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Hypertension, Diabetes and Depression as Modifiable Risk Factors for Dementia: A Common Data Model Approach in a
Corrado Zenesini1, Silvia Cascini2, Roberta Picariello3
1IRCCS Istituto delle Scienze Neurologiche di Bologna, 40139 Bologna, Italy.
Journal of Clinical Medicine
|September 27, 2025
Summary
This study explored how hypertension, diabetes, and depression impact dementia risk in over 3 million adults using Italian health data. The findings highlight the feasibility of large-scale dementia prevention research.
Area of Science:
- Epidemiology
- Public Health
- Gerontology
Background:
- Dementia poses a significant public health challenge, with aging as a primary risk factor.
- Modifiable conditions like hypertension, diabetes, and depression are potential targets for dementia prevention strategies.
- Understanding the interplay of these conditions is crucial for effective interventions.
Purpose of the Study:
- To describe the methodology and preliminary results of a study assessing the impact of hypertension, diabetes, and depression on dementia onset.
- To evaluate the interactions between these chronic conditions and their combined effect on dementia risk.
- To demonstrate the feasibility of a multi-regional, Common Data Model (CDM) approach within the Italian National Health Service (INHS).
Main Methods:
- A population-based cohort study (PREV-ITA-DEM project) utilizing a Common Data Model (CDM) across five Italian regions.
- Inclusion of individuals aged ≥ 50 years without prior diagnoses of dementia, depression, diabetes, or hypertension.
- Follow-up from 2011-2013 to 2019-2022, with time-dependent exposure assessment using Healthcare Utilization Databases (HUDs).
- Analysis using competing risks regression models adjusted for confounders, with pooled results via meta-analysis.
Main Results:
- A cohort of over 3 million individuals (mean age 63-65, 52-55% female) was established.
- Baseline dementia prevalence in individuals aged ≥ 50 years ranged from 8.7 to 14.7 per 1000 population.
- A harmonized methodological framework using CDM was successfully implemented across all participating sites.
Conclusions:
- The study confirms the feasibility of a standardized, multi-regional CDM approach for dementia research.
- Healthcare Utilization Databases (HUDs) are valuable resources for large-scale dementia prevention studies in real-world settings.
- This methodology provides a robust framework for investigating chronic conditions and dementia risk.
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