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Insomnia as an Independent Behavioral Correlate of Estimated Type 2 Diabetes Risk: Evidence from Three Validated Risk
José Luis Ribes Valles1, Pedro Juan Tárraga López2, Ángel Arturo López González3,4
1Clinical Analysis Laboratory, Son Llatzer Hospital, Palma, Spain.
Rambam Maimonides Medical Journal
|August 4, 2026
Summary
Severe insomnia significantly increases type 2 diabetes (T2DM) risk, independent of other factors. Integrating insomnia assessment into T2DM risk tools can improve early prevention strategies.
Area of Science:
- Occupational health
- Endocrinology
- Sleep medicine
Background:
- Sleep disturbances, especially insomnia, are emerging as key behavioral factors in type 2 diabetes development.
- The impact of insomnia on established diabetes risk scores, beyond traditional risk factors, requires further investigation.
Purpose of the Study:
- To evaluate the association between insomnia severity, sociodemographic factors, lifestyle, and estimated type 2 diabetes (T2DM) risk.
- To assess T2DM risk using three validated non-invasive risk assessment scales, incorporating insomnia severity.
Main Methods:
- A large-scale cross-sectional study of 84,898 Spanish workers (aged 18-69) was conducted.
- Data on sociodemographics, lifestyle (Mediterranean diet, physical activity, smoking), and insomnia severity (Insomnia Severity Index - ISI) were collected.
- Three validated T2DM risk scores (Finnish, QDScore/QDiabetes, Trinidad) were used to estimate diabetes risk.
Main Results:
- Severe insomnia was linked to a 2.1-2.6 times higher odds of high estimated T2DM risk across all assessment scales.
- Significant trends in risk were observed across insomnia severity categories (P < 0.001).
- Inclusion of ISI scores modestly improved diabetes risk prediction models' discrimination and reclassification.
Conclusions:
- Insomnia severity is an independent predictor of elevated T2DM risk, beyond established sociodemographic and lifestyle factors.
- Integrating simple sleep health assessments, like the ISI, into T2DM risk evaluations can enhance early detection and prevention efforts.
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