About the Prevalence Chart

In recent decades, estimates of how many people in Canada use various legal and illegal substances (known as the prevalence) have relied on self-report surveys. While valuable, these surveys only offer snapshot estimates for a particular year, often vary in methodology, and frequently skip years or exclude key regions. As a result, assessing trends in substance use over time is challenging.

To address this, the Canadian Substance Use Costs and Harms (CSUCH) study developed and applied a methodology to model consistent estimates of the annual prevalence across eight substance categories (alcohol, tobacco, cannabis, opioids, other central nervous system [CNS] depressants, cocaine, other CNS stimulants and any other psychoactive substances).

The Substance Use Prevalence Interactive Chart is the only national resource that provides modelled estimates of substance use across Canadian provinces and territories by age, sex and year, spanning from 2008 to 2024. They fill critical gaps left by national surveys, which often miss certain years or jurisdictions and underrepresent key population subgroups due to, for example, small sample sizes or the suppression of data (meaning data are withheld to protect people’s privacy and ensure no individual or organization can be identified from the published numbers).

The new estimates fill critical gaps left by national surveys, which often miss certain years or jurisdictions and underrepresent key population subgroups due to, for example, small sample sizes or the suppression of data (meaning data are withheld to protect people’s privacy and ensure no individual or organization can be identified from the published numbers).

Understanding substance use trends by region, time and demographic groups can help inform evidence-based policy decisions and direct resource allocation for prevention, treatment and harm reduction efforts.

Interpret the 2024 estimates with caution. They are based on linear extrapolation methods using data from 2014 to 2023 and they may not reflect actual observed values.