Prevalence and predictive modeling of undiagnosed diabetes and impaired fasting glucose in Taiwan: a Taiwan Biobank study
Authors' conclusion
Our results showed the changes in the prevalence of undiagnosed diabetes and IFG. The identified risk factors and the prediction models could be helpful in identifying individuals with undiagnosed diabetes or individuals with a high risk of developing diabetes in Taiwan.
Study context
- Population
- Individuals without known diabetes in Taiwan, Taiwan Biobank, 2012–2020
- Outcome
- Standardized prevalence of undiagnosed diabetes and IFG; risk prediction model for undiagnosed diabetes and IFG
- Follow-up
- 2012–2020
Methodological detailspopulation-based, Taiwan Biobank linked with National Health Insurance Research Database, forward continuation ratio model with Lasso penalty
- Population-based
- Taiwan Biobank linked with National Health Insurance Research Database
- Forward continuation ratio model with Lasso penalty
Main finding
As reported in the abstract
Undiagnosed diabetes, 2012-2014 / 2015-2016 / 2017-2018 / 2019-2020
1.11%, 0.99%, 1.16%, 0.99%
Impaired fasting glucose (IFG)_110 (fasting glucose 110–125 mg/dL), same periods
4.49%, 3.73%, 4.30%, 4.66%
IFG_100 (fasting glucose 100–125 mg/dL), same periods
21.0%, 18.26%, 20.16%, 21.08%
Observational data: associations, not effects.
Further findings
Risk prediction factors
- Significant risk prediction factors: age, BMI, WHR, education level, personal monthly income, betel nut chewing, self-reported hypertension, family history of diabetes
Prediction model performance (AUC)
- AUC for undiagnosed diabetes, Model 1 (IFG_110)
- 80.39%
- AUC for undiagnosed diabetes, Model 2 (IFG_100)
- 77.87%
- AUC for undiagnosed diabetes or IFG, Model 1
- 78.25%
- AUC for undiagnosed diabetes or IFG, Model 2
- 74.39%
Original publication
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