Towards Targeted Dementia Prevention: Population Attributable Fractions and Risk Profiles in Germany
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INTRODUCTION
Effective dementia prevention requires understanding the distribution of modifiable risk factors and identifying high-risk subgroups. We estimated the prevention potential in Germany and identified empirical risk profiles to inform precision public health.
METHODS
We analyzed nationally representative data from the 2023 German Ageing Survey. Population Attributable Fractions (PAFs) and Potential Impact Fractions (PIFs) were computed for established modifiable risk factors. Latent Class Analysis identified population-based risk profiles.
RESULTS
An estimated 36% of dementia cases in Germany are attributable to modifiable risk factors. Reducing their prevalence by 15–30% could prevent 170,000–330,000 cases by 2050. We identified four distinct risk profiles – metabolic, sensory impairment, alcohol consumption, and lower-risk – each associated with demographic and regional characteristics.
DISCUSSION
Our findings highlight considerable national prevention potential and reveal population subgroups with shared risk patterns. These profiles provide a novel foundation for designing targeted, equitable, and more efficient dementia prevention strategies.
