Abstract

Objective: To develop and validate a diabetes risk assessment tool for Australia based on demographic, lifestyle and simple anthropometric measures.

Design and setting: 5-year follow-up (2004–2005) of the Australian Diabetes, Obesity and Lifestyle study (AusDiab, 1999–2000).

Participants: 6060 AusDiab participants aged 25 years or older who did not have diagnosed diabetes at baseline.

Main outcome measures: Incident diabetes at follow-up was defined by treatment with insulin or oral hypoglycaemic agents or by fasting plasma glucose level ≥ 7.0 mmol/L or 2-hour plasma glucose level in an oral glucose tolerance test ≥ 11.1 mmol/L. The risk prediction model was developed using logistic regression and converted to a simple score, which was then validated in two independent Australian cohorts (the Blue Mountains Eye Study and the North West Adelaide Health Study) using the area under the receiver operating characteristic curve (AROC) and the Hosmer–Lemeshow (HL) χ² statistic.

Results: 362 people developed diabetes. Age, sex, ethnicity, parental history of diabetes, history of high blood glucose level, use of antihypertensive medications, smoking, physical inactivity and waist circumference were included in the final prediction model. The AROC of the diabetes risk tool was 0.78 (95% CI, 0.76–0.81) and HL χ² statistic was 4.1 (P = 0.85). Using a score ≥ 12 (maximum, 35), the sensitivity, specificity and positive predictive value for identifying incident diabetes were 74.0%, 67.7% and 12.7%, respectively. The AROC and HL χ² statistic in the two independent validation cohorts were 0.66 (95% CI, 0.60–0.71) and 9.2 (P = 0.32), and 0.79 (95% CI, 0.72–0.86) and 29.4 (P < 0.001), respectively.

Conclusions: This diabetes risk assessment tool provides a simple, non-invasive method to identify Australian adults at high risk of type 2 diabetes who might benefit from interventions to prevent or delay its onset.

Abstract

Background:

National guidelines disagree on who should be screened for undiagnosed diabetes. No existing diabetes risk score is highly generalizable or widely followed.

Objective:

To develop a new diabetes screening score and compare it with other available screening instruments (Centers for Disease Control and Prevention, American Diabetes Association, and U.S. Preventive Services Task Force guidelines; 2 American Diabetes Association risk questionnaires; and the Rotterdam model).

Design:

Cross-sectional data.

Setting:

NHANES (National Health and Nutrition Examination Survey) 1999 to 2004 for model development and 2005 to 2006, plus a combined cohort of 2 community studies, ARIC (Atherosclerosis Risk in Communities) Study and CHS (Cardiovascular Health Study), for validation.

Participants:

U.S. adults aged 20 years or older.

Measurements:

A risk-scoring algorithm for undiagnosed diabetes, defined as fasting plasma glucose level of 7.0 mmol/L (126 mg/dL) or greater without known diabetes, was developed in the development data set. Logistic regression was used to determine which participant characteristics were independently associated with undiagnosed diabetes. The new algorithm and other methods were evaluated by standard diagnostic and feasibility measures.

Results:

Age, sex, family history of diabetes, history of hypertension, obesity, and physical activity were associated with undiagnosed diabetes. In NHANES (ARIC/CHS), the cut-point of 5 or more points selected 35% (40%) of persons for diabetes screening and yielded a sensitivity of 79% (72%), specificity of 67% (62%), positive predictive value of 10% (10%), and positive likelihood ratio of 2.39 (1.89). In contrast, the comparison scores yielded a sensitivity of 44% to 100%, specificity of 10% to 73%, positive predictive value of 5% to 8%, and positive likelihood ratio of 1.11 to 1.98.

Limitation:

Data during pregnancy were not available.

Conclusion:

This easy-to-implement diabetes screening score seems to demonstrate improvements over existing methods. Studies are needed to evaluate it in diverse populations in real-world settings.

Abstract

More than 100 million Americans have prediabetes or diabetes. Prediabetes is a condition in which individuals have blood glucose levels higher than normal but not high enough to be classified as diabetes. People with prediabetes have an increased risk of Type 2 diabetes. An estimated 34% of adults have prediabetes. Prediabetes is now recognized as a reversible condition that increases an individual’s risk for development of diabetes. Lifestyle risk factors for prediabetes include overweight and physical inactivity.

Increasing awareness and risk stratification of individuals with prediabetes may help physicians understand potential interventions that may help decrease the percentage of patients in their panels in whom diabetes develops. If untreated, 37% of the individuals with prediabetes may have diabetes in 4 years. Lifestyle intervention may decrease the percentage of prediabetic patients in whom diabetes develops to 20%.

Long-term data also suggest that lifestyle intervention may decrease the risk of prediabetes progressing to diabetes for as long as 10 years. To prevent 1 case of diabetes during a 3-year period, 6.9 persons would have to participate in the lifestyle intervention program. In addition, recent data suggest that the difference in direct and indirect costs to care for a patient with prediabetes vs a patient with diabetes may be as much as $7000 per year. Investment in a diabetes prevention program now may have a substantial return on investment in the future and help prevent a preventable disease.

Abstract

Introduction Pre-diabetes, a status conferring high risk of overt diabetes, is defined differently by the American Diabetes Association (ADA) and the WHO. We investigated the impact of applying definitions of pre-diabetes on lifetime risk of diabetes in women and men from the general population.

Research design and methods We used data from 8844 women without diabetes and men aged ≥45 years from the prospective population-based Rotterdam Study in the Netherlands. In both gender groups, we calculated pre-diabetes prevalence according to ADA and WHO criteria and estimated the 10-year and lifetime risk to progress to overt diabetes with adjustment for competing risk of death.

Results Out of 8844 individuals, pre-diabetes was identified in 3492 individuals (prevalence 40%, 95% CI 38% to 41%) according to ADA and 1382 individuals (prevalence 16%, 95% CI 15% to 16%) according to WHO criteria. In both women and men and each age category, ADA prevalence estimates doubled WHO-defined pre-diabetes. For women and men aged 45 years having ADA-defined pre-diabetes, the 10-year risk of diabetes was 14.2% (95% CI 6.0% to 22.5%) and 9.2% (95% CI 3.4% to 15.0%) compared with 23.2% (95% CI 6.8% to 39.6%) and 24.6% (95% CI 8.4% to 40.8%) in women and men with WHO-defined pre-diabetes. At age 45 years, the remaining lifetime risk to progress to overt diabetes was 57.5% (95% CI 51.8% to 63.2%) vs 80.2% (95% CI 74.1% to 86.3%) in women and 46.1% (95% CI 40.8% to 51.4%) vs 68.4% (95% CI 58.3% to 78.5%) in men with pre-diabetes according to ADA and WHO definitions, respectively.

Conclusion Prevalence of pre-diabetes differed considerably in both women and men when applying ADA and WHO pre-diabetes definitions. Women with pre-diabetes had higher lifetime risk to progress to diabetes. The lifetime risk of diabetes was lower in women and men with ADA-defined pre-diabetes as compared with WHO. Improvement of pre-diabetes definition considering appropriate sex-specific and age-specific glycemic thresholds may lead to better identification of individuals at high risk of diabetes.