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Geographic distribution of cardiometabolic risk factors: a small area level approach

Conference Paper


Abstract


  • Introduction: Cardiovascular diseases (CVDs) are the leading cause of death and disability in Australia. Centralised approaches for prevention of CVDs may not suit regional requirements as the risk distribution at smaller regions may significantly differ from larger areas. Understanding the small-area geographic distribution of cardiometabolic risk factors (CMRFs) can inform resource planning and provision of preventive services based on actual need, and can aid in subsequent regional policy developments.

    Methods: A cross-sectional hierarchical design and geospatial methods were used to estimate and map the small-area geographic variability in CMRFs. Test results on selected CMRFs such as diabetes, hyperlipidaemia, chronic kidney disease and high BMI recorded between 2012 and 2016 were extracted from the Southern.IML Research (SIMLR) database, which is a major laboratory network database across the Illawarra Shoalhaven region of NSW Australia. The study area covers a land mass of 5615 square kilometres and had an estimated resident population of 389157 on 30 June 2010.Statistical Area Level-1(SA1) as defined by Australian Statistical Geography Standard(ASGS) is the small-area scale used, and the statistical variance at each level of data and its extent of variation explained by introduction of selected independent variables were analysed through multilevel models. The best-fit model is chosen for description and illustration along with its geospatial risk maps.

    Results: Cardiometabolic risk map of the study region, along with its epidemiological findings.

    Conclusions: Small-area level analyses of cardiometabolic risk factors have the potential to reveal area level contexts and can highlight areas for targeted preventive interventions.

Publication Date


  • 2018

Citation


  • Toms, R., Bonney, A., Mayne, D. J. & Feng, X. (2018). Geographic distribution of cardiometabolic risk factors: a small area level approach. Public Health Prevention Conference (pp. 1-1).

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Abstract


  • Introduction: Cardiovascular diseases (CVDs) are the leading cause of death and disability in Australia. Centralised approaches for prevention of CVDs may not suit regional requirements as the risk distribution at smaller regions may significantly differ from larger areas. Understanding the small-area geographic distribution of cardiometabolic risk factors (CMRFs) can inform resource planning and provision of preventive services based on actual need, and can aid in subsequent regional policy developments.

    Methods: A cross-sectional hierarchical design and geospatial methods were used to estimate and map the small-area geographic variability in CMRFs. Test results on selected CMRFs such as diabetes, hyperlipidaemia, chronic kidney disease and high BMI recorded between 2012 and 2016 were extracted from the Southern.IML Research (SIMLR) database, which is a major laboratory network database across the Illawarra Shoalhaven region of NSW Australia. The study area covers a land mass of 5615 square kilometres and had an estimated resident population of 389157 on 30 June 2010.Statistical Area Level-1(SA1) as defined by Australian Statistical Geography Standard(ASGS) is the small-area scale used, and the statistical variance at each level of data and its extent of variation explained by introduction of selected independent variables were analysed through multilevel models. The best-fit model is chosen for description and illustration along with its geospatial risk maps.

    Results: Cardiometabolic risk map of the study region, along with its epidemiological findings.

    Conclusions: Small-area level analyses of cardiometabolic risk factors have the potential to reveal area level contexts and can highlight areas for targeted preventive interventions.

Publication Date


  • 2018

Citation


  • Toms, R., Bonney, A., Mayne, D. J. & Feng, X. (2018). Geographic distribution of cardiometabolic risk factors: a small area level approach. Public Health Prevention Conference (pp. 1-1).

Start Page


  • 1

End Page


  • 1