The Need for Standardized Data Collection to Improve Harmonization and Pooling of Information About Modifiable Risk Factors for Alzheimer’s Diseases in Italian Clinical Studies: A Systematic Review

Background/Objectives: At the international level, harmonized networks of dementia clinical studies are available, but Italian participation remains limited. This systematic review aims to define harmonization rules to facilitate the inclusion of Italian clinical studies in existing networks and to propose standardized data collection methods to enable comparison of the study results. Methods: A systematic review was conducted (January 2019–December 2024) to identify Italian clinical studies evaluating Alzheimer’s disease and other dementias as outcomes. Eight modifiable risk factors were extracted: BMI, arterial hypertension, diabetes, dietary patterns, alcohol consumption, smoking habits, depressive symptomatology, and physical activity. WHO definitions and internationally accepted criteria were used as reference standards. Variable harmonization potential was assessed using the DataSHaPER methodology and classified as complete, partial, or impossible, considering information loss across studies. Results: Of 365 records identified, 18 studies met the inclusion criteria. Obesity assessed via BMI showed the highest harmonization potential (44% complete, 33% partial), along with dietary habits measured by food frequency questionnaires (44% complete). Diabetes and physical inactivity followed (33% complete), assessed through fasting glucose or pharmacological treatment and the IPAQ, respectively. Smoking habits classified as current, former, or never smokers were reported in 28% of studies. Depression (assessed by GDS or CES-D) and hypertension (blood pressure measurement or antihypertensive treatment) showed complete harmonization in only 22% of studies. Conclusions: Italian studies show substantial limitations in the harmonization of modifiable risk factor data for Alzheimer’s disease, mainly due to heterogeneous and non-standardized data collection methods, highlighting the need for uniform research protocols.