Risk Factors and Preventative Strategies for Dementia Dr Blossom Stephan Senior Lecturer (in Risk Prediction) Newcastle University Institute for Ageing and Institute of Health and Society BGS Spring Meeting 27 th April 2017
Talk Structure Population ageing An update on the number of people with dementia Protective and harmful risk factors Education Diet Health Personalised Medicine Intervention and risk factor management Summary
Background Public Health Impact of Dementia What is dementia? A disease associated with cognitive and functional decline (and mood/behavior) usually of a chronic and progressive nature 46.8 million people have dementia worldwide (2015) and will increase to 131.5 million by 2050 Estimated 850,000 cases currently in the UK Approximately 80% of people with dementia have another long term illness Examples Diabetes, cardiovascular disease or delirium Cost is significant (US$818 billion) UK overall economic impact = 23.6 billion/year
Treatment & Prevention Alzheimer's disease drug candidates have one of the highest failure rates of any disease area (99.6%) No cure Current treatments only offer symptomatic relief In the absence of a cure, risk reduction and prevention are the only ways we can decrease the numbers of people getting dementia, postpone disease onset or mitigate the impact of disease
Findings in Support of Prevention What evidence is there to suggest that dementia can be prevented? New research from the UK (Germany, the Netherlands & USA) suggest that older people s risk of getting dementia is going down 1989 to 1994 (UK)* 8.3% (884,000) In the UK there were 214,000 fewer people with dementia (2008-2011) than population ageing alone would have predicted Supports the idea that cognitive impairment and risk of dementia are modifiable Reference *Cognitive Function and Ageing Study, Matthews et al (2013). The Lancet 2008 to 2011 (UK)* 6.5% (670,000)
Intervention Targets Protective & Risk Factors Dementia is a complex disease often resulting from the combination of factors including genetic, environmental and lifestyle factors Education Mental Activity Social Engagement Exercise Diet Genetics Smoking Obesity Diabetes Hypertension High Cholesterol Depression Head Injury Protective Risks
1. Education & Cognitive Reserve Decreased risk Higher education, IQ and occupational attainment Cognitive Reserve Hypothesis those with higher educational attainment appear to able to compensate for changes (e.g. disease-related loss) in the brain: Increase in the number of synapses and neurons OR The synapses may be more efficient or alternative circuitry is likely to be operating in those with higher education
2. Health Factors Cardio-metabolic conditions Poor cardio-metabolic health can lead to: Blood vessel changes Increased risk of stroke Increased risk of heart attack. all which are related to dementia Timing of Risk Factor Risk Factor Mid-life Later-life High Blood Pressure Unclear Obesity (BMI 30) Unclear Diabetes
3. Lifestyle Factors Diet Adherence to a healthy and balanced diet (e.g. Mediterranean) and low alcohol intake may protect against cognitive decline and dementia Physical Activity Higher levels of physical activity associated with reduced risk of cognitive decline and dementia Why? Better brain health link between heart and brain health Improvement in some of the biological factors associated with the development of dementia such as inflammation Reduced risk of disease (heart attack, diabetes, obesity)
Action on Dementia How are we going to prevent dementia? Improving risky behaviours could make a substantial reduction in dementia numbers 20% reduction (per decade) in all seven of the following risk factors Diabetes Mid life hypertension Mid life obesity Physical inactivity Smoking Depression Low Education could potentially reduce the number of dementia (Alzheimer s Disease) cases worldwide by 15% in 2050 Reference Norton et al (2014). Lancet Neurology
When to Intervene? Evolution in the Development of Alzheimer s disease (AD)
Personalised Risk Assessment Need for an accurate dementia risk prediction model Must be validated and able to be easily integrated into healthcare systems and research settings Move away from a one size fits all approach Personalised risk factor reduction Targets unique risk profiles
Three Dementia Risk Prediction Models CAIDE 1 LLDRI 2 DRS 3 N=1,409 (M age = 50) Follow-up = 20 years Country = Finland N=3,375 (M age = 76) Follow-up = 6 years Country = USA 1 Kivipelto et al., Lan Neurl, 2006; 2 Barnes et al., Neurology, 2009; 3 Walters et al., BMC Medicine, 2016 N=930,395 (Age 60) Follow-up = 5 years Country = UK
Three Dementia Risk Prediction Models CAIDE 1 LLDRI 2 DRS 3 N=1,409 (M age = 50) Follow-up = 20 years Country = Finland N=3,375 (M age = 76) Follow-up = 6 years Country = USA Age Age Age BMI BMI BMI 1 Kivipelto et al., Lan Neurl, 2006; 2 Barnes et al., Neurology, 2009; 3 Walters et al., BMC Medicine, 2016 N=930,395 (Age 60) Follow-up = 5 years Country = UK
Three Dementia Risk Prediction Models CAIDE 1 LLDRI 2 DRS 3 N=1,409 (M age = 50) Follow-up = 20 years Country = Finland N=3,375 (M age = 76) Follow-up = 6 years Country = USA Age Age Age BMI BMI BMI Sex Alcohol Sex Alcohol 1 Kivipelto et al., Lan Neurl, 2006; 2 Barnes et al., Neurology, 2009; 3 Walters et al., BMC Medicine, 2016 N=930,395 (Age 60) Follow-up = 5 years Country = UK
Three Dementia Risk Prediction Models CAIDE 1 LLDRI 2 DRS 3 N=1,409 (M age = 50) Follow-up = 20 years Country = Finland N=3,375 (M age = 76) Follow-up = 6 years Country = USA N=930,395 (Age 60) Follow-up = 5 years Country = UK Age Age Age BMI BMI BMI Sex Alcohol Sex Education Digit Symbol Substitution Test Alcohol Cholesterol Mini Mental State Exam Social Deprivation Physical Activity Carotid Artery thickening Smoking Systolic BP History of Bypass Surgery Diabetes Slow Physical Performance Anti-hypertensive Drugs Genetics (APOE) Stroke/TIA MRI White Matter Disease MRI Ventricular Enlargement 1 Kivipelto et al., Lan Neurl, 2006; 2 Barnes et al., Neurology, 2009; 3 Walters et al., BMC Medicine, 2016 Atrial Fibrillation Aspirin Depression
Three Dementia Risk Prediction Models CAIDE 1 LLDRI 2 DRS 3 N=1,409 (M age = 50) Follow-up = 20 years Country = Finland N=3,375 (M age = 76) Follow-up = 6 years Country = USA N=930,395 (Age 60) Follow-up = 5 years Country = UK Age Age Age BMI BMI BMI Sex Alcohol Sex Education Digit Symbol Substitution Test Alcohol Cholesterol Mini Mental State Exam Social Deprivation Physical Activity Carotid Artery thickening Smoking Systolic BP History of Bypass Surgery Diabetes Slow Physical Performance Anti-hypertensive Drugs Genetics (APOE) Stroke/TIA MRI White Matter Disease Atrial Fibrillation MRI Ventricular Enlargement Aspirin Depression AUC = 0.77 (0.71 to 0.83) AUC = 0.81 (0.79 to 0.83) C-stat = 0.84 (0.81 to 0.87) 1 Kivipelto et al., Lan Neurl, 2006; 2 Barnes et al., Neurology, 2009; 3 Walters et al., BMC Medicine, 2016
Next Steps Risk Stratification What is needed? Identification of new, more accurate markers of risk Neuroimaging: structural and functional Cerebrospinal Fluid (CSF) Markers: AB42 Validation of models across populations to stratify individuals by risk Best target group (stratified by age and gender) That is appropriate for routine measurement in a general practice environment That could be used in clinical trials and research settings
Summary Dementia is a serious public health problem Many dementia cases may be due to modifiable risk factors Public health interventions to high risk groups: 1. Increase educational levels 2. Reduce disease 3. Improve people s lifestyle choices could have a dramatic impact on the number of people who develop dementia
Thank you If you would like to get in touch here are my details: Dr Blossom Stephan Senior Lecturer Newcastle University Email blossom.stephan@ncl.ac.uk Phone 0191 208 3811