The Clinical Utility of the AUSDRISK Tool in Assessing Change in Type 2 Diabetes Risk in Overweight/obese Volunteers Undertaking a Healthy Lifestyle Intervention

Overview

Journal Prev Med Rep

Date 2018 Dec 12

PMID 30534513

Citations 5

Authors

Allison Martin

Elizabeth P Neale

Linda C Tapsell

Affiliations

Soon will be listed here.

Abstract

The objective of this study was to assess the clinical utility of the AUSDRISK tool for determining risk of Type 2 diabetes mellitus (T2DM). In this secondary analysis from the HealthTrack study, the AUSDRISK tool was applied to data from overweight/obese volunteers completing a lifestyle intervention trial. Participants were volunteer residents of the Illawarra region recruited in 2014-2015. From 377 trial participants (BMI 25-40 kg/m, 25-54 yr), 161 provided data required for measurement of AUSDRISK, collected at 0 and 12 months. They had been randomised to one of two lifestyle interventions (±a healthy food sample, 30 g walnuts/day, I and IW) delivered by dietitians, or a control intervention (C) delivered by nurse practitioners. HbA1c measures were considered for comparison. At baseline the AUSDRISK score indicated  = 83 (51.5%) were at high risk of T2DM within 5 years (≥12 points). After 12 months the proportion scored as high risk significantly decreased in the IW group (51.5% vs 33.3%;  = 0.005), but not I (51.2% vs 39.0%;  = 0.063) or C group (51.9% vs 38.9%;  = 0.065). By comparison, HbA1c measures indicated high risk in  = 24 (17%) of 139 participants at baseline and borderline non-significant changes over time in the randomised groups. In conclusion, the AUSDRISK tool has reasonable clinical utility in identifying T2DM risk in clinical samples of overweight/obese individuals.

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References

Chen L, Magliano D, Balkau B, Colagiuri S, Zimmet P, Tonkin A . AUSDRISK: an Australian Type 2 Diabetes Risk Assessment Tool based on demographic, lifestyle and simple anthropometric measures. Med J Aust. 2010; 192(4):197-202. DOI: 10.5694/j.1326-5377.2010.tb03507.x. View

. Standards of medical care in diabetes--2013. Diabetes Care. 2012; 36 Suppl 1:S11-66. PMC: 3537269. DOI: 10.2337/dc13-S011. View

Esposito K, Pontillo A, Di Palo C, Giugliano G, Masella M, Marfella R . Effect of weight loss and lifestyle changes on vascular inflammatory markers in obese women: a randomized trial. JAMA. 2003; 289(14):1799-804. DOI: 10.1001/jama.289.14.1799. View

Martin G, Tapsell L, Denmeade S, Batterham M . Relative validity of a diet history interview in an intervention trial manipulating dietary fat in the management of Type II diabetes mellitus. Prev Med. 2003; 36(4):420-8. DOI: 10.1016/s0091-7435(02)00054-3. View

Delahanty L, Pan Q, Jablonski K, Aroda V, Watson K, Bray G . Effects of weight loss, weight cycling, and weight loss maintenance on diabetes incidence and change in cardiometabolic traits in the Diabetes Prevention Program. Diabetes Care. 2014; 37(10):2738-45. PMC: 4170126. DOI: 10.2337/dc14-0018. View

Zhou D, Yu H, He F, Reilly K, Zhang J, Li S . Nut consumption in relation to cardiovascular disease risk and type 2 diabetes: a systematic review and meta-analysis of prospective studies. Am J Clin Nutr. 2014; 100(1):270-7. DOI: 10.3945/ajcn.113.079152. View

Astrup A, Finer N . Redefining type 2 diabetes: 'diabesity' or 'obesity dependent diabetes mellitus'?. Obes Rev. 2002; 1(2):57-9. DOI: 10.1046/j.1467-789x.2000.00013.x. View

Colditz G, Willett W, Rotnitzky A, Manson J . Weight gain as a risk factor for clinical diabetes mellitus in women. Ann Intern Med. 1995; 122(7):481-6. DOI: 10.7326/0003-4819-122-7-199504010-00001. View

Pi-Sunyer X, Blackburn G, Brancati F, Bray G, Bright R, Clark J . Reduction in weight and cardiovascular disease risk factors in individuals with type 2 diabetes: one-year results of the look AHEAD trial. Diabetes Care. 2007; 30(6):1374-83. PMC: 2665929. DOI: 10.2337/dc07-0048. View

10.

Lorenzo C, Wagenknecht L, Hanley A, Rewers M, Karter A, Haffner S . A1C between 5.7 and 6.4% as a marker for identifying pre-diabetes, insulin sensitivity and secretion, and cardiovascular risk factors: the Insulin Resistance Atherosclerosis Study (IRAS). Diabetes Care. 2010; 33(9):2104-9. PMC: 2928372. DOI: 10.2337/dc10-0679. View

11.

Phillips C . Metabolically Healthy Obesity: Personalised and Public Health Implications. Trends Endocrinol Metab. 2016; 27(4):189-191. DOI: 10.1016/j.tem.2016.02.001. View

12.

Tapsell L, Lonergan M, Batterham M, Neale E, Martin A, Thorne R . Effect of interdisciplinary care on weight loss: a randomised controlled trial. BMJ Open. 2017; 7(7):e014533. PMC: 5734361. DOI: 10.1136/bmjopen-2016-014533. View

13.

Buchmueller T, Johar M . Obesity and health expenditures: evidence from Australia. Econ Hum Biol. 2015; 17:42-58. DOI: 10.1016/j.ehb.2015.01.001. View

14.

Aguiar E, Morgan P, Collins C, Plotnikoff R, Callister R . Characteristics of men classified at high-risk for type 2 diabetes mellitus using the AUSDRISK screening tool. Diabetes Res Clin Pract. 2015; 108(1):45-54. DOI: 10.1016/j.diabres.2015.01.017. View

15.

Pasco J, Kotowicz M, Henry M, Nicholson G . Evaluating AUSDRISK for predicting incident diabetes in an independent sample of women. Med J Aust. 2010; 193(6):374. DOI: 10.5694/j.1326-5377.2010.tb03955.x. View

16.

Salas-Salvado J, Fernandez-Ballart J, Ros E, Martinez-Gonzalez M, Fito M, Estruch R . Effect of a Mediterranean diet supplemented with nuts on metabolic syndrome status: one-year results of the PREDIMED randomized trial. Arch Intern Med. 2008; 168(22):2449-2458. DOI: 10.1001/archinte.168.22.2449. View

17.

Bonora E, Tuomilehto J . The pros and cons of diagnosing diabetes with A1C. Diabetes Care. 2011; 34 Suppl 2:S184-90. PMC: 3632159. DOI: 10.2337/dc11-s216. View

18.

Dhippayom T, Chaiyakunapruk N, Krass I . How diabetes risk assessment tools are implemented in practice: a systematic review. Diabetes Res Clin Pract. 2014; 104(3):329-42. DOI: 10.1016/j.diabres.2014.01.008. View

19.

Wong K, Brown A, Li S . AUSDRISK - application in general practice. Aust Fam Physician. 2011; 40(7):524-6. View

20.

Kris-Etherton P . Walnuts decrease risk of cardiovascular disease: a summary of efficacy and biologic mechanisms. J Nutr. 2014; 144(4 Suppl):547S-554S. DOI: 10.3945/jn.113.182907. View