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Identifying modifiable factors and their joint effect on dementia risk in the UK Biobank

Author

Listed:
  • Yi Zhang

    (National Center for Neurological Disorders)

  • Shi-Dong Chen

    (National Center for Neurological Disorders)

  • Yue-Ting Deng

    (National Center for Neurological Disorders)

  • Jia You

    (Fudan University
    Ministry of Education
    Zhejiang Normal University)

  • Xiao-Yu He

    (National Center for Neurological Disorders)

  • Xin-Rui Wu

    (National Center for Neurological Disorders)

  • Bang-Sheng Wu

    (National Center for Neurological Disorders)

  • Liu Yang

    (National Center for Neurological Disorders)

  • Ya-Ru Zhang

    (National Center for Neurological Disorders)

  • Kevin Kuo

    (National Center for Neurological Disorders)

  • Jian-Feng Feng

    (Fudan University
    Ministry of Education
    Zhejiang Normal University
    Fudan University)

  • Wei Cheng

    (National Center for Neurological Disorders
    Fudan University
    Ministry of Education
    Zhejiang Normal University)

  • John Suckling

    (University of Cambridge)

  • A. David Smith

    (University of Oxford)

  • Jin-Tai Yu

    (National Center for Neurological Disorders)

Abstract

Previous hypothesis-driven research has identified many risk factors linked to dementia. However, the multiplicity and co-occurrence of risk factors have been underestimated. Here we analysed data of 344,324 participants from the UK Biobank with 15 yr of follow-up data for 210 modifiable risk factors. We first conducted an exposure-wide association study and then combined factors associated with dementia to generate composite scores for different domains. We then evaluated their joint associations with dementia in a multivariate Cox model. We estimated the potential impact of eliminating the unfavourable profiles of risk domains on dementia using population attributable fraction. The associations varied by domain, with lifestyle (16.6%), medical history (14.0%) and socioeconomic status (13.5%) contributing to the majority of dementia cases. Overall, we estimated that up to 47.0%–72.6% of dementia cases could be prevented.

Suggested Citation

  • Yi Zhang & Shi-Dong Chen & Yue-Ting Deng & Jia You & Xiao-Yu He & Xin-Rui Wu & Bang-Sheng Wu & Liu Yang & Ya-Ru Zhang & Kevin Kuo & Jian-Feng Feng & Wei Cheng & John Suckling & A. David Smith & Jin-Ta, 2023. "Identifying modifiable factors and their joint effect on dementia risk in the UK Biobank," Nature Human Behaviour, Nature, vol. 7(7), pages 1185-1195, July.
    • Handle: RePEc:nat:nathum:v:7:y:2023:i:7:d:10.1038_s41562-023-01585-x
    DOI: 10.1038/s41562-023-01585-x
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