Agreement Between Non-Invasive Type 2 Diabetes Risk Assessment Models and Associated Demographic and Socioeconomic Factors: A Cross-Sectional Study in Iranian Adults.
- 1Neuroscience Research Center, Institute of Neuropharmacology, Kerman University of Medical Sciences, Kerman, Iran.
- 2Social Determinants of Health Research Center, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran.
- 3Department of Community Medicine, Shiraz University of Medical Sciences, Shiraz, Iran.
Abstract
Introduction
Non-invasive tools are recommended to identify individuals at high risk of type 2 diabetes. Agreement between validated models is unclear. This study assessed agreement between four risk-assessment models among adults attending health posts in Kerman, Iran.Methods
In this cross-sectional study, 430 adults aged≥30 years attending health posts in Kerman, Iran, were selected by multistage random sampling. Data collected by interview and examination were used to calculate FINDRISC, ModAsian FINDRISC, ADA, and AUSDRISK risk scores. Agreement was assessed with Cohen's kappa; logistic regression identified correlates of discordant classification.Results
Agreement between AUSDRISK and ADA was poor (kappa=-0.06, 95% CI -0.07 to -0.05, P<0.001); 45.1% were high-risk by AUSDRISK but low-risk by ADA. Discordant high-risk individuals were younger, with higher BMI and waist circumference, lower physical activity, lower fruit/vegetable intake, and more hyperglycaemia. Waist circumference, male sex, and employment independently predicted discordance. Agreement between FINDRISC and ModAsian FINDRISC was moderate (kappa=0.536, 95% CI 0.48-0.60, P<0.001); 65.3% were classified into the same category by both tools, with most discordance reflecting ModAsian FINDRISC assigning a higher category than FINDRISC. Male sex was the strongest independent predictor of discordance between these two tools; BMI and low socioeconomic status were not statistically significant.Conclusion
Agreement between these tools was poor to moderate and varied by demographic context, indicating a need for population-based calibration. As no glycaemic outcome was measured, this study cannot establish predictive accuracy; prospective validation and calibration studies are needed to determine the most appropriate model.
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BibTeX
@article{momeni2026agreement,
title = {{Agreement Between Non-Invasive Type 2 Diabetes Risk Assessment Models and Associated Demographic and Socioeconomic Factors: A Cross-Sectional Study in Iranian Adults.}},
author = {Mohsen Momeni and Paria Dehesh and Mehrdad Askarian and Mina Danaei},
journal = {Health promotion perspectives},
year = {2026},
month = aug,
doi = {10.34172/hpp.45086},
url = {https://europepmc.org/article/MED/42968736},
note = {CC BY},
}
RIS
TY - JOUR
TI - Agreement Between Non-Invasive Type 2 Diabetes Risk Assessment Models and Associated Demographic and Socioeconomic Factors: A Cross-Sectional Study in Iranian Adults.
AU - Mohsen Momeni
AU - Paria Dehesh
AU - Mehrdad Askarian
AU - Mina Danaei
PY - 2026
DA - 2026/08/21
JO - Health promotion perspectives
DO - 10.34172/hpp.45086
UR - https://europepmc.org/article/MED/42968736
AB - Introduction Non-invasive tools are recommended to identify individuals at high risk of type 2 diabetes. Agreement between validated models is unclear. This study assessed agreement between four risk-assessment models among adults attending health posts in Kerman, Iran.Methods In this cross-sectional study, 430 adults aged≥30 years attending health posts in Kerman, Iran, were selected by multistage random sampling. Data collected by interview and examination were used to calculate FINDRISC, ModAsian FINDRISC, ADA, and AUSDRISK risk scores. Agreement was assessed with Cohen's kappa; logistic regression identified correlates of discordant classification.Results Agreement between AUSDRISK and ADA was poor (kappa=-0.06, 95% CI -0.07 to -0.05, P<0.001); 45.1% were high-risk by AUSDRISK but low-risk by ADA. Discordant high-risk individuals were younger, with higher BMI and waist circumference, lower physical activity, lower fruit/vegetable intake, and more hyperglycaemia. Waist circumference, male sex, and employment independently predicted discordance. Agreement between FINDRISC and ModAsian FINDRISC was moderate (kappa=0.536, 95% CI 0.48-0.60, P<0.001); 65.3% were classified into the same category by both tools, with most discordance reflecting ModAsian FINDRISC assigning a higher category than FINDRISC. Male sex was the strongest independent predictor of discordance between these two tools; BMI and low socioeconomic status were not statistically significant.Conclusion Agreement between these tools was poor to moderate and varied by demographic context, indicating a need for population-based calibration. As no glycaemic outcome was measured, this study cannot establish predictive accuracy; prospective validation and calibration studies are needed to determine the most appropriate model.
SN - 2228-6497
ER -