Deep phenotyping meets big data: the Geoscience and hEalth Cohort COnsortium (GECCO) data to enable exposome studies in The Netherlands

Jeroen Lakerveld*, Alfred Wagtendonk, Ilonca Vaartjes, Derek Karssenberg, GECCO Consortium, Annemarie Koster, Coen Stehouwer

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review


Environmental exposures are increasingly investigated as possible drivers of health behaviours and disease outcomes. So-called exposome studies that aim to identify and better understand the effects of exposures on behaviours and disease risk across the life course require high-quality environmental exposure data. The Netherlands has a great variety of environmental data available, including high spatial and often temporal resolution information on urban infrastructure, physico-chemical exposures, presence and availability of community services, and others. Until recently, these environmental data were scattered and measured at varying spatial scales, impeding linkage to individual-level (cohort) data as they were not operationalised as personal exposures, that is, the exposure to a certain environmental characteristic specific for a person. Within the Geoscience and hEalth Cohort COnsortium (GECCO) and with support of the Global Geo Health Data Center (GGHDC), a platform has been set up in The Netherlands where environmental variables are centralised, operationalised as personal exposures, and used to enrich 23 cohort studies and provided to researchers upon request. We here present and detail a series of personal exposure data sets that are available within GECCO to date, covering personal exposures of all residents of The Netherlands (currently about 17 M) over the full land surface of the country, and discuss challenges and opportunities for its use now and in the near future.

Original languageEnglish
Article number49
Number of pages16
JournalInternational Journal of Health Geographics
Issue number1
Publication statusPublished - 13 Nov 2020


  • Big data
  • Cohorts
  • Data science
  • Environment
  • Exposome
  • Exposure
  • Non-communicable disease
  • Prevention
  • Upstream determinants

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