A record high-but who’s behind it?

In 2022–23, the share of Australians who had recently used an illicit drug reached 15.1%-the highest in two decades. But that headline hides the real story. The rise isn’t being driven by the usual suspects. It’s being driven by young women, who are closing — and in one age group reversing-a gender gap that has held for a generation.

Chart 1-A two-decade high

Source: AIHW NDSHS 2022–23, Table 5.6.

Chart 2-Among 20–29s, the gap is closing

Source: AIHW NDSHS 2022–23, Table 5.8. (Multivariate: year × gender.)

Chart 3-Cocaine: women are catching up

Source: AIHW NDSHS 2022–23, Table 5.65. (Multivariate: year × gender.)

Chart 4-Men still use more of every drug (overall)

Source: AIHW NDSHS 2022–23, Table 5.15. (Multivariate: drug type × gender.)

Chart 5-But among teens, young women now lead

Source: AIHW NDSHS 2022–23, Table 5.8. (Multivariate: age × gender.)

Data & methods

Data are from the AIHW National Drug Strategy Household Survey 2022–23 (illicit drugs supplementary data tables, Tables 5.6, 5.8, 5.15 and 5.65). The raw supplementary tables were reshaped into a tidy long format (year, gender, age group / drug, value) using Python; reliability flags (*, #) were stripped and “n.a.”/“n.p.” set to missing. All visualisations were produced in R with ggplot2 and made interactive with plotly. “Recent use” means use in the previous 12 months.

References

Australian Institute of Health and Welfare. (2025). National Drug Strategy Household Survey 2022–2023 – 5. Illicit drugs. AIHW, Australian Government. https://www.aihw.gov.au/reports/illicit-use-of-drugs/national-drug-strategy-household-survey/data

R Core Team. (2024). R: A language and environment for statistical computing. R Foundation for Statistical Computing. https://www.R-project.org/

Sievert, C. (2020). Interactive web-based data visualization with R, plotly, and shiny. Chapman and Hall/CRC. https://plotly-r.com