Among older adults, late-onset dementia is highly prevalent with more than 30 per cent of adults aged over 80 years developing the disease. No cure is available and recent trials of potential pharmacological treatments have been disappointing. A key problem is that the neuropathological mechanisms underlying the disease processes are multi-factorial – particularly for common dementias like that of the Alzheimer’s and vascular types. So, treatments that target a single biological pathway are unlikely to be effective for all cases. These multiple factors are mostly related to lifestyle and preventable chronic disease. Data from studies of many thousands of individuals followed-up over decades have shown that certain modifiable risk factors are associated with a substantially increased risk of developing Alzheimer’s disease and other dementias. These risk factors include cardiovascular disease, diabetes, high cholesterol, obesity, dietary intake, physical and cognitive inactivity, low social engagement, low education and depression (Anstey, Eramudugolla, & Dixon, 2014). At the cutting edge of dementia research, these findings have led to an international race to develop effective non-pharmacological interventions for preventing dementia. Given that the disease course for late-onset dementias is typically decades long, with neuropathology that gradually accumulates over that time, interventions that target vascular and lifestyle risk factors in midlife have the greatest chance of reducing dementia risk.
Multi-domain interventions to reduce risk
Because vascular and lifestyle risk factors are highly interrelated, ‘multi-domain’ interventions are currently favoured to reduce risk of dementia. These target several key risk factors simultaneously. For example, a large Finnish trial includes physical and cognitive activity as well as vascular risk management (Ngandu et al., 2015). There is also increasing focus on midlife as a critical time for commencing dementia risk reduction strategies because this is the time when many people develop hypertension, obesity and high cholesterol and when adults consider making changes to their lifestyles for their own ageing. Working with middle-aged adults the efficacy of short-term interventions is evaluated in terms of level of risk reduction rather than dementia outcome, so that evidence-based advice may be made available for current cohorts while continued follow-up of individuals over time will indicate efficacy in terms of dementia prevention.
Body, Brain, Life online program
The Body, Brain, Life program takes this multi-domain approach to dementia risk reduction and adapts it to a low-cost, accessible, population scale intervention that is evidence-based and individually tailored (Anstey et al., 2015). To achieve this, an online dementia risk screening tool (the ANU-Alzheimer’s Disease Risk Index) is used to estimate an individual’s risk of developing dementia (Anstey et al., 2014). This tool uses only self-reported measures of health behaviours and chronic conditions and can be self-administered. The individual’s ANU-ADRI score can then be used to tailor an online psycho-educational program called ‘Body Brain Life’ (BBL). The BBL program is a 12-week self-administered intervention that includes modules to increase dementia risk literacy and to promote behaviour change using theory driven techniques. A randomised controlled trial of the BBL-online program with 126 midlife volunteers demonstrated a significant increase in their level of engaging in health protective behaviours (e.g., increased cognitive activity and dietary change). The BBL program is currently being trialled in a large general practice setting, with support from an exercise physiologist and dietician.
It has been estimated that an achievable 10 to 25 per cent reduction in seven key risk factors could prevent 1.1 to 3 million Alzheimer’s disease cases internationally per annum (Norton, Matthews, Barnes, Yaffe, & Brayne, 2014). In Australia, an intervention that could delay the onset of dementia by two years, if introduced in 2020, would reduce the cumulative number of people developing dementia between 2020 and 2050 by 13 per cent, or nearly 400,000 cases. Indeed, globally, the impact of population ageing and dementia is likely to be most apparent in lower income countries, where fewer resources are available for dementia prevention. A low-cost and self-administered multi-domain dementia risk reduction program could result in significant impacts in terms of global dementia prevention.
Modifiable risk factors associated with increased risk of developing Alzheimer’s disease and other dementias:
- Cardiovascular disease
- High cholesterol
- Dietary intake
- Physical inactivity
- Cognitive inactivity
- Low social engagement
- Low education
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- Anstey, K. J., Bahar-Fuchs, A., Herath, P., Kim, S., Burns, R., Rebok, G., & Cherbuin, N. (2015). Body Brain Life: A randomized controlled trial of an online dementia risk reduction intervention in middle-aged adults at risk of Alzheimer's disease. Alzheimer's and Dementia: Translational Research and Clinical Interventions, 1, 72-80.
- Anstey, K. J., Cherbuin, N., Herath, P., Qui, C., Kuller, L. H., Lopez, O. L., . . . Fratiglioni, L. (2014). A self report risk index to predict occurence of dementia in three independent cohorts of older adults: The ANU-ADRI. PLoS One, 9(1), e86141.
- Anstey, K. J., Eramudugolla, R., & Dixon, R. A. (2014). Contributions of a Risk Assessment Approach to the Prevention of Alzheimer's Disease and Dementia. Journal of Alzheimer's disease, 42(4), S463-473. doi:10.3233/JAD-141248
- Ngandu, T., Lehtisalo, J., Solomon, A., Levalahti, E., Ahtiluoto, S., Antikainen, R., . . . Kivipelto, M. (2015). A 2 year multidomain intervention of diet, exercise, cognitive training, and vascular risk monitoring versus control to prevent cognitive decline in at-risk elderly people (FINGER): A randomised controlled trial. Lancet, 385(9984), 2255-2263. doi:10.1016/S0140-6736(15)60461-5
- Norton, S., Matthews, F. E., Barnes, D. E., Yaffe, K., & Brayne, C. (2014). Potential for primary prevention of Alzheimer's disease: an analysis of population-based data. Lancet Neurology, 13(8), 788-794. doi:10.1016/S1474-4422(14)70136-X