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Updated: Jul 15, 2025

Methodology for Establishing a Community-Wide Life Laboratory for Capturing Unobtrusive and Continuous Remote Activity and Health Data
Published on: July 27, 2018
Data-driven lifestyle patterns and risk of dementia in older Australian women
Sara E Dingle1, Steven J Bowe2,3, Melissa Bujtor1,4
1Institute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Victoria, Australia.
Introduction:
Many lifestyle factors have been associated with dementia, but there is limited evidence of how these group together. The aim of this study was to examine the clustering of lifestyle behaviors and associations with dementia.
Methods:
This population-based study included 9947 older Australian women. Latent class analysis was employed to identify distinct lifestyle classes, and Cox proportional hazard regression compared these with incident dementia over 17 years.
Results:
Three classes were identified: (1) "highly social and non-smokers" (54.9%), (2) "highly social, smokers, and drinkers" (25.1%), and (3) "inactive and low socializers" (20.0%). Women in Class 3 exhibited a higher risk of dementia compared to both Class 1 (hazard ratio [HR] = 1.19, 95% confidence interval [CI]: 1.08 to 1.30) and Class 2 (HR = 1.12, 95% CI: 1.00 to 1.25).
Discussion:
A lifestyle pattern characterized by physical inactivity and low social engagement may be particularly detrimental for dementia risk in older women and should be prioritized in preventive strategies.
Highlights:
Latent class analysis was employed to identify distinct lifestyle clusters. Three lifestyle-related clusters were differentially associated with dementia risk. Inactive and low socializers exhibited the greatest risk of dementia. Targeting physical inactivity and low social engagement in prevention is vital.
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