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dc.contributor.authorMalo, JA
dc.contributor.authorVersace, VL
dc.contributor.authorJanus, ED
dc.contributor.authorLaatikainen, T
dc.contributor.authorPeltonen, M
dc.contributor.authorVartiainen, E
dc.contributor.authorCoates, MJ
dc.contributor.authorDunbar, JA
dc.date.accessioned2020-12-18T02:51:10Z
dc.date.available2020-12-18T02:51:10Z
dc.date.issued2015-01-01
dc.identifierpii: bmjdrc-2015-000125
dc.identifier.citationMalo, J. A., Versace, V. L., Janus, E. D., Laatikainen, T., Peltonen, M., Vartiainen, E., Coates, M. J. & Dunbar, J. A. (2015). Evaluation of AUSDRISK as a screening tool for lifestyle modification programs: international implications for policy and cost-effectiveness. BMJ OPEN DIABETES RESEARCH & CARE, 3 (1), https://doi.org/10.1136/bmjdrc-2015-000125.
dc.identifier.issn2052-4897
dc.identifier.urihttp://hdl.handle.net/11343/255524
dc.description.abstractOBJECTIVE: To evaluate the current use of Australian Type 2 Diabetes Risk Assessment Tool (AUSDRISK) as a screening tool to identify individuals at high risk of developing type 2 diabetes for entry into lifestyle modification programs. RESEARCH DESIGN AND METHODS: AUSDRISK scores were calculated from participants aged 40-74 years in the Greater Green Triangle Risk Factor Study, a cross-sectional population survey in 3 regions of Southwest Victoria, Australia, 2004-2006. Biomedical profiles of AUSDRISK risk categories were determined along with estimates of the Victorian population included at various cut-off scores. Sensitivity, specificity, positive predictive value (PPV), negative predictive value, and receiver operating characteristics were calculated for AUSDRISK in determining fasting plasma glucose (FPG) ≥6.1 mmol/L. RESULTS: Increasing AUSDRISK scores were associated with an increase in weight, body mass index, FPG, and metabolic syndrome. Increasing the minimum cut-off score also increased the proportion of individuals who were obese and centrally obese, had impaired fasting glucose (IFG) and metabolic syndrome. An AUSDRISK score of ≥12 was estimated to include 39.5% of the Victorian population aged 40-74 (916 000), while a score of ≥20 would include only 5.2% of the same population (120 000). At AUSDRISK≥20, the PPV for detecting FPG≥6.1 mmol/L was 28.4%. CONCLUSIONS: AUSDRISK is powered to predict those with IFG and undiagnosed type 2 diabetes, but its effectiveness as the sole determinant for entry into a lifestyle modification program is questionable given the large proportion of the population screened-in using the current minimum cut-off of ≥12. AUSDRISK should be used in conjunction with oral glucose tolerance testing, fasting glucose, or glycated hemoglobin to identify those individuals at highest risk of progression to type 2 diabetes, who should be the primary targets for lifestyle modification.
dc.languageEnglish
dc.publisherBMJ PUBLISHING GROUP
dc.rights.urihttps://creativecommons.org/licenses/by-nc/4.0
dc.titleEvaluation of AUSDRISK as a screening tool for lifestyle modification programs: international implications for policy and cost-effectiveness
dc.typeJournal Article
dc.identifier.doi10.1136/bmjdrc-2015-000125
melbourne.affiliation.departmentMedicine, Western Health
melbourne.affiliation.facultyMedicine, Dentistry & Health Sciences
melbourne.source.titleBMJ Open Diabetes Research and Care
melbourne.source.volume3
melbourne.source.issue1
dc.rights.licenseCC BY-NC
melbourne.elementsid1190762
melbourne.contributor.authorJanus, Edward
dc.identifier.eissn2052-4897
melbourne.accessrightsOpen Access


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