Validation of the diabetes screening tools proposed by the American Diabetes Association in an aging Chinese population

<div><p>Aim</p><p>Diabetes is a serious global health problem. A simple and effective screening tool should have substantial public health benefit. We investigated the performance of the latest American Diabetes Association diabetes screening methods in our aging Chinese population.</p><p>Methods</p><p>Subjects without diabetes who returned for the 4th Hong Kong Cardiovascular Risk Factors Prevalence Study in 2010–2012 were evaluated for the probability of having diabetes with reference to the age- and body mass index-based screening criteria (screening criteria) and the diabetes risk test (risk test), and the conclusion drawn was compared to their measured glycaemic status. Diabetes was defined by fasting glucose ≥ 7 mmol/L or 2-hour post oral glucose tolerance test glucose ≥ 11.1 mmol/L.</p><p>Results</p><p>1415 subjects, aged 58.1±10.2, were evaluated. 95 (6.7%) had diabetes. The risk test showed good accuracy (area under the receiver operating curve 0.725) in screening for diabetes with an optimal cut-off score of five. Compared to the screening criteria, the risk test had significantly better specificity (0.57 vs. 0.41, p<0.001), positive predictive value (0.12 vs. 0.09, p<0.001) and positive diagnostic likelihood ratio (1.85 vs. 1.37, p<0.001). To diagnose one case of diabetes, fewer subjects (11 vs. 18) needed to be tested for blood glucose if the risk test was adopted.</p><p>Conclusion</p><p>The risk test appears to be a more effective screening tool in our population. It is simple to use and can be adopted as a public health strategy for identifying people with undiagnosed diabetes for early intervention.</p></div

Statistics measures of the performance of the two ADA screening strategies.

<p>Statistics measures of the performance of the two ADA screening strategies.</p

Baseline characteristics of 1415 subjects at CRISPS4.

<p>Baseline characteristics of 1415 subjects at CRISPS4.</p

Different cut-off points for the ADA diabetes risk test when applied in the CRISPS population (n = 1415).

<p>Different cut-off points for the ADA diabetes risk test when applied in the CRISPS population (n = 1415).</p

Multivariate prediction of diabetes according to CDP and biomarker risk score.

<p>WC, waist circumference; FG, fasting glucose; HT, hypertension; TNF-α R2: tumor neurosis factor-alpha receptor 2.</p

Comparisons of AUCs of different diabetes prediction models.

<p>AUC, Area under the curve; All biomarker levels were sex-specific except for hsCRP;</p><p>CDP: Sex, Age, Waist circumference, fasting glucose, hypertension, dyslipidaemia, family history of diabetes, physical activity and smoking status.</p><p>TNF-α R2: tumor neurosis factor-alpha receptor 2; hsCRP, high sensitivity C-reactive protein; IL-6, Interleukin-6; A-FABP, adipocyte-fatty acid-binding protein.</p

Log-likelihood ratio tests comparing the change before and after addition of biomarkers.

<p>-2LL, -2log-likelihood; p-value (χ², df = 1);</p><p>All biomarker levels were sex specific (except for hsCRP).</p><p>CDP: Sex, Age, Waist circumference, fasting glucose, hypertension, dyslipidaemia, family history of diabetes, physical activity and smoking status.</p><p>TNF-α R2: tumor neurosis factor-alpha receptor 2; hsCRP, high sensitivity C-reactive protein; IL-6, Interleukin-6; A-FABP, adipocyte-fatty acid-binding protein.</p

Cox regression analysis showing the association the <i>KCNJ11</i> E23K variant with incident prediabetes.

<p>HWE: Hardy-Weinberg Equilibrium; EAF: Effect allele frequency; n: Number; HR: Hazards ratio; CI: Confidence interval; P: P-value; Ref: Reference.</p

Multinomial logistic regression analysis showing the association of the <i>KCNJ11</i> E23K variant with progression to prediabetes and progression to T2DM at the end of the 12-year study.

<p>HWE: Hardy-Weinberg Equilibrium; EAF: Effect allele frequency; n: Number; OR: Odds ratio; CI: Confidence interval; P: P-value.</p

Baseline clinical and biochemical characteristics of subjects with and without incident type 2 DM in 5.3 years.

<p>Mean ± SD, median (interquartile-range), or percentage as appropriate.</p>a<p>Physical activity: active if having moderate intensity exercise for at least 30 minutes in one month. ^bSex-adjusted; ^cAdjusted for hypertensive treatment; ^dLog transformed before analysis. ^eExcluded subjects on lipid treatment;</p><p>Central obesity: waist circumference ≥90 cm (M)/80 cm (F).</p><p>Hypertension: systolic blood pressure ≥140 mmHg, diastolic blood pressure ≥90 mmHg, or on hypertensive treatment.</p><p>Dyslipidaemia: triglycerides ≥1.7 mmol/L, HDL cholesterol <1.0 mmol/L (M)/1.3 mmol/L (F), LDL cholesterol ≥3.4 mmol/L, or on lipid treatment.</p