Chronic Disease Epidemiology - Old Age Notes
Learning Objectives
Population lifespan – how has it changed the game?
Population growth and ageing population
Understand epidemiology and major causes of morbidity in later life
Age-related diseases and geriatric conditions
Multiple long term conditions (MLTCs) – multimorbidity
Dependency
Dementia
Need for care
Measuring a healthy life – what is it?
Measures of health
Trends in life expectancy and healthy life expectancy
Inequalities in life expectancy and healthy life expectancy
What might the future hold?
How can we forecast future prevalence and incidence of disease?
What might the future look like?
Definition of Epidemiology
"The study of the distribution and determinants of mortality and morbidity in populations and the application of that knowledge to the planning and evaluation of preventive and therapeutic services."
Population Lifespan
By the time agriculture was invented, the total number of people on earth was about 10 million, similar to the size of big cities today like Bangkok, London, or Rio de Janeiro.
By the year 0, the world population was approximately 250 million, comparable to Indonesia's population today.
It took about 7 million years for the human population to reach 1 billion.
By 1930, the population increased to 2 billion.
30 years later, it increased to 3 billion.
14 years later, 4 billion.
12 years later, 6 billion.
12 years later, 7 billion.
The world population is still growing, but the rate is slowing down.
The total number of children in the world has already stopped increasing.
The main reason for the future fast growth is the highly predictable fill-up of adults - i.e. increased life expectancy
Changes in Life Expectancy as a function of income
Chronic Disease Epidemiology
Commonly diseases of age.
Understand epidemiology and major causes of morbidity in later life
The Ageing Person
Ageing starts at day one and unfolds throughout life.
Many factors affect health trajectories as we age:
Genes
Nutrition
Lifestyle
Environment
Socioeconomic status
Attitude
Mental Health
Health literacy
These factors and their interactions are being studied by lots of epidemiological studies and across an age range.
Study Aims and Design
Aims:
To describe in biological, medical and psychosocial terms the health of 85+
Understand the factors are associated with health maintenance in 85+
Design:
Longitudinal prospective population study (recruited from general practice)
Individuals born in 1921 and aged 85 at baseline interview (2006/7)
Followed up at 18, 36, 60 and 120 months
Health Perception at Age 85
No one has perfect medical health at age 85.
Yet, 78% rated their health compared with others of the same age as “good” (34%), “very good” (32%) or “excellent” (12%).
Dependency and Daily Activities at Age 85
A quarter of men and a sixth of women have no important functional limitation at age 85
Functional limitations include difficulties with:
Cooking/Cleaning
Shopping
Using Telephone or Transportation
Managing Money and Medications
Bathing
Ambulation
Toileting
Transfers
Eating
Dressing
Prevalence Individual Diseases
Prevalence of (and numbers with) individual diseases and impairments in 2015 in the population aged 65 years and over Kingston et al Age & Ageing (2018)
Prevalence multi-morbidity
Prevalence of (and numbers with) multi-morbidity in 2015, 2025 and 2035 and percentage change in numbers between 2015 aArthritis, cancer, CHD, dementia, depression, diabetes, hypertension, respiratory disease, stroke Kingston et al Age & Ageing (2018)
Dependency with Dementia
Numbers of adults in England aged 65 years or older who have substantial (medium or high) dependency with and without dementia and other comorbidities, Numbers are in thousands Kingston et al Lancet Public Health (2019)
Measuring a Healthy Life
Measuring a healthy life through Life Expectancy and Healthy Life Expectancy
Why Health Expectancy?
LE used as a surrogate measure of population health in the past
Emphasis on reducing mortality sufficient when infectious diseases main concern
Now continued increases in life expectancy even at older ages
Quantity of remaining life no longer sufficient – need measure of quality ---
“Increased longevity without quality of life is an empty prize. Health expectancy is more important than life expectancy.” Dr Hiroshi Nakajima, Director-General WHO 1997
Health Expectancy
Life expectancy = expected number of remaining years of life at a particular age
Health expectancy = expected number of remaining years of life spent healthy
Health expectancy
partitions years of life at a particular age into years healthy and unhealthy
adds information on quality to life expectancy
is calculated using standard life table and prevalence of ill-health from survey (age and sex specific prevalence)
is used to:
monitor population health over time
compare countries (EU Healthy Life Years)
compare regions within countries
compare different social groups within a population (education, social class)
WHO Model of Health Transitions (1984)
The graph shows the proportion surviving (%) vs. Age with curves for Mortality, Morbidity and Disability.
Are the Extra Years Healthy Ones? - Theory
Increases in life expectancy due to keeping the old and frail alive for longer (Kramer 1980)
Onset and progression of chronic diseases are being delayed (Fries 1980, 2011)
Pessimists vs. Optimists
Dynamic Equilibrium: More disability but less severe (Manton, 1982)
Terminology of Health Expectancies
Healthy Life Expectancy
Healthy LE (self rated health HLE)
Disability Free LE (DFLE)
Limiting Longstanding Illnesses (HLY)
ADL / IADL (Active LE)
Dependency Free LE (DepFLE)
Dementia or cognitive impairment free LE (DFLE / CIFLE)
Frailty Free LE (FrFLE)
Many measures of health = many health expectancies!
MRC CFAS I
Sampling from whole population geographically. Three taken forward for new study
Cambridgeshire (Ely+surrounding area)
Newcastle
Nottingham
Equal numbers in 65-74 and 75+ year age groups
Complete population (including care homes)
Design
CFAS I: Two stage – screen then assessment
CFAS II: One interview (screen and assessment combined)
Numbers of individuals interviewed
7640 (80% response) in 1991-1994
7796 (56% response) in 2008-2011
Epidemiology of Alzheimer's Disease
Neurodegenerative disease
Most common form of dementia
Causes impaired cognitive functioning
No known cure
Because it is a progressive disease, with one of the earliest symptoms being memory loss, diagnosis is difficult.
Common Symptoms
Forgetting names and objects
Not recognising friends and family
Forgetting one's own phone number or address
Difficulty finding a familiar place
Noticeable language and intellectual decline
Forgetting to eat or maintain one's hygiene
Poor judgement, inability to follow simple instructions
Progressive sense of distrust
Unusual agitation or irritability
Dementia and Age Relationship
Graph showing the prevalence of Alzheimer's disease vs age.
The Prevalence data for different age groups is:
65-69: 0.097
70-74: 0.9
75-79: 1.7
80-84: 3
85-89: 6
90+: 11.1
Cognitive Impairment-Free LE
Increase in CIFLE > increase in LE and significant decline in CILE = compression of cognitive morbidity
WOMEN aged 65
LE
1991: 16.7
2011: 20.3
Difference (2011-1991): 3.6
Years free of cognitive impairment (CIFLE) (MMSE 26-30)
1991: 10.1 (9.8 to 10.4)
2011: 14.5 (14.1 to 14.8)
Difference (2011-1991): 4.4 (4.3 to 4.5)
%CIFLE/LE
1991: 60.5 (58.6 to 62.3)
2011: 71.2 (69.5 to 72.9)
Difference (2011-1991): 10.7 (8.2 to 13.2)
Years with cognitive impairment (CILE) (MMSE 0-25)
1991: 6.6 (6.4 to 6.8)
2011: 5.9 (5.5 to 6.2)
Difference (2011-1991): -0.7 (-1.3 to -0.2)
Years with mild cognitive impairment (mildCILE) (MMSE 18-25)
1991: 5.6 (5.2 to 6.0)
2011: 5.1 (4.5 to 5.6)
Difference (2011-1991): -0.5 (-0.8 to -0.3)
Years with mod/severe impairment (sevCILE) (MMSE 0-17)
1991: 1.0 (0.9 to 1.1)
2011: 0.8 (0.7 to 0.9)
Difference (2011-1991): -0.2 (-0.4 to -0.1)
Disability-Free LE
Increase in DFLE < increase in LE and significant increase in DLE
But most increase is years with mild disability = dynamic equilibrium
WOMEN aged 65
LE
1991: 16.7
2011: 20.3
Difference (2011-1991): 3.6
Years free of any disability (DFLE)
1991: 11.0 (10.8 to 11.2)
2011: 11.5 (11.3 to 11.8)
Difference (2011-1991): 0.5 (0.2 to 0.9)
%DFLE/LE
1991: 66.1 (64.9 to 67.4)
2011: 56.8 (55.5 to 58.2)
Difference (2011-1991): -9.3 (-11.1 to - 7.5)
Years with any disability (DLE)
1991: 5.7 (5.4 to 5.9)
2011: 8.8 (8.5 to 9.0)
Difference (2011-1991): 3.1 (2.8 to 3.5)
Years with mild disability (mildDLE)
1991: 2.7 (2.6 to 2.9)
2011: 5.2 (5.0 to 5.6)
Difference (2011-1991): 2.5 (2.2 to 2.8)
Years with moderate/severe disability (sevDLE)
1991: 2.9 (2.7 to 3.1)
2011: 3.5 (3.2 to 3.7)
Difference (2011-1991): 0.6 (0.3 to 0.9)
The North-South Divide Persists
Upper tier LA LE at birth, and DFLE at birth for 2006-8 and 2009-11
Men
Mean LE: 77.7 (2006-8), 78.7 (2009-11)
10-90% range LE: 4.4, 4.2
Mean DFLE: 62.8, 63.2
10-90% range DFLE: 8.8, 9.0
Women
Mean LE: 81.8, 82.7
10-90% range LE: 3.8, 3.5
Mean DFLE: 63.9, 63.8
10-90% range DFLE: 9.0, 9.0
DFLE inequalities exceed LE inequalities
LE inequalities are reducing, DFLE inequalities are not
Male DFLE at birth 2008-10
Many factors affect health trajectories as we age:
Genes
Nutrition
Lifestyle
Environment
Socioeconomic status
Attitude
Mental Health
Health Literacy
What Might the Future Hold?
Many countries produce population projections (e.g. births / deaths)
Few estimate the prevalence of ill-health, the numbers who may require long- term care or the amount of time people spend in different health states i.e. healthy life expectancy
The Population Ageing and Care Simulation model has been developed to address this need – it uses real data from individuals in English ageing cohort datasets
Artificially ages them in a stochastic framework
The Population Ageing and Care Simulation Model
Step 1: Harmonize and combine variables across studies (Understanding Society, ELSA, CFAS)
Sociodemographics (Age, sex, education, marital status, occupation)
Lifestyle Factors (Smoking, physical activity, BMI)
Mortality Data (ONS 2014 population projections)
Dependency (High, Medium, Low, Independent)
Diseases & Impairments (CVD, hypertension, diabetes, arthritis, stroke, respiratory disease, cancer, depression, visual, hearing and cognitive impairment, dementia)
Step 2: Data Preparation & Transition Probabilities
Calculate and store transition probabilities for each variable
Weight up to national population, clone (for unit weight), take 1% sample
Starting population of individuals (n=303,560)
Step 3: Microsimulation
Age people monthly from 2014 to 2040
Update status, if changed, calculate probability of each event
Draw random number to determine if event happens
Analyse trends & Inequalities in Diseases, Multimorbidity, Dependency, Dependency Free Life Expectancy
Intervention Modelling
Prevalence of Diseases and Impairments (2014)
63.4% Overweight & Obese
28.1% Hypertension
24.4% Arthritis
14.7% Respiratory Disease
7.9% Diabetes
7.8% Chronic Heart Disease
7.1% Depression
5.9% Hearing Impairment
5.8% Cancer
3.5% Visual Impairment
3.1% Stroke
Age-Specific Prevalence of Diabetes
Graph showing the age-specific prevalence of diabetes in men and women.
Dependency - Interval of Need (Isaacs and Neville, 1975)
High (requires 24-hour care):
Bedbound or chairbound, or unable to get to or use the toilet without help, or need help feeding, or be often incontinent and need help dressing, or have severe cognitive impairment (MMSE < 10)
Medium (requires help at regular times daily):
Need help preparing a meal, or dressing
Low (requires help less than daily):
Need help to wash all over or bath, or cut toenails, or shop, or do light or heavy housework
Independent
How Much Substantial Care Needs are with Dementia Alone?
Proportion of moderate and high dependency by dementia and other diseases.
Health Expectancy at 65: Men
Care less than daily
Daily care
24-hour care
COMPRESSION OF DEPENDENCY - GOOD NEWS!
Health Expectancy at 65: Women
Care less than daily
Daily care
24-hour care
EXPANSION OF DEPENDENCY - BAD NEWS!