Assessing Risk for Development of Diabetes in Young Adults

Department of Family Medicine, Medical University of South Carolina, Charleston, South Carolina, United States
The Annals of Family Medicine (Impact Factor: 5.43). 09/2007; 5(5):425-9. DOI: 10.1370/afm.705
Source: PubMed


The prevalence of diabetes is increasing to epidemic levels. A multivariable risk score for the development of diabetes has been shown to be predictive for middle-aged adults; however, it is unclear how well it performs in a younger adult population. The purpose of this study was to evaluate a preexisting multivariable risk score for the development of diabetes in a young adult cohort.
We analyzed the Coronary Artery Risk Development in Young Adults (CARDIA), a population-based observational study of participants aged 18 to 30 years recruited in 1985-1986. We observed individuals without diabetes at baseline for 10 years for the development of diabetes (n = 2,543). We computed receiver operating characteristic (ROC) curves for a diabetes risk score composed of the following 6 variables: elevated blood pressure, low high-density lipoprotein cholesterol levels, high triglyceride levels, body mass index, large waist circumference, and hyperglycemia.
The area under the ROC curve was .70 in this population, which was less than the .78 previously found among middle-aged adults. BMI alone (.67) was not significantly different from the risk score. Blacks (.72; 95% CI, .69-.74) and whites (.68; 95% CI, .66-.71) do not significantly differ in the area under the ROC curve for the risk score; however, the area under the ROC curve for BMI is significantly larger for blacks (.69; 95% CI, .66-.72) than for whites (.63; 95% CI, .60-.65).
An established risk score for the development of diabetes among middle-aged persons has limited utility in a younger population. Future research needs to focus on identifying novel factors that may improve the risk stratification for diabetes development among young adults.

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Available from: Charles J. Everett, Dec 27, 2013
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    • "While choosing a model for prediction of diabetes the availability of risk factor data in the clinical setting, the optimal cut-point to define a positive test, and the simplicity of the model [13] must be considered. Some of previous studies are restricted with respect to age or sex [36, 37]; some used predictors like serum biomarkers, insulin resistance indices or surrogates, or genetic markers, which can only be measured by time-consuming, costly, or invasive testing procedures [38–40]. Complex models were shown to be unlikely to provide such increased predictive performances that justifies their complexity [40, 41]; this underscores the view that identification of adverse phenotypic characteristics remains the cornerstone of approaches for predicting the risk of diabetes [40–46]. "
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    ABSTRACT: Aims. To provide a yardstick for physicians/patients to efficiently communicate/measure incident diabetes risk. Methods. We included data on 5,960 (3,438 women) diabetes-free adults, aged ≥20 years at baseline who either developed diabetes during two consecutive examinations or completed the followup. Age, systolic blood pressure, family history of diabetes, waist-to-height ratio (WHtR), triglyceride-to-high-density lipoprotein cholesterol ratio (TG/HDLD-C), and fasting plasma glucose (FPG) were introduced into an accelerated failure time regression model. Results. Annual diabetes incidence rate was 0.85/1000-person (95% CIs 0.77–0.94). Point-score-system incorporated age (1 point for >65 years), family history of diabetes (4 points), systolic blood pressure (−1 to 3 points), WHtR (−4 to 6 points), TG/HDL-C (1 point for ≥1.5), and FPG (0 to 27 points). Harrell’s C statistic = 0.830 (95% CIs 0.808–0.852) and Hosmer-Lemeshow 𝜒 2 = 9 . 7 (P for lack of fitness = 0.462) indicated good discrimination and calibration. We defined beta-cell age as chronological age of a person with the same predicted risk but all risk factors at the normal levels (i.e., WHtR 0.50, no family history of diabetes, Ln (TG/HDL-C) = 0.531, and FPG = 4.9 (mmol·L−1)). Conclusion. Hereby, we have made it also possible to estimate wide ranges of “beta-cell age” for most chronological ages to assist clinician with risk communication.
    12/2012; 2013(12, supplement 5). DOI:10.5402/2013/541091
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    • "Furthermore, there is a lack of information about the consequences of ischemia on plantar foot sensitivity of healthy young adults, since sensory testing in this research area is usually carried out in elderly patients. Due to the increasing number of young adults being diagnosed with vascular diseases every year [14], investigating this population may provide first insight into initial adaptations caused by reduced blood flow in plantar foot sensitivity . Therefore, the goal of the present study was to investigate the effects of short-time ischemia on plantar foot vibration sensitivity of healthy young adults. "

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    The Annals of Family Medicine 09/2007; 5(5). DOI:10.1370/afm.771 · 5.43 Impact Factor
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