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Updated: Feb 8, 2026

A High-Throughput Multiplexed Screening for Type 1 Diabetes, Celiac Diseases, and COVID-19
Published on: July 5, 2022
Screening models for undiagnosed diabetes in Mexican adults using clinical and self-reported information
Gerardo J Félix-Martínez1, J Rafael Godínez-Fernández2
1Department of Electrical Engineering, Universidad Autónoma Metropolitana, Iztapalapa, Ciudad de México, Mexico; Department of Applied Mathematics and Computer Sciences, Universidad de Cantabria, Santander, Cantabria, Spain.
Background:
Prevalence of diabetes in Mexico has constantly increased since 1993. Since type 2 diabetes may remain undiagnosed for many years, identification of subjects at high risk of diabetes is very important to reduce its impact and to prevent its associated complications.
Objective:
To develop easily implementable screening models to identify subjects with undiagnosed diabetes based on the characteristics of Mexican adults.
Subjects And Methods:
Screening models were developed using datasets from the 2006 and 2012 National Health and Nutrition Surveys (NHNS). Variables used to develop the multivariate logistic regression models were selected using a backward stepwise procedure. Final models were validated using data from the 2000 National Health Survey (NHS).
Results:
The model based on the 2006 NHNS included age, waist circumference, and systolic blood pressure as explanatory variables, while the model based on the 2012 NHNS included age, waist circumference, height, and family history of diabetes. The sensitivity and specificity values obtained from the external validation procedure were 0.74 and 0.62 (2006 NHNS model) and 0.76 and 0.55 (2012 NHNS model) respectively.
Conclusions:
Both models were equally capable of identifying subjects with undiagnosed diabetes (∼75%), and performed satisfactorily when compared to other models developed for other regions or countries.
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