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| Main Authors: | , |
|---|---|
| Format: | Recurso digital |
| Language: | English |
| Published: |
Zenodo
2025
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| Subjects: | |
| Online Access: | https://doi.org/10.1002/dad2.70225 |
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Table of Contents:
- <p>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 risk profiles to inform precision public health. METHODS We analyzed nationally representative data from the 2023 German Aging Survey (n = 4992). Population attributable fractions and potential impact fractions were computed for established modifiable risk factors. Relative risks were taken from meta-analyses. Latent class analysis identified 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 risk profiles?metabolic, sensory impairment, alcohol, 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 foundation for designing targeted, equitable, and efficient dementia prevention strategies. Highlights 36% of dementia cases in Germany are linked to modifiable risk factors. A 15% reduction in risk factor prevalence could prevent 170,000 cases by 2050. Key contributors: depression, hearing loss, low education, and obesity. Data-driven risk profiles identified (e.g., metabolic, sensory, low-risk). Risk profiles strongly associated with sociodemographic characteristics.</p>