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BMJ Open Diabetes Res Care. 2015 Oct 5;3(1):e000125. doi: 10.1136/bmjdrc-2015-000125. eCollection 2015.

Evaluation of AUSDRISK as a screening tool for lifestyle modification programs: international implications for policy and cost-effectiveness.

Author information

1
Greater Green Triangle University Department of Rural Health , Flinders and Deakin Universities , Warrnambool, Victoria , Australia.
2
Greater Green Triangle University Department of Rural Health , Flinders and Deakin Universities , Warrnambool, Victoria , Australia ; Western Centre for Health Research and Education, Western Health, University of Melbourne , St. Albans, Victoria , Australia.
3
Greater Green Triangle University Department of Rural Health , Flinders and Deakin Universities , Warrnambool, Victoria , Australia ; National Institute for Health and Welfare , Helsinki , Finland ; Faculty of Health Sciences , Institute of Public Health and Clinical Nutrition, University of Eastern Finland , Kuopio , Finland.
4
National Institute for Health and Welfare , Helsinki , Finland.
5
Greater Green Triangle University Department of Rural Health , Flinders and Deakin Universities , Warrnambool, Victoria , Australia ; National Institute for Health and Welfare , Helsinki , Finland.
6
Faculty of Health , Deakin Population Health Strategic Research Centre, Deakin University , Burwood , Australia.

Abstract

OBJECTIVE:

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.

KEYWORDS:

Cost Effectiveness; Lifestyle Modification; Risk Assessment; Type 2 Diabetes

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