A number is never just a number when it shows a life lost. My interest in this topic is personal: I battled COVID-19 and spent 12 days in hospital. During that time, I saw fear, sadness, hope and loss up close. It made me think about health not only as an individual experience, but as something that shapes families and communities.
That experience left me with a question: what can the pattern of deaths recorded across Australia tell us about the health challenges the country faces? To explore it, I turned to the Australian Bureau of Statistics (ABS) underlying causes-of-death data for 2015–2024. The five visualisations that follow move from a snapshot of the latest year to a longer view of how major causes changed across the decade.
These figures cannot tell the whole story behind any death, and counts alone do not measure a person’s risk of dying. But they can help us see which causes account for the largest numbers, where patterns shift, and which questions deserve closer attention.
Start with the latest year: if we compare the six largest cause-of-death chapters side by side, which ones take up the most space? Neoplasms—the broad ICD-10 chapter that contain cancers—make up about 35.1% of the deaths illustrated in this chart. Diseases of the circulatory system follow at about 28.1%. The remaining slices belong to respiratory diseases, external causes, nervous system diseases, and mental and behavioural disorders.
The first message is the size of the gap: the two largest categories account for much more of this selected group than any of the others. One important detail, though: these percentages describe only the six chapters shown, not every death recorded in Australia. To understand whether this snapshot reflects a lasting pattern or a change in the making, we need to look back across the decade.
The snapshot becomes more revealing when we follow the same six chapters from 2015 to 2024. Neoplasms remain the largest category in the chart and trend upward overall. Diseases of the circulatory system also account for many deaths, but their line moves differently, with fluctuations across the period. The other chapters follow their own paths rather than rising or falling together.
So there is no single story shared by every cause. Some categories change gradually; others fluctuate more noticeably. This chart shows recorded counts, not age-standardised mortality rates, and it cannot explain why a line changes. One category’s rise is especially clear, so next we zoom in on it.
A closer look at one of the largest categories helps explain why its decade-long line deserves attention.
The line for neoplasms is worth a closer look. Recorded deaths stayed close to the same level from 2015 to 2017, rose in 2018 and 2019, dipped in 2020, and then climbed in each year from 2021 through 2024. The count rose from 46,640 in 2015 to 52,819 in 2024—an increase of about 13.3% across the period.
That is a clear change in the number of deaths recorded, but it is not proof that an individual’s risk rose by the same amount. Population size and age structure matter, and this chart shows counts rather than age-standardised rates. With that caution in mind, the next question is how this category compares with the wider range of causes in the latest year.
The top two categories do not tell the whole story. Ranking the ten largest chapters in 2024 brings the next group into view: respiratory diseases sit behind the top two, while external causes, nervous system diseases, and mental and behavioural disorders also appear among the largest categories.
The horizontal bars make the differences easier to compare at a glance. They also remind us that “largest” here means the number of deaths recorded, not the level of risk for an individual. We have seen the latest-year ranking and the decade-long trend; to bring those views together, the final chart compares the same six leading chapters at the two ends of the period.
This final comparison strips the decade back to two points in time: 2015 and 2024. Neoplasm deaths increased from 46,640 to 52,819, while the recorded count for diseases of the circulatory system fell. The other four chapters selected because they were among the six largest in 2024—respiratory diseases, external causes, nervous system diseases, and mental and behavioural disorders—also recorded higher counts in 2024 than in 2015.
The slopes make one thing clear: the leading categories did not all move in the same direction. This is a comparison of recorded counts at two endpoints, not a measure of individual risk and not an explanation for the changes. It is a final view of how different the paths can be even among the most prominent causes of death.
There is an important boundary around this story. The dataset reports recorded death counts, not individual-level mortality risk or age-standardised mortality rates. Counts can be influenced by population size and age structure, so they should not be read as direct measures of a person’s chance of dying.
The ABS may also revise figures from different years, and broad ICD-10 chapters should not be added indiscriminately to detailed subcategories. These charts can show what changed in the recorded data; they cannot, by themselves, establish why it changed.
I began with a personal question about what public health data might help us understand. The five views offer part of an answer: neoplasms account for the largest recorded count among the selected broad chapters, circulatory diseases remain another major category, and the leading causes have not all followed the same path between 2015 and 2024.
The data cannot explain every rise or fall, and counts are not the same as individual risk. But they give us a clearer map of the questions worth asking next. Behind each number is a person, a family, and a community—one reason these patterns deserve careful attention rather than a quick glance.
Australian Bureau of Statistics. (2025). Causes of Death, Australia, 2024. Australian Government. https://www.abs.gov.au/statistics/health/causes-death/causes-death-australia
James Baglin. (2025). Storytelling with data. Data Visualisation. https://data-visualisation.stem.melbourne/storytelling-with-data.html
James Baglin. (2025). Grammar and vocabulary. Data Visualisation. https://data-visualisation.stem.melbourne/grammar-and-vocabulary.html
James Baglin. (2025). Multivariate strategies. Data Visualisation. https://data-visualisation.stem.melbourne/multivariate-strategies.html
James Baglin. (2025). Accessibility and deception. Data Visualisation. http://data-visualisation.stem.melbourne/accessibility-and-deception.html
James Baglin. (2025). Adding interactivity. Data Visualisation. https://data-visualisation.stem.melbourne/adding-interactivity.html
I used ChatGPT by OpenAI to improve the clarity of my writing and correct spelling and grammatical errors. I reviewed the suggestions carefully and checked their accuracy before incorporating them into my assignment.