Abstract
Background
The MINDMAP project implemented a multinational data infrastructure to
investigate the direct and interactive effects of urban environments and
individual determinants of mental well-being and cognitive function in ageing
populations. Using a rigorous process involving multiple teams of experts,
longitudinal data from six cohort studies were harmonised to serve MINDMAP
objectives. This article documents the retrospective data harmonisation process
achieved based on the Maelstrom Research approach and provides a descriptive
analysis of the harmonised data generated.
Methods
A list of core variables (the DataSchema) to be generated across cohorts
was first defined, and the potential for cohort-specific data sets to generate
the DataSchema variables was assessed. Where relevant, algorithms were
developed to process cohort-specific data into DataSchema format, and
information to be provided to data users was documented. Procedures and
harmonisation decisions were thoroughly documented.
Results
The MINDMAP DataSchema (v2.0, April 2020) comprised a total of 2841
variables (993 on individual determinants and outcomes, 1848 on environmental
exposures) distributed across up to seven data collection events. The
harmonised data set included 220 621 participants from six cohorts (10
subpopulations). Harmonisation potential, participant distributions and missing
values varied across data sets and variable domains.
Conclusion
The MINDMAP project implemented a collaborative and transparent process to
generate a rich integrated data set for research in ageing, mental well-being
and the urban environment. The harmonised data set supports a range of research
activities and will continue to be updated to serve ongoing and future MINDMAP
research needs.
Funder
Netherlands
Organization for Scientific Research
Canadian
Institutes of Health Research
Horizon 2020
Framework Programme
Canada
Foundation for Innovation
Subject
Public Health, Environmental and Occupational Health,Epidemiology
Cited by
11 articles.
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