Related Experiment Video
Updated: Feb 28, 2026
Fetal Mouse Cardiovascular Imaging Using a High-frequency Ultrasound 30/45MHZ System
Published on: May 5, 2018
Using big data to search for possible geographic clustering of Congenital Heart Disease (CHD) across Australia
Calum Nicholson1,2,3, Geoff Strange1,2,3, David S Celermajer1,2,3
1University of Sydney, Camperdown, New South Wales, Australia.
Insights
Geographic analysis of Congenital Heart Disease (CHD) in Australia reveals its distribution mirrors the general population. This suggests spatial clusters are unlikely to stem from genetic or environmental factors.
Area of Science:
- Cardiology
- Epidemiology
- Geographic Health Analysis
Background:
- The causes of Congenital Heart Disease (CHD) are not fully understood.
- Previous geographic analyses of CHD have lacked large, national datasets.
- Understanding disease distribution can offer insights into genetic and environmental influences.
Purpose of the Study:
- To analyze the geographic distribution of structural Congenital Heart Disease (CHD) cases in Australia.
- To determine if CHD distribution correlates with the general Australian population.
- To assess the likelihood of spatially driven genetic or environmental causes for CHD.
Main Methods:
- Utilized data from the Australia and New Zealand CHD Registry for individuals with structural CHD.
- Geocoded addresses of living individuals by linking with the National Death Index.
- Aggregated CHD case data to standardized geographic regions and compared with Australian population data, considering remoteness and hospital proximity.
Main Results:
- Analyzed 63,863 geocoded individuals with structural CHD out of 81,349 in the registry.
- Found that the geographic distribution of the CHD population closely follows the general Australian population.
- Observed a strong positive correlation between Australian and CHD populations, with only 6% of areas showing proportional differences.
Conclusions:
- The geographic distribution of Congenital Heart Disease (CHD) proportionally mirrors the general Australian population.
- Evidence suggests that CHD spatial clustering is unlikely to be driven by specific genetic or environmental factors.
- Further research may explore other etiological factors beyond geographic distribution.
Abstract:
Several diseases show geographic clustering, giving insights into possible genetic and environmental causes. The pathogenesis of Congenital Heart Disease (CHD) remains largely unknown and analysis of geographic distribution of CHD cases lacks input from large, national-scale datasets. People with structural CHD were selected from the Australia and New Zealand CHD Registry. Of people known to be still living, from linkage with the National Death Index, addresses were geocoded and aggregated to standardised geographic regions with measures of the Australian population. Areas were described based on measures of their remoteness and driving time to hospitals. The relationship between the distribution of the CHD and Australian populations was compared with bivariate spatial correlation. Of 81,349 people with structural CHD in the Registry, 63,863 were still living and could be geocoded. Overall, most people lived in Major Cities, and within 1-hour drive from a hospital, with the proportion the same across the CHD population, the "complex CHD" population and the Australian population. Across the country, there was a strong positive correlation between the Australian population and the CHD population. There were only a small number of areas (6%) where the Australian and the CHD populations were proportionally different. Overall, there was clear evidence that the geographic distribution of the CHD population proportionally follows the general Australian population. This suggests that there is unlikely to be any spatial clusters that are driven by genetic or environmental causes.
More Related Videos
08:28Analysis of Congenital Heart Defects in Mouse Embryos Using Qualitative and Quantitative Histological Methods
Published on: March 10, 2020
13:07Optical Coherence Tomography Based Biomechanical Fluid-Structure Interaction Analysis of Coronary Atherosclerosis Progression
Published on: January 15, 2022
