Mortality Over Regions and Time - Leading Causes by Area

One row per geographic area, sex, and cause-of-death grouping for the 2019-2023 MORT extract. The table covers 856 Australian geographies across local government areas, statistical areas, primary health networks, remoteness areas, socioeconomic groups, states, and territories, with death counts, rank, percentages, crude rates, age-standardised rates, and rate ratios. The period is a fixed five-year extract, and age-standardised measures are not populated for every row.

aihw-3b7d81af-943f-447d-9d64-9ce220be35e7·12 columns·486 KB·Creative Commons Attribution 4.0 International (CC BY 4.0)·updated 1mo ago
AIHW

Source: AIHW · connector code

Schema

mort_codestring
categorystring
geographystring
periodstring
sexstring
rankint64
cause_of_deathstring
deathsint64
deaths_percentdouble
crude_rate_per_100000double
age_standardised_rate_per_100000double
rate_ratiodouble

Get this dataset on your machine

subsets sync --bundle medium clones the mid-size tiers as queryable local tables — use --bundle large for the widest tier

pip install subsetsio
subsets sync --bundle small # or medium, or large
subsets serve # search + SQL at http://localhost:8080

Free and open — the data syncs straight from the public bucket, and search + SQL run entirely on your machine. See docs →

Query it locally

Full docs →
Bash
subsets serve   # local API on http://localhost:8080
curl -s -X POST "http://localhost:8080/query" \
  -H "Content-Type: application/json" \
  -d '{"sql": "SELECT * FROM \"aihw-3b7d81af-943f-447d-9d64-9ce220be35e7\" LIMIT 5"}'

No account, no API key — the data syncs straight from bundles.subsets.io and every query runs on your machine. See the local API reference.