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

Yi ZhangShi-Dong ChenYue-Ting DengJia YouXiao-Yu HeXin-Rui WuBang-Sheng WuLiu YangYa-Ru ZhangKevin KuoJian-Feng FengWei ChengJohn SucklingA David SmithJin-Tai Yu
Published in: Nature human behaviour (2023)
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.
Keyphrases
  • mild cognitive impairment
  • risk factors
  • cognitive impairment
  • type diabetes
  • metabolic syndrome
  • healthcare
  • physical activity
  • electronic health record
  • machine learning