates produced from both the CADUMS/CTADS and Canadian Community Health Survey. The new model estimates indicate increases in binge drinking, cannabis use, other CNS depressant substance use and cocaine use between 2006 and 2017. Rates of use of opioids and tobacco showed declines. Rates of use of other substances were relatively stable or did not show overall change across the whole time period. Conclusion The mixed model-adjusted approaches produced reliable estimates for small areas and age-gender groups and help fill gaps caused by data suppression in local and national surveys. We suggest that these methods provide the most comprehensive and reliable estimates available of Canadian substance use by substance category, year, jurisdiction, age and gender. The methods could also be applied in other countries where similar data are available.