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Dementia Prevention: optimizing the use of observational data for personal, clinical, and public health decision-making.

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Dementia Prevention: optimizing the use of observational data for personal, clinical, and public health decision-making. The journal of prevention of Alzheimer's disease Dacks, P. A., Andrieu, S., Blacker, D., Carman, A. J., Green, A. M., Grodstein, F., Henderson, V. W., James, B. D., Lane, R. F., Lau, J., Lin, P., Reeves, B. C., Shah, R. C., Vellas, B., Yaffe, K., Yurko-Mauro, K., Shineman, D. W., Bennett, D. A., Fillit, H. M. 2014; 1 (2): 117-123

Abstract

Worldwide, over 35 million people suffer from Alzheimer's disease and related dementias. This number is expected to triple over the next 40 years. How can we improve the evidence supporting strategies to reduce the rate of dementia in future generations? The risk of dementia is likely influenced by modifiable factors such as exercise, cognitive activity, and the clinical management of diabetes and hypertension. However, the quality of evidence is limited and it remains unclear whether specific interventions to reduce these modifiable risk factors can, in turn, reduce the risk of dementia. Although randomized controlled trials are the gold-standard for causality, the majority of evidence for long-term dementia prevention derives from, and will likely continue to derive from, observational studies. Although observational ÌÇÐÄ´«Ã½ has some unavoidable limitations, its utility for dementia prevention might be improved by, for example, better distinction between confirmatory and exploratory ÌÇÐÄ´«Ã½, higher reporting standards, investment in effectiveness ÌÇÐÄ´«Ã½ enabled by increased data-pooling, and standardized exposure and outcome measures. Informed decision-making by the general public on low-risk health choices that could have broad potential benefits could be enabled by internet-based tools and decision-aids to communicate the evidence, its quality, and the estimated magnitude of effect.

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