Utility of hemoglobin A(1c) for diagnosing prediabetes and diabetes in obese children and adolescents

OBJECTIVE

Hemoglobin A_1c (A1C) has emerged as a recommended diagnostic tool for identifying diabetes and subjects at risk for the disease. This recommendation is based on data in adults showing the relationship between A1C with future development of diabetes and microvascular complications. However, studies in the pediatric population are lacking.

RESEARCH DESIGN AND METHODS

We studied a multiethnic cohort of 1,156 obese children and adolescents without a diagnosis of diabetes (male, 40%/female, 60%). All subjects underwent an oral glucose tolerance test (OGTT) and A1C measurement. These tests were repeated after a follow-up time of ∼2 years in 218 subjects.

RESULTS

At baseline, subjects were stratified according to A1C categories: 77% with normal glucose tolerance (A1C <5.7%), 21% at risk for diabetes (A1C 5.7–6.4%), and 1% with diabetes (A1C >6.5%). In the at risk for diabetes category, 47% were classified with prediabetes or diabetes, and in the diabetes category, 62% were classified with type 2 diabetes by the OGTT. The area under the curve receiver operating characteristic for A1C was 0.81 (95% CI 0.70–0.92). The threshold for identifying type 2 diabetes was 5.8%, with 78% specificity and 68% sensitivity. In the subgroup with repeated measures, a multivariate analysis showed that the strongest predictors of 2-h glucose at follow-up were baseline A1C and 2-h glucose, independently of age, ethnicity, sex, fasting glucose, and follow-up time.

CONCLUSIONS

The American Diabetes Association suggested that an A1C of 6.5% underestimates the prevalence of prediabetes and diabetes in obese children and adolescents. Given the low sensitivity and specificity, the use of A1C by itself represents a poor diagnostic tool for prediabetes and type 2 diabetes in obese children and adolescents.After years of debate, the American Diabetes Association (ADA) published revised recommendations to use hemoglobin A_1c (A1C) to diagnose diabetes and to identify subjects at risk for developing diabetes in the future (1). The decision is based on numerous cross-sectional and longitudinal studies showing the correlation between A1C and diabetes at baseline or long-term association between A1C and risk of diabetes and diabetes-related comorbidities (1–6). Additional factors influencing this decision were as follows: A1C does not require a fasting state, reflects the usual 3–4 months before glycemia, has low intraindividual variability, and is a good predictor of diabetes-related complications (1,5). It should be noted that this decision was made only on studies performed in adults. Little is known about the use of the A1C test for the diagnosis of type 2 diabetes and prediabetes in childhood and adolescence. In view of the fact that both prediabetes and, more important, type 2 diabetes have recently emerged as early complications of childhood obesity (7), it is of critical importance to diagnose these forms of dysglycemia early in their development. Thus, the aim of this study was to assess the diagnostic utility of A1C for the diagnosis of prediabetes and type 2 diabetes in obese children and adolescents. We therefore conducted this study to evaluate the following: 1) the distribution of A1C levels in a multiethnic cohort of obese children and adolescents without known diabetes and 2) the sensitivity and specificity of A1C for type 2 diabetes and prediabetes diagnoses compared with the current oral glucose tolerance test (OGTT) gold standard.     

Cardiometabolic risk profiles and carotid atherosclerosis in individuals with prediabetes identified by fasting glucose, postchallenge glucose, and hemoglobin A1c criteria

OBJECTIVE

We evaluated whether cardiometabolic risk profiles differ for subjects identified as having prediabetes by A1C, fasting glucose (FPG), or 2-h postchallenge glucose (2-PG) criteria.

RESEARCH DESIGN AND METHODS

Atherosclerosis risk factors, oral glucose tolerance test, and ultrasound measurement of carotid intima–media thickness (IMT) were analyzed in 780 nondiabetic individuals.

RESULTS

Poor agreement existed for A1C and FPG criteria for identification of subjects with prediabetes (κ coefficient = 0.332). No differences in cardiometabolic risk profiles were observed among the three groups of individuals with prediabetes by A1C only, FPG only, and both A1C and FPG. Poor agreement also existed for A1C and 2-PG criteria for identification of individuals with prediabetes (κ coefficient = 0.299). No significant differences in cardiometabolic risk factors were observed between IGT-only and individuals with prediabetes by A1C and 2-PG. Compared with subjects with prediabetes identified by A1C only, IGT-only individuals exhibited a worse cardiometabolic risk profile, with significantly higher systolic blood pressure, pulse pressure, 2-h postchallenge insulin, triglycerides, high-sensitivity C-reactive protein, and carotid IMT, and lower HDL cholesterol levels and insulin sensitivity.

CONCLUSIONS

These results suggest that considerable discordance between A1C, FPG, and 2-PG exists for the identification of individuals with prediabetes and that the cardiometabolic risk profile of these individuals varies by metabolic parameter, with 2-PG showing the stronger association with cardiometabolic risk factors and subclinical atherosclerosis than FPG or A1C.Hemoglobin A_1c (A1C) is an integrated measure of average blood glucose concentrations over the preceding 2–3 months and is widely used for monitoring metabolic control in individuals with diabetes (1). Recently, the American Diabetes Association (ADA) has revised criteria for the diagnosis of type 2 diabetes and the categories at increased risk for diabetes already including impaired fasting glucose (IFG) and impaired glucose tolerance (IGT) on the basis of an ample analysis performed by an international expert committee (2,3) recommending the use of A1C measurements as another diagnostic test option in addition to glucose values. Specifically for the categories of increased risk for type 2 diabetes, the new ADA recommendations state that an A1C from 5.7 to 6.4% identifies individuals at high risk for diabetes to whom the term prediabetes may be applied (2).A1C measurements offer some practical advantages over assessments of fasting plasma glucose (FPG) or glucose levels during an oral glucose tolerance test (OGTT), including lower day-to-day variability, less perturbations during periods of stress or illness, and requirement of a nonfasting sample (3). However, the A1C measure may identify distinct subjects at increased risk for type 2 diabetes compared with IFG and IGT, and if extensively implemented, may to some extent change the present epidemiologic setting of these dysglycemic conditions. Although it would be desirable for fasting glucose, 2-h postchallenge glucose, and A1C values to be equivalent in identifying at-risk subjects, a poor concordance among the three prediabetes categories has been reported in different ethnic groups (4–10).Early detection of individuals at high risk for type 2 diabetes is essential not only for prevention of diabetes itself but also of the associated cardiovascular complications. Indeed, the risk of cardiovascular disease is already increased before glucose levels reach the diagnostic threshold of diabetes, and 2-h postchallenge glucose has been reported to be a better predictor of cardiovascular disease than FPG (11,12). However, A1C was shown to be a better predictor of cardiovascular disease than FPG (13). Head-to-head comparisons between 2-h postchallenge glucose and A1C as predictors of cardiovascular disease have been focused on mortality, and results are controversial (14–16).In consideration of the expected augmented use of A1C as a screening tool to identify individuals with dysglycemic conditions, it would be important to evaluate the effect of the new ADA recommendations for prediabetes definition on the ability to identify individuals who are at increased risk for a number of adverse clinical outcomes. In the current study, we examined the concordance of A1C, FPG, or 2-h postchallenge glucose tests for the identification of prediabetes in a cohort of Italian Caucasians. We also evaluated whether metabolic and cardiovascular risk factors, including carotid preclinical atherosclerosis, differ for subjects identified as having prediabetes by each of these criteria.     

Hemoglobin A1c, fasting glucose, and cardiovascular risk in a population with high prevalence of diabetes: the strong heart study

OBJECTIVE

We compared A1C and fasting plasma glucose (FPG) in predicting cardiovascular disease (CVD) in a population with widespread obesity and diabetes.

RESEARCH DESIGN AND METHODS

A total of 4,549 American Indian adults underwent the Strong Heart Study (SHS) baseline examination (1989–1991). Data from 3,850 individuals (60% women) with baseline measurements of FPG and A1C and no prevalent CVD were analyzed; 1,386 had known diabetes. CVD events were ascertained over a median of 15 years.

RESULTS

A1C ≥6.5% had a 44.3% sensitivity and 98.9% specificity to identify participants with FPG ≥126 mg/dL. Increases in A1C were associated with adverse CVD risk factor profiles; individuals with known diabetes had worse profiles. For A1C <5, 5 to <5.5, 5.5 to <6, 6–6.5, or ≥6.5% or known diabetes, the multivariate-adjusted hazard ratio (HR) [95% CI] for coronary heart disease (CHD) was significant only for individuals with known diabetes (2.76 [2.17–3.51]). Similarly, the adjusted HRs for total CVD were significant only for individuals with A1C ≥6.5% or known diabetes (1.50 [1.10–2.04] and 2.52 [2.06–3.08], respectively). Similar results were observed for FPG.

CONCLUSIONS

Individuals with known or newly diagnosed diabetes had increased risk for CVD. Although A1C is more convenient than FPG in diagnosing diabetes, neither test adds to conventional CVD risk factors in predicting CHD or total CVD.Fasting plasma glucose (FPG) has been the standard measure for diagnosing diabetes (1). Hemoglobin A_1c (A1C) ≥6.5% has been offered as an alternative diagnostic criterion (2) on the basis of the relationship between A1C and microvascular complications. A1C and FPG measure differing aspects of glucose metabolism; A1C measures chronic glycemia (during the previous 2–3 months), while FPG primarily reflects hepatic glucose output at the time of sampling. As expected, A1C identifies different individuals as diabetic than does FPG (3). Additionally, it was reported (4) in a predominantly white cohort with low prevalence of obesity or diabetes that increments of A1C >5.5% predict significantly increased risk for coronary heart disease (CHD) and stroke, whereas FPG of 100–126 mg/dL does not.Many U.S. minority populations have high rates of obesity, insulin resistance, and diabetes (5,6). We recently reported that A1C alone identifies fewer diabetes cases than FPG, and neither FPG nor A1C alone can identify all diabetes cases (7). Because the Strong Heart Study (SHS) cohort had a high prevalence of obesity and type 2 diabetes >20 years ago, it serves as a model for other minority populations experiencing epidemics of these disorders (8). In this article, cardiovascular disease (CVD) incidence by A1C category will be examined, and the value of A1C and FPG in predicting CVD will be compared.     

Hemoglobin A1c as a screen for previously undiagnosed prediabetes and diabetes in an acute-care setting

OBJECTIVE

Hemoglobin A_1c (HbA_1c) is recommended for identifying diabetes and prediabetes. Because HbA_1c does not fluctuate with recent eating or acute illness, it can be measured in a variety of clinical settings. Although outpatient studies identified HbA_1c-screening cutoff values for diabetes and prediabetes, HbA_1c-screening thresholds have not been determined for acute-care settings. Using follow-up fasting blood glucose (FBG) and the 2-h oral glucose tolerance test (OGTT) as the criterion gold standard, we determined optimal HbA_1c-screening cutoffs for undiagnosed dysglycemia in the emergency department setting.

RESEARCH DESIGN AND METHODS

This was a prospective observational study of adults aged ≥18 years with no known history of hyperglycemia presenting to an emergency department with acute illness. Outpatient FBS and 2-h OGTT were performed after recovery from the acute illness, resulting in diagnostic categorizations of prediabetes, diabetes, and dysglycemia (prediabetes or diabetes). Optimal cutoffs were determined and performance data identified for cut points.

RESULTS

A total of 618 patients were included, with a mean age of 49.7 (±14.9) years and mean HbA_1c of 5.68% (±0.86). On the basis of an OGTT, the prevalence of previously undiagnosed prediabetes and diabetes was 31.9 and 10.5%, respectively. The optimal HbA_1c-screening cutoff for prediabetes was 5.7% (area under the curve [AUC] = 0.659, sensitivity = 55%, and specificity = 71%), for dysglycemia 5.8% (AUC = 0.717, sensitivity = 57%, and specificity = 79%), and for diabetes 6.0% (AUC = 0.868, sensitivity = 77%, and specificity = 87%).

CONCLUSIONS

We identified HbA_1c cut points to screen for prediabetes and diabetes in an emergency department adult population. The values coincide with published outpatient study findings and suggest that an emergency department visit provides an opportunity for HbA_1c-based dysglycemia screening.There are 26.8 million people with diabetes in the U.S., and by the year 2030, it is estimated to increase to 36 million people (1). Current estimates are that 27% of individuals with diabetes remain undiagnosed, and by the time of diagnosis, there often are microvascular and macrovascular abnormalities found (2–4). Early recognition is important because lifestyle modifications and medications can reduce the incidence of diabetes in people at high risk (5), and the treatment of diabetes can prevent or delay microvascular end-organ complications.The use of hemoglobin A_1c (HbA_1c) to diagnose prediabetes and diabetes recently was recommended by the American Diabetes Association (ADA) (6). HbA_1c testing has an advantage over glucose-based testing because it does not require fasting, and the test can be performed at any time. Guidelines recommend an HbA_1c ≥6.5% to diagnose diabetes and HbA_1c between 5.7 and 6.4% for identifying prediabetes. These cutoff values for HbA_1c are derived in part from outpatient studies and are based on populations of those not acutely ill at the time of testing (7–9).Less attention has been given to screening and diagnosing diabetes and prediabetes in acute-care settings such as the emergency department, where blood is routinely drawn to manage acute illness and clinicians are available to interpret the results. The HbA_1c test can be quickly performed in many different clinical settings, including the hospital. However, it is not known whether HbA_1c thresholds differ between the higher-risk acute-care and the general outpatient populations. The purpose of this study was to determine optimal HbA_1c-screening cutoff points for undiagnosed dysglycemia in the emergency department setting using follow-up fasting blood glucose (FBS) and 2-h oral glucose tolerance tests (OGTTs) as the criterion gold standard.     

糖化血红蛋白对糖尿病的诊断价值分析

目的探讨糖化血红蛋白(HbA1c)对糖尿病(DM)诊断的临床价值。方法以143例健康人、82例空腹血糖受损(IFG)患者和340例DM患者进行口服糖耐量试验(OGTT),葡萄糖氧化酶电极法测定血糖,免疫透射比浊法测定HbA1c,对结果进行分析。结果从健康组、IFG组到DM组,HbA1c水平逐渐增高,各组间比较差异均有统计学意义(P<0.05),以HbA1c≥6.5%或HbA1c≥7.0%作为DM诊断临界值,其诊断灵敏度分别为99.18%和97.33%,诊断特异度分别为94.45%和99.97%,均优于以空腹血糖(FPG)大于或等于7 mmol/L作为诊断临界值的诊断灵敏度(76.43%)和诊断特异度(89.82%)。结论 HbA1c具有比FPG更高的DM诊断灵敏度和诊断特异度;比OGTT更为简便快速,有利于DM的早期诊断,适合作为DM诊断指标而广泛应用。     

Medication adherence and associated hemoglobin A1c in type 2 diabetes

BACKGROUND: Tight blood glucose control has been correlated with a reduction in diabetes complications. Adherence to antidiabetic medications is crucial to achieving blood glucose control. OBJECTIVE: To assess the relationship between good glucose control [glycosylated hemoglobin (HbA1c) levels] and adherence to prescribed treatment in patients on a stable medication regimen for type 2 diabetes. METHODS: The Morisky survey, a 4-item questionnaire that predicts patient medication-taking behavior, was used to assess adherence in 301 patients. The relationship of HbA1c to Morisky score was evaluated, controlling for other variables related to patient demographics and clinical characteristics. Data were analyzed using a general linear model on log (HbA1c). RESULTS: Unadjusted mean HbA1c values (capped at 14.0%) for patients with Morisky scores of 0 or 1, 2, 3, and 4 were 8.92%, 8.67%, 7.74%, and 7.60%, respectively. Of all patients, 13.0%, 14.0%, 24.3%, and 48.8% had scores of 0 or 1, 2, 3, and 4, respectively. Good adherence (Morisky score > or = 3) was associated with a 10% lower total HbA1c (p = 0.0003) adjusted for all other factors in the model. Duration of diabetes (5-10 y) and presence of diabetes complications were also significantly associated with HbA1c (p = 0.026 and 0.002, respectively). Adherence was poor in 27% of patients. CONCLUSIONS: This study found that patients with a higher score on the Morisky scale had a lower associated HbA1c measurement. The Morisky score may be an efficient tool for identifying patients with poor medication-taking behavior who can then be targeted for directed adherence counseling services.     

Glycated hemoglobin A1c level is associated with high urinary albumin/creatinine ratio in non-diabetic adult population

Background: Regarding the association between glycated hemoglobin A1c (HbA1c) levels and microvascular complications, high HbA1c level in participants without diabetes mellitus (DM) may be associated with a high urinary albumin-to-creatinine ratio (UACR).

Patients and methods: Twelve thousand seven hundred and seventy four participants without DM were included in this study. The participants were divided into three groups according to HbA1c levels: a Low group (<5.7%), Middle group (5.7–6.0%), and High group (>6.0%). A high UACR was defined as UACR ≥3.9?mg/g for men and UACR ≥7.5?mg/g for women.

Results: The proportions of participants with a high UACR in the Low, Middle, and High groups were 22.4%, 27.9%, and 38.1%, respectively. Both univariate and multivariate analyses showed that logUACR was greatest in the High group compared to the other groups. For participants without metabolic syndrome (MetS), the proportions of participants with high UACR and logUACR values were greatest in the High group compared to the other groups. For participants with MetS, no differences were found for proportions of participants with high UACR and logUACR values in the Low, Middle, and High groups.

Conclusion: Non-DM participants with relatively high HbA1c levels should be closely monitored for UACR, especially if participants do not have MetS.

• KEY MESSAGES

• HbA1c level was positively associated with the proportion of participants with a high UACR and logUACR in participants without DM.

• For participants without MetS, the proportion of participants with a high UACR was greater in the High group than in the other groups and logUACR was greatest in the High group compared to the other groups.

• For participants with MetS, there were significant associations between HbA1c and the proportion of participants with a high UACR as a categorical variable or logUACR as a continuous variable, but the statistical significance of this finding was weak. No differences were found for proportions of participants with high UACR and logUACR values in the Low, Middle, and High groups.

     

Clinical utility of serum fructosamine in diabetes mellitus compared with hemoglobin A1c

To evaluate the clinical utility of fructosamine as a mean of monitor glycaemic control, fructosamine and HbA1c were compared in 46 random out-patients visiting a Diabetic Clinic as well as in 25 inpatients admitted to a Diabetes Day Care Unit. In the out-patients, there were a significant correlations between fructosamine and fasting blood glucose (r = 0.75) as well as between fructosamine and HbA1c (r = 0.91). However, when the reference values were considered, interesting differences were found; only 4% of the out-patients showed normal HbA1c values while 39% showed normal fructosamine values. Accordingly, fructosamine and HbA1c evaluate different aspects of glycaemic control. During an admission of 7 days to the Diabetes Day Care Unit no statistical changes in mean blood glucose and fructosamine values occurred. On the other hand, two weeks after discharge from the Unit, not only fructosamine (3.58 +/- 0.16 mmol vs 3.09 +/- 0.08 mmol/l) but also HbA1c (9.52 +/- 0.38% vs 8.33 +/- 0.23%) had improved significantly. Thus HbA1c measures improvements in glycaemic control as early as 3 weeks after changes in treatment. At six weeks after discharge HbA1c (7.63 +/- 0.34%) but not fructosamine (3.02 + 0.14 mmol/l) had improved further. HbA1c is a reliable marker of glycaemic control while the value of fructosamine in clinical practice is unclear.     

The usage of fasting glucose and glycated hemoglobin for the identification of unknown type 2 diabetes in high risk patients with morbid obesity

Background: In spite of increased vigilance of undiagnosed type 2 diabetes (DM2), the prevalence of unknown DM2 in subjects with morbid obesity is not known.

Aim: To assess the prevalence of undiagnosed DM2 and compare the performance of glycated A1c (HbA1c) and fasting glucose (FG) for the diagnosis of DM2 and prediabetes (preDM) in patients with morbid obesity.

Patients and methods: We measured fasting glucose and HbA1c in 537 consecutive patients with morbid obesity without previously known DM2.

Results: A total of 49 (9%) patients with morbid obesity had unknown DM2 out of which 16 (33%) fulfilled both the criteria for HbA1c and FG. Out of 284 (53%) subjects with preDM, 133 (47%) fulfilled both the criteria for HbA1c and FG. Measurements of agreement for FG and HbA1c were moderate for DM2 (κ?=?0.461, p?<?.001) and fair for preDM (κ?=?0.317, p?<?.001). Areas under the curve for FG and HbA1c in predicting unknown DM2 were 0.970 (95% CI 0.942, 0.998) and 0.894 (95% CI 0.837, 0.951) respectively. The optimal thresholds to identify unknown DM2 were FG ≥6.6?mmol/L and HbA1c ≥ 6.1% (43?mmol/mol).

Conclusions: The prevalence of DM2 remains high and both FG and HbA1c identify patients with unknown DM2. FG was slightly superior to HbA1c in predicting and separating patients with unknown DM2 from patients without DM2. We suggest that an FG ≥6.6?mmol/L or an HbA1c ≥6.1% (43?mmol/mol) may be used as primary cut points for the identification of unknown DM2 among patients with morbid obesity.     

糖化血红蛋白及糖化白蛋白在妊娠期糖尿病诊断中的价值

目的评估糖化血红蛋白(HbA1c)和血清糖化白蛋白(GA)在妊娠期糖尿病(GDM)患者早期监测中的作用。方法根据美国糖尿病协会(ADA)建议,以口服75 g葡萄糖耐量试验(OGTT)测定值作为诊断GDM的标准,将98例妊娠妇女(孕期22~24周)分为正常妊娠组50例、GDM组48例,同时测定2组的HbA1c和GA,并进行统计学分析及受试者工作特征(ROC)曲线分析。结果 GDM组的HbA1c和GA明显高于正常妊娠组(P0.01)。当HbA1c的Cut-off值为5.15%时,ROC曲线下面积为0.954±0.020,敏感性为87.5%,特异性为92.0%。当GA的Cut-off值12.50%时,ROC曲线下面积为0.910±0.029,敏感性为81.3%,特异性为84.0%。HbA1c和GA联合诊断GDM的敏感性为70.8%、特异性为98.0%。结论当HbA1c5.15%和GA12.50%时,诊断GDM的敏感度和特异性较高。HbA1c和GA联合检测对GDM有重要价值。     

Comparison of hemoglobin A1c with fasting plasma glucose and 2-h postchallenge glucose for risk stratification among women with recent gestational diabetes mellitus

OBJECTIVE

Postpartum testing with a 75-g 2-h oral glucose tolerance test or fasting plasma glucose (FPG) alone is often not performed among women with histories of gestational diabetes mellitus (GDM). Use of hemoglobin A_1c (A1C) might increase testing. The association between A1C and glucose has not been examined in women with histories of GDM.

RESEARCH DESIGN AND METHODS

We assessed the association of A1C ≥5.7% with FPG ≥100 mg/dL and 2-h glucose ≥140 mg/dL among 54 women with histories of GDM between 6 weeks and 36 months postpartum.

RESULTS

A1C ≥5.7% had 65% sensitivity and 68% specificity for identifying elevated FPG or 2-h glucose and 75% sensitivity and 62% specificity for elevated FPG alone. The area under the receiver operating characteristic curve for A1C was 0.76 for elevated FPG or 2-h glucose and 0.77 for elevated FPG alone.

CONCLUSIONS

The agreement between A1C and glucose levels is fair for detection of abnormal glucose tolerance among women with histories of GDM.Postpartum testing is recommended for women with histories of gestational diabetes mellitus (GDM) to diagnose diabetes and to stratify women for risk of future diabetes (1–3). Several groups have recommended postpartum testing with fasting plasma glucose (FPG) alone (1), others have recommended 2-h 75-g oral glucose tolerance tests (OGTTs) (2), and others have recommended hemoglobin A_1c (A1C) (4). Agreement between A1C and glucose has not yet been reported in this population. Our objective was to examine the agreement between A1C, FPG, and 2-h glucose among women with recent GDM.     

Development and validation of a risk assessment model for prediabetes in China national diabetes survey

BACKGROUNDPrediabetes risk assessment models derived from large sample sizes are scarce.AIMTo establish a robust assessment model for prediabetes and to validate the model in different populations.METHODSThe China National Diabetes and Metabolic Disorders Study (CNDMDS) collected information from 47325 participants aged at least 20 years across China from 2007 to 2008. The Thyroid Disorders, Iodine Status and Diabetes Epidemiological Survey (TIDE) study collected data from 66108 participants aged at least 18 years across China from 2015 to 2017. A logistic model with stepwise selection was performed to identify significant risk factors for prediabetes and was internally validated by bootstrapping in the CNDMDS. External validations were performed in diverse populations, including populations of Hispanic (Mexican American, other Hispanic) and non-Hispanic (White, Black and Asian) participants in the National Health and Nutrition Examination Survey (NHANES) in the United States and 66108 participants in the TIDE study in China. C statistics and calibration plots were adopted to evaluate the model’s discrimination and calibration performance.RESULTSA set of easily measured indicators (age, education, family history of diabetes, waist circumference, body mass index, and systolic blood pressure) were selected as significant risk factors. A risk assessment model was established for prediabetes with a C statistic of 0.6998 (95%CI: 0.6933 to 0.7063) and a calibration slope of 1.0002. When externally validated in the NHANES and TIDE studies, the model showed increased C statistics in Mexican American, other Hispanic, Non-Hispanic Black, Asian and Chinese populations but a slightly decreased C statistic in non-Hispanic White individuals. Applying the risk assessment model to the TIDE population, we obtained a C statistic of 0.7308 (95%CI: 0.7260 to 0.7357) and a calibration slope of 1.1137. A risk score was derived to assess prediabetes. Individuals with scores ≥ 7 points were at high risk of prediabetes, with a sensitivity of 60.19% and specificity of 67.59%.CONCLUSIONAn easy-to-use assessment model for prediabetes was established and was internally and externally validated in different populations. The model had a satisfactory performance and could screen individuals with a high risk of prediabetes.