Toward targeted dementia prevention: Population attributable fractions and risk profiles in Germany

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.

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.

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.

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.

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.