Introduction to the life-course
influences on health
Outline
• Introducing the lifecourse into social epidemiology
• Lifecourse epidemiological models
• How lifecourse thinking can inform policy
Lifecourse epidemiology
Fetus and
infant
Child
Adult
Aetiology
Mechanisms Intervention
T
HealthWelfare
Education
Stability
Employment
Physical
The lifespan
Ecological model of health across the lifecourse
Prenatal Pre-school School Training Employment Retirement
Family building
Accumulation of positive and
negative effects on health
and wellbeing
Life course stages
Life course epidemiology
• Causal pathways
– accumulation
– chain of risk
– trajectory
• Timing of causal actions
– critical and sensitive periods
Causal pathways
• Accumulation
– exposures (environmental, socioeconomic,
behavioural) gradually accumulate to damage health
as body systems age and are less able to repair
themselves
• Chain of risk
– a sequence of linked exposures that raise disease
risk because one bad experience or exposure tends
to lead to another and then another
• Trajectory
– long term view of one dimension of an individual’s life
over time
ACCUMULATION OF RISK
Power et al. AJPH, 1999
Cumulative social circumstances and health
at age 33
Mean vitamin C concentrations by number of adverse life
course indicators among British women aged 60–79 years.
Lawlor D A et al. Heart 2005;91:1086-1087
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
5
1 2 3
Lynch, Kaplan & Shema, NEJM 1997
No. times household income below 200% of USA federal poverty level
Sustained economic hardship and odds ratio of selfreported
cognitive difficulty (C) and depression (D)
in late midlife (controlling for age, sex and prevalent diseases)
C C CD D D
**
***
*
CHAIN OF RISK MODELS
Education
Adult
SEP
Chains of causes of the life course:
social position and cognition in later life
14
Childhood
SEP
Health &
Lifestyle
Life course
Cognitive
development
Cognition
HEALTH TRAJECTORY
MODELS
Mean predicted health scores by NS-SEC
3.50
3.75
4.00
4.25
4.50
20 30 40 50 60
Current age in years
PredictedSAHscore
Professional &
managerial
Intermediate
occupations
Small
employers &
own account
Lower
supervisory &
technical
Semi-routine &
routine
Sacker et al. JECH, 2005
Health decline by ethnic minority status
-1
0
1
25 30 35 40 45 50 55 60 65
Age
a) United States
-1
0
1
PredictedSRHZ-score
25 30 35 40 45 50 55 60 65
Age
b) Britain
-1
0
1
25 30 35 40 45 50 55 60 65
Age
c) Germany
-1
0
1
PredictedSRHZ-score
25 30 35 40 45 50 55 60 65
Age
d) Denmark
Majority Minority
Sacker A et al. (2011) JECH 65(2):130-6
Health decline by employment status
-1.5
-.5
.5
25 30 35 40 45 50 55 60 65
Age
a) United States
-1.5
-.5
.5
PredictedSRHZ-score
25 30 35 40 45 50 55 60 65
Age
b) Britain
-1.5
-.5
.5
25 30 35 40 45 50 55 60 65
Age
c) Germany
-1.5
-.5
.5
PredictedSRHZ-score
25 30 35 40 45 50 55 60 65
Age
d) Denmark
Employed Unemployed OLF
Sacker A et al. (2011) JECH 65(2):130-6
CRITICAL AND SENSITIVE
PERIOD MODELS
Timing of causal actions
• Critical period
– ‘‘biological programming’’ or ‘‘latency model” of
disease
– exposure has effects on body systems that cannot be
modified in any dramatic way, precipitating disease
later in life
• Sensitive period
– Time when the individual is particularly sensitive to
the environment
– Increases risk but less deterministic than a critical
period
– Probabilistic
Timing of exposure to rubella in pregnancy
and risk of congenital malformation
0
0.2
0.4
0.6
0.8
1
0-11 weeks 11-12 weeks 13-14 weeks 15-16 weeks >16 weeks
Barker hypothesis
• Proposed in 1990 by David Barker
• Intrauterine growth retardation, low birth weight,
and premature birth have a causal relationship to
the origins of hypertension, coronary heart
disease, and non-insulin-dependent diabetes, in
middle age.
• The hypothesis was derived from a historical
cohort study that revealed a significant association
between the occurrence of hypertension and
coronary heart disease in middle age and
premature birth or low birth weight.
• Evidence remains inconsistent
Critical periods (foetal programming)
Impaired
foetal
growth
Low
Birth
weight
Obesity
High
blood
pressure
CVD
In utero Birth Adolescence Midlife
BIRTH WEIGHT
SYSTEMATIC REVIEW: SHENKIN ET AL.
Psychol Bulletin 2004; 130: 989-1013
“Small, consistent, positive association between
birth weight and childhood cognitive ability, even
when corrected for confounders”
• Record et al. Ann Human Genet 1969; 33: 71-79
• Matte et al. BMJ 2001; 323: 310-314
• Richards et al. BMJ 2001; 322: 199-203
• Shenkin et al. Arch Dis Child 2001; 85: 189-196
• Jefferis et al. BMJ 2002; 325: 305-308.
• Corbett et al. 2004 unpublished
Verbal ability: months ahead or behind by no. of risk factors
-40
-30
-20
-10
0
10
20
0 1 2 3 4 5 6 7+
Numberofmonths
Number of risk factors
Age 3 Age 5 Age 7 Age 11
Early cognition and dementia risk
• 93 members of the School Sisters of Notre Dame
born before 1917 in the Milwaukee area
• Idea density and grammatical complexity, derived
from autobiographies written around age 22
years was a strong predictor of cognitive
function and Alzheimer’s disease risk in later life
(Snowdon et al. JAMA 1996)
• Childhood IQ was associated with late-onset
dementia (Whalley et al. Neurology 2000), but
with VaD rather than AD (McGurn et al. Neurology
2008)
A LIFECOURSE PERSPECTIVE
ON POLICY INTERVENTIONS
Functional capacity across the lifecourse
Chronic disease
risk
Plasticity
Life course
Infancy
Very early intervention
increases functional
capacity & responses
Inadequate response
to new challenges
Childhood
Adulthood
Late intervention
impactful for
vulnerable groups
Lifecourse strategy for disease
prevention
Adapted from Godfrey et al DOI: http://dx.doi.org/10.1016/j.tem.2009.12.008
Intervention in
childhood increases
resilience to new
challenges