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 is 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 Excel workbook was read and cleaned entirely in R using readxl and the tidyverse: multi-year and age/gender tables were reshaped into a tidy long format, reliability flags were stripped, and “n.a.”/“n.p.” set to missing. All visualisations were produced 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. AIHW. 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