Laurie Brown, University of Canberra: How strong are the links between lifestyle and dementia? Bridging the physical and mental health divide

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Information about Laurie Brown, University of Canberra: How strong are the links between...
Health & Medicine

Published on February 20, 2014

Author: informaoz

Source: slideshare.net

Description

Laurie Brown, Research Director, NATSEM, University of Canberra delivered this presentation at the 2014 National Dementia Congress. The event examined dementia case studies and the latest innovations from across the whole dementia pathway, from diagnosis to end of life, focusing on the theme of "Making Dementia Care Transformation Happen Today. For more information on the annual event, please visit the conference website: http://www.healthcareconferences.com.au/dementiacongress2014

THE LINKS BETWEEN LIFESTYLE AND DEMENTIA Professor Laurie Brown National Dementia Congress, 20 February 2014, Melbourne

AIM-OUTLINE • Provide an overview of key risk factors and understanding the difficulties in measuring and interpreting risk • Look at impact of smoking, physical activity and BMI on risk of dementia • Look at impact of trends in midlife BMI on dementia in latelife • Consider the association of dementia with diabetes

Background • Number of Australians with dementia is expected to more than double by 2030 as is the cost of providing care. • Population ageing is often considered the most important factor determining the occurrence of dementia in the future • Projections of dementia cases are therefore often based solely on the projected age composition of the population. ● from under 200,000 persons in the year 2000, to over 300,000 by the early 2020s, and rising to approximately 500,000 in the 2030s 3

Background cont. • Emerging evidence for the role of modifiable risk factors in dementia - reduce the disease burden by reducing risk, delaying onset and/or by early intervention to modify disease progression. • As more intervention options become available, policy makers will need decision-support tools that allow them to evaluate and compare the likely health and economic outcomes of these strategies to identify the most cost effective approaches at a population level.  Development of a computer model that simulates the health and economic impacts of dementia prevention strategies. 4

Background – The Evidence Base • DCRC – Early Diagnosis & Prevention • DYNOPTA • Alzheimer’s Australia • Literature – epidemiological studies

Background – Risk (and Protective) Factors Protective Factors Risk Factors Cognitively stimulating activities (across Age the lifespan) Regular physical activity Genetic factors e.g. Apolipoprotein E status, Down syndrome Higher engagement in leisure/social activities Family history Higher education Light-moderate alcohol intake Under & overweight, obesity Cardiovascular risk factors e.g. smoking, hypertension, elevated cholesterol, high intake of saturated fat Diet e.g. Fish intake Diabetes, stroke, heart disease Traumatic brain injury Depressive symptoms

Example - Dementia & Physical Activity • Barnes et al (2013) estimated that 13% of AD cases are potentially attributable to physical inactivity • High levels of physical activity were associated with a 38% lower risk of cognitive decline in older people and low to moderate levels of physical activity with 35% lower risk of cognitive decline, compared to those who were sedentary (Sofi et al, 2011) • A 28% reduced risk of any dementia and 45% reduced risk of AD for those in the highest physical activity category compared to the lowest (Hamer & Chida, 2009) • Exercising at least twice a week at midlife was associated with a 52% reduced risk of dementia at age 65-79 years (Rovio et al, 2005)

Background – Understanding Risk (and Protective) Factors • • • • Changing list Modifiable Beneficial at a population level – not necessarily so for each individual All types of dementia (Alzheimer’s disease ~ 60%, vascular dementia ~ 20%) • Reduce the risk of dementia and/or delay onset • Selection effects e.g. alcohol drinkers • Non-linear effects e.g. U-shaped relationship for alcohol or BMI • Mid vs late life e.g. obesity, chol • Interactions e.g. lifestyle with APOE, joint distributions

MECHANISMS • Build brain reserve (allowing normal cognitive function to continue for longer) • Reduce protein accumulations • Effects on brain health – reducing inflammation, increasing brain blood flow, growth of new neurons and synapses • Benefits for other health factors related to cognitive functioning – vascular conditions, diabetes and depression.

NATSEM (DCRC-EDP) Dementia Prevention Model • To develop a cell-based cohort (dynamic-longitudinal) model to project the impact of modifying risk factors on dementia at a population level • Process ● Collect data (often cross-sectional available) ● Create synthetic (5yr age-sex) cohorts & generate projections ● Get risk estimates for dementia ● Model trends in risk factors ● Project future risk factor profile in age-sex cohorts ● Estimate proportions of older people having a history of midlife or latelife risk factor (X) ● Model dementia numbers by risk factor categories

PREVALENCE OF DEMENTIA

Ageing of Australia's Population (next 45 years) Australia 2006 Male Australia 2051 Female Male 100+ 90 90 80 80 70 70 60 60 50 50 40 40 30 30 20 20 10 10 0 Female 100+ 0 200000 100000 0 100000 200000 200000 100000 0 100000 200000 12

Age-specific Prevalence Rates of Selected Risk Factors 90% Ever smoked 80% BMI>=30 70% Sedentary 60% 50% 40% 30% 20% 10% Male 85+ 80-84 75-79 70-74 65-69 60-64 55-59 50-54 45-49 85+ 80-84 75-79 70-74 65-69 60-64 55-59 50-54 45-49 0% Female 13

Relative Risk of Dementia • Ever smoked vs never smoked 1.140 • Obese vs non-obese 2.296 • Sedentary vs active ` 1.693 14

Number of persons with dementia Projected Numbers of People Living With Dementia Considering Ageing Only 700,000 600,000 Male Female 500,000 400,000 300,000 200,000 100,000 2006 2011 2016 2021 2026 2031 2036 2041 2046 2051 15

2051 2046 2041 2036 2031 2026 2021 2016 2011 2006 Impact of Reducing Smoking Per cent differnce compared to 'ageing only' scenario 0.0% Ageing only -1.0% -2.0% -3.0% Smoking drops 2.5% every 5 years Smoking drops 5% every 5 years Smoking drops 10% every 5 years -4.0% 16

2051 2046 2041 2036 2031 2026 2021 2016 2011 2006 Impact of Obesity Per cent differnce compared to 'ageing only' scenario 3% 2% Ageing only 1% 0% -1% -2% -3% -4% -5% Obesity rises 2.5% every 5 years Obesity drops 5% every 5 years Obesity drops 10% every 5 years -6% -7% 17

2051 2046 2041 2036 2031 2026 2021 2016 2011 2006 Impact of Promoting Physical Activity 10.0% Per cent differnce compared to 'ageing only' scenario Ageing only 5.0% 0.0% -5.0% Physical inactivity rises 2.5% every 5 years Physical inactivity drops 5% every 5 years -10.0% -15.0% Physical inactivity drops 10% every 5 years -20.0% 18

Impact of Midlife Obesity on Dementia Prevalence • Risk of dementia 1.64x for midlife obesity and 1.26x for midlife overweight versus midlife normal weight (Low BMI in midlife compared with normal BMI - 1.96 risk of developing AD) (Anstey et al 2011) • Use dynamic modelling to project future proportions and numbers of older people with a history of a given BMI status at their midlife • Model impact of midlife BMI on dementia in older population ● Compare ageing only and BMI factored ‘what-if’ projections 19

Prevalence of Dementia by BMI Status prev_normal prev_obese 70-74 80-84 prev_overwt prev_underwt prev_total 80% 70% 60% 50% 40% 30% 20% 10% 0% 65-69 75-79 Male 85-89 90+ 65-69 70-74 75-79 80-84 85-89 90+ Female 20

Estimated Historical and Predicted Prevalence of BMIs at 50 years of age Male ● Female ‘Obs’ = estimated historical data. 21

Percentage of Older Persons who were Obese at Midlife Male Male Female Female

Projected Prevalence of Dementia with and without factoring midlife BMI profile In 2050, there will be 14% more people aged 65 years and over living with dementia than that estimated on the basis of demographic ageing only.

Impact of Changing Prevalence of Midlife Obesity

Dementia and Diabetes • Persons with Type 2 diabetes exhibited significantly increased risk of all dementia RR = 1.66, and risk of AD was also elevated for men, RR = 2.27 and for women, RR = 1.37 (population based cohort study in Rochester, Minnesota)(Leibson, 1997) • A meta-analysis found diabetes was associated with a 47% increased risk of any dementia, a 39% increased risk of AD, and a 138% increased risk of VaD (Lu, 2009) • 2% of cases of AD could be attributed to diabetes (Barnes & Yaffe, 2011) • Prevention of diabetes could reduce the incidence of mild cognitive impairment and dementia by 5% (Ritchie et al, 2010)

Decomposition of the Projected Diabetic Population – Ageing vs Lifestyle Factors Millions Millions 6.0 6.0 6.0 Number of Pre-Diabetics Number of Pre-Diabetics Lifestyle Factors Ageing Population Ageing Population Base Case Base Case Base Case Prevalence of Pre-Diabetics Prevalence of Pre-Diabetics Prevalence Prevalence 25.0% 25.0% 5.0 5.0 5.0 Lifestyle Factors Ageing Population Ageing Population Base Case Base Case Base Case 20.0% 20.0% 4.0 4.0 4.0 15.0% 15.0% 3.0 3.0 3.0 10.0% 10.0% 2.0 2.0 2.0 5.0% 5.0% 1.0 1.0 1.0 0.0 0.0 0.0 2007 2007 2007 2052 2052 2052 2052 2052 2052 0.0% 0.0% 2007 2007 3.0 3.0 3.0 2052 2052 Prevalence of Diabetics Prevalence of Diabetics Number of Diabetics Number of Diabetics Millions Millions 2052 2052 Prevalence Prevalence Lifestyle Factors Ageing Population Ageing Population Base Case Base Case Base Case 20.0% 20.0% Lifestyle Factors Ageing Population Ageing Population Base Case BaseBase Case Case 2.5 2.5 2.5 15.0% 15.0% 2.0 2.0 2.0 10.0% 10.0% 1.5 1.5 1.5 1.0 1.0 1.0 5.0% 5.0% 0.5 0.5 0.5 0.0% 0.0% 0.0 0.0 0.0 2007 2007 2007 2052 2052 2052 2052 2052 2052 2007 2007 2052 2052 2052 2052

The Comparative Contributors to the Projected Diabetic Population 2007 Pre-Diabetes Base Ageing Population Lifestyle Factors Total Diabetes Base Ageing Population Lifestyle Factors Total 2052 % of Increase 63.61% 36.39% 2,573.307 2,573.307 1,592.681 911.215 5,077.203 60.34% 39.66% 1,186.434 1,186.434 1,061.649 697.767 2,945.851

Conclusions • Despite the significant health and cost burden associated with dementia, there is a major gap in our knowledge about future impacts and the role prevention strategies might play in reducing these. • Need to better understand the role and impact of modifiable risk factors • Dementia (and Diabetes) simulation models provide an new and different evidence base for informing health policy. 28

References • K. J. Anstey, N. Cherbuin, M. Budge and J. Young (2011) Body mass index in midlife and late-life as a risk factor for dementia: a meta-analysis of prospective studies. obesity reviews (2011) 12, e426–e437, doi: 10.1111/j.1467-789X.2010.00825.x • Barnes DE, Yaffe K. (2011) The projected effect of risk factor reduction on Alzheimer’s disease prevalence. Lancet Neurol, 10(9):819-828. • Hamer M, Chida Y. (2009) Physical activity and risk of neurodegenerative disease: a systematic review of prospective studies. Psychol Med, 39:3-11. • C. L Leibson, W. A. Rocca, V. A. Hanson, R. Cha, E. Kokmen, P. C. O'Brien, and P. J. Palumbo (1997) Risk of Dementia among Persons with Diabetes Mellitus: A Population-based Cohort Study American Journal of Epidemiology, Vol. 145, No. 4 • Lu F-P, et al. Diabetes and the risk of multi-system aging phenotypes: a systematic review and meta-analysis. PLoS One, 2009, 4(1): e4144. doi:10.1371/journal.pone.0004144. • Ritchie K, et al. Designing prevention programmes to reduce incidence of dementia: prospective cohort study of modifiable risk factors. BMJ, 2010, 341:c3885. doi:10.1136/bmj.c3885 • Rovio S, et al. (2005) Leisure-time physical activity at midlife and the risk of dementia and Alzheimer’s disease. Lancet Neurol, 4:705-711. • Sofi F, et al. (2011) Physical activity and risk of cognitive decline: a meta-analysis of prospective studies. J Intern Med, 269:107-117. • Farrow, M & O’Connor, E (2012). Targeting Brain, Body and Heart For Cognitive Health and Dementia Prevention-Current Evidence and Future Directions, Paper 29, Alzheimer’s Australia.

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