Quantifying cause-related mortality in Australia, incorporating multiple causes: observed patterns, trends and...

Area of Science:

• Public Health
• Epidemiology
• Biostatistics

Background:

• Mortality statistics traditionally use a single underlying cause (UC), which is insufficient given rising multimorbidity.
• Additional causes of death are often excluded due to data and methodological complexities.
• This study addresses the need to integrate multiple causes (MC) into mortality indicators.

Purpose of the Study:

• To assess trends and patterns in cause-related mortality in Australia.
• To integrate multiple causes (MC) of death into mortality indicator analysis.
• To compare different methods of cause-related mortality analysis.

Main Methods:

• Utilized Australian death data from 2006-2017 (n=1,773,399).
• Mapped deaths to 136 ICD-10-based groups and applied MC indicators.
• Compared age-standardized rates using single UC (ASRUC), any mention (ASRAM), and weighted multiple causes (ASRW).

Main Results:

• Deaths involved an average of 3.4 causes in 2017, with over 24% involving more than four causes.
• Ischemic heart disease, dementia, and cerebrovascular diseases were leading causes by all methods.
• Hypertension, atrial fibrillation, and diabetes showed significantly higher rates when considering any mention (ASRAM) or weighted multiple causes (ASRW) compared to UC.
• Renal failure, atrial fibrillation, and hypertension emerged as leading causes when using ASRAM and ASRW, but not ASRUC.

Conclusions:

• While leading causes show some overlap, MC analysis highlights preventable diseases.
• MC analyses provide a more comprehensive perspective for population health monitoring.
• Integrating MC data is crucial for effective public health policy development.