Fertility histories and later life health Emily Grundy and Sanna Read

1. Fertility histories and later life health Emily Grundy and Sanna Read Website http://pathways.lshtm.ac.uk Email pathways@lshtm.ac.uk Twitter @pathwaysNCRM

2. 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)

3. 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

4. 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.

5. 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

6. 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.

7. 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

8. Fertility history and mortality ages ~45-69 comparing England & Wales, Norway & USA (controlling for age, marital & socio-economic status &, in USA, race/ethnicity). Analysis of ONS LS data ; Norwegian register data & US HRS, Grundy 2009. P<0.05; P<0.10

9. Associations between parity and mortality by cause group, Norwegian women aged 45-68 Controlling for age, year, education, marital status, region, log population size of municipality, Grundy & Kravdal 2010.

10. 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?”

11. BHPS analysis: Results for a) parous men & women and b) parous with 2+ children

12. 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) Source: Analysis of BHPS data in Read, Grundy & Wolf, Population Studies 2011

13. 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

14. Are children the key to a health and happy old age? Yes 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 • 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 BUT the context is very important – known variations and interactions by Gender, country, education etc AND we need to consider selection.

15. 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

16. 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

17. 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

18. Factors associated with allostatic load in previous studies Ethnicity: Non-whites (U.S.) Socioeconomics: education, income, occupational status, downward mobility, homelessness Spirituality: religious attendance, sense of meaning/purpose Family: attachment, violence, single parent, separation, care-giving, demands/criticism, spouse Allostatic load Individual: type A/hostility, locus of control, a polymorphism of ACE gene Work: control, demands, decisions, career instability, effort-reward imbalance Neigbourhoods: crowding, noise, lack of housing, rural/urban Social networks: emotional support, social position

19. 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)

20. Selected biomarkers to measure allostatic load in ELSA * only in wave 4

21. 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

22. Allostatic load change in ELSA Is 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)

23. Allostatic load change in ELSA Comparison between wave 2 (2004) and wave 4 (2008): • Low allostatic score (score 0-1) and high allostatic score (2+) 2004 2008 High High Low Low

24. Does allostatic load predict later disability?:Allostaticload measures in 2004 and ADL limitations in 2006 in men in ELSA ADL problem % Lowest 25% Highest25%

25. Allostatic load change in ELSA

26. Allostatic load change between 2004 and 2008 in ELSA

27. Allostatic load change in ELSA

28. Allostatic load change in ELSA

29. Allostatic load change in ELSA Results from fully adjusted model

30. Allostatic load change in ELSA Results from full adjusted model

31. Allostatic load change in ELSA Is 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

32. The model to be tested Is the association between fertility history and health mediated by allostatic load? Does SEP influence this association? Wealth Education Health Allostatic load Fertility history

33. All men 0.897 (0.070) Wealth 0.144 (0.015) -0.186 (0.023) -0.282 (0.070) -0.499 (0.088) -0.097 (0.022) Education Health Allostatic load 4+ children vs. 2 children Model adjusted for age. Unstandardized estimate and standard error shown.

34. Parous men 1.238 (0.400) Wealth -0.209 (0.032) 0.136 (0.022) -0.555 (0.130) 0.238 (0.400) -2.884 (0.765) -0.239 (0.087) -0.157 (0.016) Education Late birth 7.691 (2.310) Health Early birth Allostatic load Model adjusted for age, n of children and coresidence with child. Unstandardized estimate and standard error shown.

35. All women 0.779 (0.254) Wealth 0.136 (0.026) -3.637 (0.995) 0.784 (0.253) -0.095 (0.034) 0.290 (0.079) -0.239 (0.087) 1 child vs. 2 children Education -0.461 (0.075) Health 0 children vs. 2 children Allostatic load 4+ children vs. 2 children -0.124 (0.060) Model adjusted for age. Unstandardized estimate and standard error shown.

36. Parous women 0.631 (0.060) Wealth 0.103 (0.015) -0.168 (0.023) 0.174 (0.046) -0.064 (0.012) -0.735 (0.112) -0.225 (0.063) Education -0.248 (0.079) Health Allostatic load Early birth Model adjusted for age, n of children, late birth and coresidence with child. Unstandardized estimate and standard error shown.

37. Fertility history, allostatic load and health in ELSA 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.

38. 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

39. Stress/ support Childhood SEP • - Several time-ordered exposures • intermediate outcomes Smoking, Diet/BMI Early adulthood SEP Smoking Diet/BMI fertility Health in late adulthood