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A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Broadening dementia risk models: building on the 2024 Lancet Commission report for a more inclusive global framework
Cyprian M Mostert1, Chinedu Udeh-Momoh2, Andrea Sylvia Winkler3
1Global Brain Health Institute, The University of Dublin, Trinity College Institute of Neuroscience, D02 PN40, Ireland; Aga Khan University, Brain and Mind Institute, 3rd Parklands Avenue, Nairobi, 0010, Kenya; Department of Population Health, Aga Khan University, 3rd Parklands Avenue, Nairobi, 00100, Kenya.
Abstract:
The 2024 Lancet Commission Report on dementia prevention has identified 14 modifiable risk factors that account for approximately 45% of global dementia cases. We used a global multidimensional approach that integrates gender equity considerations, poverty, wealth shocks, income inequality and HIV infection rates to identify additional risk factors beyond those reported in 2024 report. This methodological framework aims to enhance equitable prevention strategies to mitigate the global burden of dementia. We demonstrate that adding four additional risk factors: poverty, wealth shocks, income inequality, and HIV, while also considering the influences of sex and gender will improve the global applicability of the 2024 report. This is important because, despite dementia primarily affecting women, 57% of the risk factors identified in the 2024 report are more prevalent in men. Our analysis suggests that incorporating these four additional factors could potentially increase the proportion of preventable dementia cases to about 65%. This approach would also reshape the understanding of dementia risk, indicating that around 56% of modifiable risks disproportionately impact women. Expanding risk models in this manner is crucial for developing equitable and effective global dementia prevention strategies, particularly in underrepresented regions. We present these considerations as enhancements to the Commission's significant work.
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