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@INPROCEEDINGS{Wittmann:283084,
      author       = {Wittmann, Felix Georg and Röhr, Susanne and Köhler,
                      Sebastian and Janssen, Niels and Luppa, Melanie and Wagner,
                      Michael and Kleineidam, Luca and Berger, Klaus and Pabst,
                      Alexander and Riedel-Heller, Steffi G.},
      title        = {{S}ame risk – different profile? {I}dentification of
                      different risk profiles for dementia in the {G}erman
                      {N}ational {C}ohort {NAKO}},
      journal      = {Alzheimer's and dementia},
      volume       = {21},
      number       = {S6},
      issn         = {1552-5260},
      reportid     = {DZNE-2025-01491},
      pages        = {e106369},
      year         = {2025},
      abstract     = {Background:Risk and protective factors for dementia are
                      well established. Multidomain lifestyle interventions have
                      shown promise in reducing dementia risk, yet their
                      effectiveness often varies across predictors and subgroups.
                      To enhance prevention strategies, it is crucial to tailor
                      interventions more effectively. While research is focusing
                      on single risk factors or sum scores, evidence on more
                      specific risk profiles is lacking. The LIfestyle for BRAin
                      Health (LIBRA) index is a standardized index to calculate
                      dementia risk by integrating modifiable risk and protective
                      factors. We aimed to identify distinct risk profiles for
                      dementia based on the LIBRA factors.Method:Using a
                      three-step procedure, a Latent Class Analysis was conducted
                      with n = 106,192 participants of the German National Cohort
                      (NAKO; aged 40–75, mean age 51.4 years, $49.4\%$ women) to
                      identify distinct classes (i.e. risk profiles). Ten LIBRA
                      factors (coronary heart disease, hypertension, diabetes,
                      hypercholesterolemia, depression, obesity, smoking, alcohol
                      consumption, physical inactivity, and low social
                      participation) were used as indicators, followed by analyses
                      of sociodemographic predictors of class membership and
                      class-specific differences in cognitive functioning
                      accounting for classification uncertainty.Result:A latent
                      four-class model fitted the data best: The largest class
                      $(>60\%)$ represents a low-risk group with low probabilities
                      across all factors. A second class $(∼16\%)$ was defined
                      by cardiometabolic risks (high probabilities of
                      hypercholesterolemia, hypertension and comparatively high
                      values for heart disease and diabetes). A third class
                      $(14\%)$ is mainly defined by low social participation but
                      also high smoking rates and comparatively higher physical
                      inactivity, alcohol intake, and depression. The fourth and
                      smallest class $(∼8\%)$ consisted entirely of individuals
                      with obesity and high hypertension probability. Results are
                      preliminary and will be detailed regarding predictors and
                      cognitive functioning at the
                      conference.Conclusion:Identifying four distinct dementia
                      risk profiles offers the potential for more targeted
                      prevention strategies. Instead of a one-size-fits-all
                      approach, tailored interventions may yield greater benefits
                      for individuals characterized by a specific high-risk
                      profile. Highlighting the importance of replication and
                      validation in future studies, these findings have the
                      potential to reshape intervention study designs and public
                      health campaigns. Early interventions could be better
                      tailored, ultimately contributing to more effective dementia
                      risk reduction.},
      month         = {Jul},
      date          = {2025-07-27},
      organization  = {Alzheimer’s Association
                       International Conference, Toronto
                       (Canada), 27 Jul 2025 - 31 Jul 2025},
      cin          = {AG Wagner},
      ddc          = {610},
      cid          = {I:(DE-2719)1011201},
      pnm          = {353 - Clinical and Health Care Research (POF4-353)},
      pid          = {G:(DE-HGF)POF4-353},
      typ          = {PUB:(DE-HGF)1 / PUB:(DE-HGF)16},
      doi          = {10.1002/alz70860_106369},
      url          = {https://pub.dzne.de/record/283084},
}