How to screen for diabetes risk in multi-ethnic populations: does one method fit all?

Authors

  • Peter EH Schwarz
  • Gabriele Müller

DOI:

https://doi.org/10.1002/edn.229

Keywords:

risk score, diabetes risk, waist, type 2 diabetes, impaired glucose tolerence, risk stratification

Abstract

Abstract

The question as to how to screen diabetes risk in a multi-ethnic population is not easy to answer. There are a number of diagnostic procedures and risk score tools which may help identify people with increased risk. Some of the risk factors for diabetes have a clear ethnic component, thus the risk stratification is different in Caucasian, Asian and Latin American populations. However, we can expect that the pathophysiology for diabetes development consisting of insulin resistance and progressive beta-cell failure is very similar in its pathomechanistic background between ethnic groups, although the speed and progressive destruction may have ethnic and varying genetic components. In this environment, we have to find clinically applicable approaches to identify those with increased diabetes risk which have to be easy to understand, transparent and replicable for diabetes risk detection. The International Diabetes Federation recently started the PREDICT-2 study to develop a global diabetes risk score.

In this article, we discuss some of the strategies to identify diabetes risk and give some ideas about ethnic variation.

Downloads

Download data is not yet available.

References

Lindstrom J, et al. Prevention of diabetes mellitus in subjects with impaired glucose tolerance in the Finnish diabetes prevention study: results from a randomized clinical trial. J Am Soc Nephrol 2003;14(7 Suppl 2):S108–13.

Knowler WC, et al Reduction in the inci-dence of type 2 diabetes with lifestyle inter-vention or metformin. N Engl J Med 2002; 346:393–403.

Tuomilehto J, et al Prevention of type 2 dia-betes mellitus by changes in lifestyle among subjects with impaired glucose tolerance. N Engl J Med 2001;344:1343–50.

Unwin N, et al Impaired glucose tolerance and impaired fasting glycaemia: the current status on definition and intervention. Diabet Med 2002;19:708–23.

Abdul-Ghani MA, et al. Risk of progression to type 2 diabetes based on relationship between postload plasma glucose and fasting plasma glucose. Diabetes Care 2006;29:1613–8.

Stern MP, et al. Identification of persons at high risk for type 2 diabetes mellitus: do we need the oral glucose tolerance test? Ann Intern Med 2002;136: 575–81.

Aekplakorn W, et al. A risk score for predicting incident diabetes in the Thai populadon. Diabetes Care 2006;29:1872–7.

Wannamethee SG, et al. Metabolic syndrome vs Framingham Risk Score for prediction of coronary heart disease, stroke, and type 2 diabetes mellitus. Arch Intern Med 2005; 165:2644–50.

Kanaya AM, et al. Predicting the development of diabetes in older adults: the derivation and validation of a prediction rule. Diabetes Care 2005;28:404–8.

McNeely MJ, et al. Comparison of a clinical model, the oral glucose tolerance test, and fasting glucose for prediction of type 2 dia-betes risk in Japanese Americans. Diabetes Care 2003;26:758–63.

Gray LJ, et al. The Leicester Risk Assessment score for detecting undiagnosed type 2 dia-betes and impaired glucose regulation for use in a multiethnic UK setting. Diabet Med 2010;27:887–95.

Schwarz PE, et al. The Finnish Diabetes Risk Score is associated with insulin resistance and progression towards type 2 diabetes. J Clin Endocrinol Metab 2009;94:920–6.

Schulze MB, et al. An accurate risk score based on anthropometric, dietary, and lifestyle factors to predict the development of type 2 diabetes: response to Schwarz et al. Diabetes Care 2007;30:e88.

Glumer, C, et al. A Danish diabetes risk score for targeted screening: the Inter99 study. Diabetes Care 2004;27:727–33.

Lindstrom J, Tuomilehto J. The Diabetes Risk Score: a practical tool to predict type 2 diabetes risk. Diabetes Care 2003;26:725–31.

Schwarz PE, et al. Tools for predicting the risk of type 2 diabetes in daily practice. Horm Metab Res 2009;41:86–97.

American Diabetes Association, Inter-national Expert Committee report on the role of the Ali assay in the diagnosis of dia-betes. Diabetes Care 2009;32:1327–34.

Gillies CL, et al. Pharmacological and lifestyle interventions to prevent or delay type 2 diabetes in people with impaired glu-cose tolerance: systematic review and meta-analysis. BMJ 2007;334 ( 7588) :299.

Abdul-Ghani MA, et al. Contributions of beta-cell dysfunction and insulin resistance to the pathogenesis of impaired glucose tol-erance and impaired fasting glucose. Diabetes Care 2006;29:1130–9.

Valensi P, et al. Pre-diabetes essential action: a European perspective. Diabetes Metab 2005; 31:606–20.

Schwarz PE, Lindstrom J. From evidence to practice - the IMAGE project - new stan-dards in the prevention of type 2 diabetes. Diabetes Res Clin Pract 2011;91:138–40.

Paulweber B, et al. A European evidence-based guideline for the prevention of type 2 diabetes. Horm Metab Res 2010;42 (Suppl 1):S3–S36.

Lindstrom J, et al. Take action to prevent dia-betes - the IMAGE toolkit for the prevention of type 2 diabetes in Europe. Horm Metab Res 2010;42(Suppl 1):537–55.

National Institute for Health and Clinical Excellence. NICE public health guidance 35: Preventing type 2 diabetes: population and community-level interventions in high-risk groups and the general population. London: NICE, 2011.

Griffin SJ, et al. Effect of early intensive mul-dfactorial therapy on 5-year cardiovascular outcomes in individuals with type 2 diabetes detected by screening (ADDITION-Europe): a cluster-randomised trial. Lancet 2011;378:156–67.

Franciosi M, et al. Use of the diabetes risk score for opportunistic screening of undiag-nosed diabetes and impaired glucose toler-ance: the IGLOO (Impaired Glucose Tolerance and Long-Term Outcomes Observational) study. Diabetes Care 2005; 28:1187–94.

Rathmann W, et al. Performance of screen-ing questionnaires and risk scores for undi-agnosed diabetes: the KORA Survey 2000. Arch Intern Med 2005;165:436–41.

Glumer CK, et al. Can a screening pro-gramme for diabetes be applied to another population? Diabet Med 2005;22:1234–8.

Mohan V, et al. A diabetes risk score helps identify metabolic syndrome and cardiovas-cular risk in Indians - the Chennai Urban Rural Epidemiology Study (CURES-38). Diabetes Obes Metab 2007;9:337–43.

Park PJ, et al. The performance of a risk score in predicting undiagnosed hyper-glycemia. Diabetes Care 2002;25:984–8.

Hippisley-Cox, J, et al. Predicting risk of type 2 diabetes in England and Wales: prospective derivation and validation of QDScore. BMJ2009; 338: b880.

Taub NA, et al. Automated detection of high risk for impaired glucose regulation and type 2 diabetes mellitus, using primary care electronic data, in a multi-ethnic UK community setting. Diabetologia 2009; 52 (Suppl 1):S325–S326.

Bluher S, et al. Who should we target for dia-betes prevention and diabetes risk reduction? Curr Diab Rep 2012;12: 147–56.

Lee CM, Colagiuri S. Risk scores for diabetes prediction: The International Diabetes Federation PREDICT-2 project. Diabetes Res Clin Prad 2013;100:285–6.

American Diabetes Association. Diagnosis and classification of diabetes mellitus. Diabetes Care 2010;33 (Suppl 1):S62–9.

Abdul-Ghani MA, et al. Role of glycated hemoglobin in the prediction of future risk of T2DM. J Clin Endocrinol Metab 2011;96: 2596–600.

Skriver MV, et al. HbAli as predictor of all-cause mortality in individuals at high risk of diabetes with normal glucose tolerance, identified by screening: a follow-up study of the Anglo-Danish-Dutch Study of Intensive Treatment in People with Screen-Detected Diabetes in Primary Care (ADDITION), Denmark. Diabetologia 2011;53:2328–33.

Zhang X, et al. Ali level and future risk of diabetes: a systematic review. Diabetes Care 2010;33:1665–73.

Lorenzo C, et al. Ak 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;33:2104–9.

Hawleyi Exercise as a therapeutic interven-tion for the prevention and treatment of insulin resistance. Diabetes Metab Res Rev 2004;20:383–93.

Bassuk SS, Manson JE. Epidemiological evidence for the role of physical activity in reduc-ing risk of type 2 diabetes and cardiovascular disease. Appi Physiol 2005;99:1193–204.

Telford RD. Low physical activity and obesity: causes of chronic disease or simply pre-dictors? Med Sci Sports Exerc 2007;39:1233–40.

Sisson SB, Katzmarzyk PT. International prevalence of physical activity in youth and adults. Obes Rev 2008;9:606–14.

Carlson SA, et al. Trend and prevalence esti-mates based on the 2008 Physical Activity Guidelines for Americans. Am J Prey Med 2010;39:305–13.

NHS Information Centre. Health survey for England - 2008: physical activity and fitness. 2009. www.ic.nhs.uk/statistics-and-data-collections/health-and-lifestyles-related-surveys/health-survey-for-england/health-survey-for-england-2008-physical-activity-and-fitness.

Troiano RP et al. Physical activity in the United States measured by accelerometer. Med Sci Sports Exerc 2008;40:181–8.

Schwarz PE, et al. Nonpharmacological interventions for the prevention of type 2 diabetes mellitus. Nat Rev Endocrinol 2012; 8:363–73.

Gill JM, et al. Sitting time and waist circum-ference are associated with glycemia in U.K. South Asians: data from 1,228 adults screened for the PODOSA trial. Diabetes Care 2011;34:1214–8.

Whitlock G, et al. Body-mass index and cause-specific mortality in 900 000 adults: collaborative analyses of 57 prospective stud-ies. Lancet 2009;373 (9669) :1083–96.

Thamer C, et al. High visceral fat mass and high liver fat are associated with resistance to lifestyle intervention. Obesity (Silver Spring) 2007;15:531–8.

Salopuro TM, et al. Population-level effects of the national diabetes prevention pro-gramme (FIN-D2D) on the body weight, the waist circumference, and the prevalence of obesity. BMC Public Health 2011;11:350.

Gillies CL, et al. Different strategies for screening and prevention of type 2 diabetes in adults: cost effectiveness analysis. BMJ 2008;336(7654):1180–5.

Gillett M, et al. Delivering the diabetes edu-cation and self management for ongoing and newly diagnosed (DESMOND) pro-gramme for people with newly diagnosed type 2 diabetes: cost effectiveness analysis. BMJ2010;341:c4093.

Bethel MA, et al. Evaluation of a self-admin-istered oral glucose tolerance test. Diabetes Care 2013;36:1483–8.

Yates T, et al. Effect of physical activity meas-urement type on the association between walking activity and glucose regulation in a high-risk population recruited from primary care. Int J Epidemiol 2013;42:533–40.

Schwarz PE, Albright AL. Prevention of type 2 diabetes: the strategic approach for imple-mentation. Horm Metab Res 2011;43:907–10.

Sodjinou R, et al. Obesity and cardio-meta-bolic risk factors in urban adults of Benin: relationship with socio-economic status, urbanisation, and lifestyle patterns. BMC Public Health 2008;8:84.

Zampetaki A, et al. Plasma microRNA profil-ing reveals loss of endothelial miR-126 and other microRNAs in type 2 diabetes. Circ Res 2010;107:810–7.

Downloads

Published

2013-07-01

How to Cite

Schwarz, P. E., & Müller, G. (2013). How to screen for diabetes risk in multi-ethnic populations: does one method fit all?. International Diabetes Nursing, 10(2), 63–68. https://doi.org/10.1002/edn.229

Issue

Section

Review Article