Umbrella review and Delphi study on modifiable factors for dementia risk reduction.

A 2013 systematic review and Delphi consensus study identified 12 modifiable risk and protective factors for dementia, which were subsequently merged into the "LIfestyle for BRAin health" (LIBRA) score. We systematically evaluated whether LIBRA requires revision based on new evidence. To identify modifiable risk and protective factors suitable for dementia risk reduction, we combined an umbrella review of systematic reviews and meta-analyses with a two-round Delphi consensus study. The review of 608 unique primary studies and opinions of 18 experts prioritized six modifiable factors: hearing impairment, social contact, sleep, life course inequalities, atrial fibrillation, and psychological stress. Based on expert ranking, hearing impairment, social contact, and sleep were considered the most suitable candidates for inclusion in updated dementia risk scores. As such, the current study shows that dementia risk scores need systematic updates based on emerging evidence. Future studies will validate the updated LIBRA score in different cohorts. HIGHLIGHTS: An umbrella review was combined with opinions of 18 dementia experts. Various candidate targets for dementia risk reduction were identified. Experts prioritized hearing impairment, social contact, and sleep. Re-assessment of dementia risk scores is encouraged. Future work should evaluate the predictive validity of updated risk scores.

Validation of the Updated "LIfestyle for BRAin health" (LIBRA) Index in the English Longitudinal Study of Ageing and Maastricht Aging Study.

Background: The "LIfestyle for BRAin health" (LIBRA) index was recently updated with three new modifiable factors: hearing impairment, social contact, and sleep (LIBRA2), but has not yet been validated. Objective: Comparison of the performance of both LIBRA versions in predicting dementia risk. Methods: Longitudinal data from the English Longitudinal Study of Ageing (ELSA) and the Maastricht Aging Study (MAAS) were used. The weighted LIBRA (11/12 factors available) and LIBRA2 (14/15 factors available) scores were calculated, with higher scores representing an unhealthier lifestyle. Dementia diagnoses were based on self- or informant reported physician diagnosis, an informant-based cognitive screening tool, registry data or test data. Cox-proportional hazards regression was used to investigate the association between LIBRA(2) scores and dementia risk. Model fit and predictive accuracy were determined using the Akaike information criterion and Harrell's C index. Results: Over an average follow-up of 8.3 years in ELSA and 17.9 years in MAAS, 346 (4.6%) and 120 (8.5%) individuals developed dementia, respectively. In ELSA, a one-point increase in LIBRA2 was associated with an 8% (1.06-1.11) higher dementia risk (LIBRA: 13%, 1.09-1.16). In MAAS, a one-point increase in LIBRA2 was associated with a 6% (1.01-1.12) higher dementia risk (LIBRA: 8%, 0.99-1.16). In ELSA, LIBRA (Harrell's C = 0.68) and LIBRA2 (Harrell's C = 0.67) performed similarly. In MAAS, LIBRA2 (Harrell's C = 0.62) performed better compared to LIBRA (Harrell's C = 0.52). Conclusions: LIBRA2 is a better model for identifying individuals at increased dementia risk and for public health initiatives aimed at dementia risk reduction.