Detection of High Risk People for Diabetes by American Diabetes Association Risk Score in PERSIAN Guilan Cohort Study

Overview

Journal BMC Endocr Disord

Publisher Biomed Central

Specialty Endocrinology

Date 2023 Jan 10

PMID 36627658

Authors

Tolou Hasandokht

Farahnaz Joukar

Saman Maroufizadeh

Zahra Sibeveih

Mohammadreza Naghipour

Zahra Hedayaztadeh

Fariborz Mansour-Ghanaei

Affiliations

Soon will be listed here.

Abstract

Background: Diabetes mellitus (DM) is known as one of the most prevalent non communicable diseases with high cost of health services in the world. Present study was conducted to assess the frequency of high risk people for diabetes mellitus based on American Diabetes Association (ADA) risk score among Iranian people.

Methods: Present study was a cross sectional study on non-diabetic subjects aged 35-70 years from 10,520 PERSIAN Guilan Cohort Study (PGCS). ADA risk score was calculated for every individual through an online calculator. Receiver operating characteristic (ROC) curves was used to assess diagnostic accuracy of the anthropometric indices to identify individuals with high risk ADA score for developing DM, represented by the area under the curve (AUC).

Results: From 7989 study subjects, ADA risk score found 3874 (48.5%) and 1912 (23%) at risk for developing PreDM and DM, respectively. The results of ROC curve analyses showed the highest diagnostic value was related to waist circumference (WC) in total population and Waist to Height Ratio in both sex (0.695 total, 0.743 female, 0.744 male). The cut-points of WC in total population to identifying high risk group were 97 cm.

Conclusions: A considerable number of populations were classified as high ADA risk for developing DM and PreDM that provide the importance of prevention strategies. Present study showed WC and Waist to Height Ratio have the highest diagnostic value to identify high risk people for DM.

Citing Articles

Indirect estimation of the prevalence of type 2 diabetes mellitus in the sub-population of Tehran: using non-laboratory risk-score models in Iran.

Azizpour Y, Asgari S, Yaseri M, Fotouhi A, Akbarpour S BMC Public Health. 2024; 24(1):2797.

PMID: 39395938 PMC: 11470634. DOI: 10.1186/s12889-024-20278-2.

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