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Transcript of NCRM is funded by the Economic and Social Research Council Fertility histories and later life health...
NCRM is funded by the Economic and Social Research Council
Fertility histories and later life healthEmily Grundy and Sanna Read
Website http://pathways.lshtm.ac.uk
Email [email protected]
Twitter @pathwaysNCRM
NCRM is funded by the Economic and Social Research Council
Determinants of health in mid and later life
• Life course influences are recognized to be important, but most attention paid to socio-economic (and early life) factors
• Largely separate literature has shown differences by marital and household status and social support, more recent attention to partnership and parenting histories
• This literature has examined associations between the fertility histories of women (and less usually men) and mortality or health measured at one point in time
• Several, but not all, studies show worse health/higher mortality for nulliparous and high parity women (and men).
• Early parenthood is associated with poorer later health/mortality (women) and poorer later mental health (women and men)
• Late fertility associated better health/lower mortality in both women and men (but some studies the reverse)
NCRM is funded by the Economic and Social Research Council
Childrearing and health:Health promoting:• Incentives towards healthy
behaviours and risk avoidance • More social participation and
activity• Role enhancement• Social support - in childrearing
phases and in later life
Health challenging:• Physiological demands of
pregnancy, childbirth and lactation (although reduced risk breast & some other hormonally related cancers)
• Potential role conflict/role overload
• Stress (and depression)• Economic strain• Increased exposure infections• Disruption of careers/education –
especially for young parents
NCRM is funded by the Economic and Social Research Council
Associations between fertilityhistories and mortality in later life – Selection and reverse causation– Direct effects e.g. physiological consequences of pregnancy
and childbirth.– Indirect effects e.g. costs/benefits of child rearing mediated by
factors such as social support and health related behaviours.
NCRM is funded by the Economic and Social Research Council
Possible selection effects
• Poor health/health behaviours may restrict opportunities for marriage and reduce fertility (obesity, excessive alcohol and smoking all associated with fecundity of both women and men).
• Antecedent disadvantage associated both with early parenthood and with later poorer health
• Late fecundity and fertility may be marker of slower ageing/better health
NCRM is funded by the Economic and Social Research Council
Gender, age and SES variations/interactions
• Physiological effects of pregnancy/childbirth: mainly applicable women but some evidence of hormonal changes in new fathers
• Early childbearing may disrupt attainment adult career/educational roles
• Late childbearing may be stressful if perceived as ‘off time
• Ages at which mortality/morbidity observed may be important because of associations between cause and age of death
• Stress: negative effects likely to be greater for lone parents, those on low incomes and those with more stressful parenting histories (many children, children early in life).
• Social support: Women have closer links adult children, but some evidence that social support from children more important for health of older men – especially poorly educated
• Upward transfers greater to lower SES parents: support of children therefore potentially more important
• Life style/behavioural: effects noted for women and men – modified by residence with children.
NCRM is funded by the Economic and Social Research Council
Fertility history and later life health: previous research:
Data sources and outcomes investigated: • All cause mortality: Norwegian population registers; ONS
Longitudinal Study (E&W): USA Health and Retirement Survey linked to mortality
• Cause specific mortality: Norwegian population registers• Health, health trajectories, mental health: USA HRS;
UK British Household Panel Study; English Longitudinal Study of Ageing, 1946 birth cohort (NSHD).
• Quality of life, loneliness, social contacts, receipt of help from children: ELSA
NCRM is funded by the Economic and Social Research Council
Fertility history and mortality ages ~45-69 comparing England & Wales, Norway & USA (controlling for age, marital & socio-economic status &, in
USA, race/ethnicity).E&W deaths 19802000 at ages 50-69
Norway deaths 19802003 at ages 45-68
USA deaths 19942000 at ages 53-69
ALL Women/Men: OR OR OR
0 1.28 1.50 1.47
1 1.10 1.31 1.34
2 (ref) 1.00 1.00 1.00
3 1.01 0.95 1.21
4 1.11 0.95 1.41
5+ 1.25 0.94 1.66
PAROUS
Birth before 20 (F)/23 (M) 1.30 1.21 1.55
Birth after 39 0.94 0.86 0.74
Number of deaths 2,212 23,241 329
Analysis of ONS LS data ; Norwegian register data & US HRS, Grundy 2009. P<0.05; P<0.10
NCRM is funded by the Economic and Social Research Council
Associations between parity and mortality by cause group, Norwegian women aged 45-68
0 1 2 3 4+0
0.5
1
1.5
2
2.5
Lung caOther caCirc disResp disAlcoholAccs & ViOtherAll
Odd
s R
atio
Controlling for age, year, education, marital status, region, log population size of municipality, Grundy & Kravdal 2010.
NCRM is funded by the Economic and Social Research Council
BHPS analysis: Measures
• Fertility history: Number of natural children (0, 1, 2, 3, 4+); for parous: young age at first birth (<20/23); any birth at age >35/39; for parents with 2+ births: any birth interval < 18 months.
• Co-variates: Education; marital status; housing tenure; smoking; emotional support; co-residence with children (parents only)- all time varying except emotional support.
• Variables hypothesised to be associated with sample retention- interviewers’ reports of problems with interview; recent mover; foreign born.
Outcomes: • Self rated health: Excellent,
Good, Fair, Poor, Very poor. Ordinal variable, higher=worse.
• Health limitation: “Does your health in any way limit your activities compared to most people of your age?”
NCRM is funded by the Economic and Social Research Council
BHPS analysis: Results for a) parous men & women and b) parous with 2+ childrenHealth limitations Self-rated health
Men Women Men Womena) Parous respondents:
Number of children:1 +34+ +++ +++ +++ +++Birth before 23/20 +++ +++ +++ ++Birth after 39/35
b) Parity 2+; spacing effects
Number of children:3 +4+ +++ +++ +++Birth before 23/20 ++ +++ +++ +++Birth after 39/35
Birth interval < 18 months ++ +++ +++ +++
NCRM is funded by the Economic and Social Research Council
Rate-of-change in health over 11 years: Predicted probability of health limitation by fertility history characteristics, British women born 1923-49
(reference group = women with 2 children born when mother 20-34)
42 44 46 48 50 52 54 56 58 60 62 64 66 68 70 72 740.00
0.10
0.20
0.30
0.40
0.50
0.60
0.70
Pr(HLIM=1 for reference group)
Pr(HLIM=1|early first birth)
Pr(HLIM=1|short birth interval)
Pro
bab
ilit
y
Source: Analysis of BHPS data in Read, Grundy & Wolf, Population Studies 2011
NCRM is funded by the Economic and Social Research Council
BHPS analysis: key findings• High parity (4+ children) associated with
health limitation and worse self-rated health among women and men
• Also a slightly higher risk of health limitation for childless women
• Early parenthood for parous) and short birth intervals (among those with 2+ children) associated with higher risk of health limitation, worse self rated health and faster accumulation of health limitation
NCRM is funded by the Economic and Social Research Council
Are children the key to a health and happy old age?
Yes• More children increases
chance of social contacts ; for parents especially having a daughter
• More children associated with more help from children
• Parents (of smallish families) seem to have lower mortality and better health than the childless
No• High parity associated
higher mortality and worse health
• ‘Intensive’ family formation patterns – early parenthood and short birth intervals- associated with worse health and faster decline in health
BUT the context is very important – known variations and interactions by Gender, country, education etc AND we need to consider selection.
NCRM is funded by the Economic and Social Research Council
Limitations of previous work• Outcome measures –
mortality and ADL limitation- may be too far ‘upstream’ – need indicators of sub clinical morbidity observable earlier in life course
• Failure to identify PATHWAYs through which fertility histories influence later life health
• Limited consideration of early life influences on both fertility histories and later health
Addressing these limitations• Measures of allostatic load in
mid and later life
• SEM and path analysis to
identify pathways
• Modelling including early life indicators
15
NCRM is funded by the Economic and Social Research Council
Progress to date:• Identifying earlier health outcomes: derivation
of a measure of allostatic load using data from the English Longitudinal Study of Ageing (ELSA)
• Identifying pathways from fertility histories to later life health (via allostatic load).
• In progress; taking account of early life influences
16
Allostatic load• a multisystem dysregulation state resulting from
accumulated physiological ‘wear and tear’ • Allostasis = a process whereby organism maintains
physiological stability by adapting itself to environmental demands
- > health is a state of responsiveness and optimal predictive fluctuation to adapt to the demands of the environment -> dynamic biological process interacting with context
Factors associated with allostatic load in previous studies
Socioeconomics: education, income, occupational status, downward mobility, homelessness
Family: attachment, violence, single parent, separation, care-giving, demands/criticism, spouse
Individual: type A/hostility, locus of control, a polymorphism of ACE gene
Neigbourhoods: crowding, noise, lack of housing, rural/urban
Allostatic load
Ethnicity: Non-whites (U.S.)
Spirituality: religious attendance, sense of meaning/purpose
Social networks: emotional support, social position
Work: control, demands, decisions, career instability, effort-reward imbalance
Sample• English Longitudinal Study of Ageing (ELSA) waves 1 -
4 (2002-2008)• men and women (n = 5279) aged 50+ in 2002• Measures:
– Biomarkers available in waves 2 and 4– Health: self reported health, limitation in health, ADL and
IADL limitation– Fertility history: number of children, birth before age 20
(women) or age 23 (men), birth after age 34 (women) and 39 (men), coresidence with child
– Background factors: age, marital status, qualification, tenure status, net wealth quintile (non-pension wealth indicating financial, physical and housing wealth net of debts)
Selected biomarkers to measure allostatic load in ELSA
Neuro-endocrine
Immune Cardiovascular Respiratory Metabolic Body fat
DHEAS* (dehydroepiandrostorone sulphate)
C-reactive protein
Systolic blood pressure
Peak expiratory flow
Total blood cholesterol/HDL cholesterol ratio
Waist-hip ratio
Fibrinogen Diastolic blood pressure
Triglycerides
IGF-1* (insulin-like growth hormone)
Glycated HgB
* only in wave 4
Allostatic load scores in ELSA• Group allostatic load index: number of biomakers
indicating high risk (25th percentile) calculated separately for men and women, range 0 - 9
Upper 25th percentile Lower 25th percentile
Systolic blood pressure Diastolic blood pressure
Fibrinogen Peak expiratory flow
Triglycerides
C-reactive protein
Glycated HgB
Waist-hip ratio
Total/HDL cholesterol ratio
Allostatic load change in ELSAIs change associated with any of the following factors? • Age• Qualification, tenure status, net wealth quintile• Being married• Perceived support and critique received from family
and friends• Number of children• Coresidence with child, early child birth, late child
birth (among parents only)
Allostatic load change in ELSAComparison between wave 2 (2004) and wave 4
(2008):• Low allostatic score (score 0-1) and high allostatic
score (2+)
High High
Low Low
2004 2008
Does allostatic load predict later disability?:Allostatic load measures in 2004 and ADL limitations in 2006 in men in ELSA
Systo
lic BP
Diasto
lic BP
Fibrin
ogen
C-reac
tive pro
tein
Triglys
erides
Glycate
d HgB
Wais
t-hip ra
tio
HDL choleste
role ra
tio
Peak exp
irato
ry flow
0
5
10
15
20
25
1234
ADL
prob
lem
%
Lowest 25%
Highest25%
Allostatic load change in ELSA
Men Women0
10
20
30
40
Low -> LowLow -> HighHigh -> LowHigh -> High
AD
L lim
itatio
n %
Allostatic load change between 2004 and 2008 in ELSA
Women Men0%
20%
40%
60%
80%
100%
High -> HighHigh -> LowLow -> HighLow -> Low
Allostatic load change in ELSA
Women Men56.00
60.00
64.00
68.00
72.00
Low -> lowLow -> HighHigh -> LowHigh -> HighA
ge in
yea
rs
Allostatic load change in ELSA
Men Women0
10
20
30
40
50
Low -> LowLow -> HighHigh -> LowHigh -> High
No
qual
ifica
tion
%
Allostatic load change in ELSA
Men Women0
10
20
Low -> LowLow -> HighHigh -> LowHigh -> HighCh
ildle
ss %
Results from fully adjusted model
Allostatic load change in ELSA
Men Women0
10
20
Low -> LowLow -> HighHigh -> LowHigh -> High
4+ c
hild
ren
%
Results from full adjusted model
Allostatic load change in ELSAIs change associated with any of the following factors? • Age -> Yes• Qualification, tenure status, net wealth quintile ->
Yes• Being married -> No• Perceived support and critique received from family
and friends -> Yes• n of children -> Yes• coresidence with child, early child birth, late child
birth (among parents only) -> No
Fertility history Allostatic load
Health
Education
Is the association between fertility history and health mediated by allostatic load?Does SEP influence this association?
The model to be tested
Wealth
4+ children vs. 2 children
Allostatic loadHealth
Education
All men
Wealth
Model adjusted for age. Unstandardized estimate and standard error shown.
-0.282 (0.070)
0.897 (0.070)
-0.499 (0.088)
-0.186 (0.023)
0.144 (0.015)
-0.097 (0.022)
Early birth Allostatic loadHealth
Education
Parous men
Wealth
Late birth
Model adjusted for age, n of children and coresidence with child. Unstandardized estimate and standard error shown.
1.238 (0.400)
-0.555 (0.130)
-0.239 (0.087)
-2.884 (0.765)
-0.209 (0.032)
0.238 (0.400)
-0.157 (0.016)
0.136 (0.022)
7.691 (2.310)
0 children vs. 2 children Allostatic load
Health
Education
All women
Wealth
4+ children vs. 2 children
Model adjusted for age. Unstandardized estimate and standard error shown.
0.779 (0.254)
1 child vs. 2 children
-3.637 (0.995)
-0.124 (0.060)
0.136 (0.026)
0.784 (0.253)
0.290 (0.079)
-0.461 (0.075)
-0.239 (0.087)
-0.095 (0.034)
Early birth Allostatic loadHealth
Education
Parous women
Wealth
Model adjusted for age, n of children, late birth and coresidence with child. Unstandardized estimate and standard error shown.
0.631 (0.060)
0.103 (0.015)-0.168
(0.023)0.174 (0.046)-0.225
(0.063)
-0.248 (0.079)
-0.064 (0.012)
-0.735 (0.112)
Is the association between fertility history and health mediated by allostatic load? - Yes, it is in men and to some extent also in women. In women there are also direct paths to health suggesting that there are other potential mediators.
Does SEP influence this association?- In men, and to some extent in women, SEP mediates the association between fertility history and later allostatic load and health.
Fertility history, allostatic load and health in ELSA
Work in progress
• Refinement of measures of allostatic load including medication use
• Further modelling of Pathways including life style variables
• Investigation of Pathways including early life influences
• Analyses taking account of missing data
NCRM is funded by the Economic and Social Research Council
- Several time-ordered exposuresintermediate outcomes
Early adulthood
SEP
Health in late
adulthood
fertility
Childhood SEPStress/support
Smoking,Diet/BMI Smoking
Diet/BMI