Overview of retrospective data harmonisation in the MINDMAP project: process and results

Area of Science:

• Gerontology
• Environmental Health
• Public Health

Background:

• The MINDMAP project established a multinational data infrastructure.
• It investigates urban environment effects on mental well-being and cognitive function in aging populations.
• Longitudinal data from six cohort studies were harmonized.

Purpose of the Study:

• To document the retrospective data harmonization process.
• To provide a descriptive analysis of the generated harmonized data.
• To create an integrated dataset for research on aging, mental well-being, and urban environments.

Main Methods:

• Defined a core variable list (DataSchema).
• Assessed cohort data potential for generating DataSchema variables.
• Developed algorithms for data processing and documented harmonization decisions.

Main Results:

• The MINDMAP DataSchema (v2.0) includes 2841 variables.
• Harmonized data covers 220,621 participants from six cohorts.
• Data harmonization revealed variations in potential, distributions, and missing values.

Conclusions:

• MINDMAP created a collaborative and transparent process for data integration.
• The harmonized dataset supports diverse research activities.
• The dataset will be updated for future research needs.