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Updated: Jan 8, 2026

A High-Throughput Multiplexed Screening for Type 1 Diabetes, Celiac Diseases, and COVID-19
Published on: July 5, 2022
Predictive power of youth diabetes screening guidelines
Sarah M Halvorson-Fried1,2, Nita Vangeepuram3,4,5, Negar Golestani6
1Division of General Internal Medicine, Icahn School of Medicine at Mount Sinai.
Introduction:
Early-onset type 2 diabetes (EOD), defined as type 2 diabetes diagnosed before age 45, is a growing public health problem. Adolescence is a critical period for prevention interventions because related health behaviors and biological processes are established during this time. Early screening for type 2 diabetes risk including prediabetes (preDM) could identify youth most in need of intervention but unlike for adults, no questionnaire-based youth risk screeners exist. In this study, we assessed the ability of adapted American Diabetes Association (ADA) screening guidelines in adolescence to predict EOD and prediabetes (preDM/EOD) in adulthood.
Methods:
We used data from the National Longitudinal Study of Adolescent to Adult Health (Add Health). We applied ADA guidelines (modified to align with available data) in Waves I and II, when participants were 12-19, and assessed ability to predict preDM/EOD in Waves IV and V, when participants were 24-43. We then calculated screening performance measures with (N=13,530) and without (N=14,540) accounting for the survey design.
Results:
In weighted analyses, 40% of participants (5,383) had preDM/EOD based on biomarkers at Waves IV-V. Of these participants, 1,272 were considered at risk according to the ADA screening criteria in Waves I-II (sensitivity=23.6%). Of 8,147 participants without preDM/EOD, 7,218 were not considered at risk in Wave I-II (specificity=88.6%). The screening guidelines had a positive predictive value (PPV) of 57.8% and a negative predictive value (NPV) of 63.7%. The F+ and F- measures were 33.5% and 74.1%, respectively. Unweighted analyses produced similar results.
Conclusions:
Adapted ADA youth screening guidelines demonstrated poor ability to predict preDM/EOD before age 45. Although specificity was high, sensitivity was low: 76% of participants who developed preDM/EOD would not have been identified as at risk in adolescence using the adapted ADA guidelines. Given the high prevalence of preDM/EOD, there is a need for better screening tools to identify youth at risk and better target diabetes prevention interventions.
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