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This paper is in the following e-collection/theme issue:

Reviews on Public Health Technology and Innovation (194) Secondary Use of Clinical Data for Research and Surveillance (630) Innovative Methods in Public Health and Surveillance (509) Digital Health Meta-Research and Bibliographic Studies (117)

Published on in Vol 11 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/62939, first published .
Red tractor plowing a field with green crops on the right

Leveraging Administrative Health Databases to Address Health Challenges in Farming Populations: Scoping Review and Bibliometric Analysis (1975-2024)

Leveraging Administrative Health Databases to Address Health Challenges in Farming Populations: Scoping Review and Bibliometric Analysis (1975-2024)

Authors of this article:

Pascal Petit1 Author Orcid Image ;   Nicolas Vuillerme1, 2 Author Orcid Image
Article Authors Cited by (10) Tweetations Metrics

Journals

  1. Petit P, Vuillerme N. Global research trends on the human exposome: a bibliometric analysis (2005–2024). Environmental Science and Pollution Research 2025;32(13):7808 View
  2. Petit P, Bonneterre V, Vuillerme N, Chiappini S. Using Machine Learning and Nationwide Population‐Based Data to Unravel Predictors of Treated Depression in Farmers. Mental Illness 2025;2025(1) View
  3. Petit P, Vuillerme N. Datagraphy: toward a systematic approach to dataset discovery. GigaScience 2025;14 View
  4. Yang M, Bohnet-Joschko S. Thematic Mapping and Evolution of Social Media Mining in Health Research: Hybrid Bibliometric Synthesis. Journal of Medical Internet Research 2026;28:e86200 View
  5. Kakada P, Yuwanati M. Biochemical profiling of salivary monosodium glutamate in relation to dental caries: An observational analytical study. Folia Medica 2026;68(3) View
  6. Brunier S, Jouzel J, Prete G. From blood disorders to data disorder. The thwarted path from onco-haematology clinic to occupational cancer epidemiology. Social Science & Medicine 2026;405:119567 View
  7. Petit P, Berger F, Bonneterre V, Vuillerme N. Leveraging machine learning with real-world data for hypothesis generation by identifying exposomic predictors in Parkinson's disease among farmers. Journal of Parkinson’s Disease 2026 View
  8. Yang Z, Shen S, Preissner S, Preissner R. Pesticide exposure and multidomain symptom burden in Parkinson’s disease: a longitudinal triangulation study. npj Parkinson's Disease 2026;12(1) View

Books/Policy Documents

  1. Bandi J, Prakash D, Nelapati A, Dulla J, Venkateswarulu T. Cutting-Edge Strategies in Drug Delivery and Immunotherapy for Autoimmune Disorders. View
  2. Kumar P. Pesticides and Neurotoxicant Exposures. View