The health of grandparents caring for their grandchildren: The role of early and mid-life

conditionsDi Gessa G, Glaser K and Tinker A

Institute of Gerontology, Department of Social Science, Health & Medicine, King’s College London, United Kingdom

ESRC ES/K003348/1

Symposium, Harnessing the power of secondary data analysis: insights from the “Ageing Cluster” of ESRC’s Secondary Data Analysis Initiative

British Society of Gerontology Annual ConferenceSouthampton, 1-3 September 2014

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Outline• Partnerships and timescale• Background• Aim and objectives• Data and methods• Results• Conclusion

The research study – partnerships and timescale

• Funded by ESRC, and in partnership with Calouste Gulbenkian Foundation, Grandparents Plus and the Beth Johnson Foundation

• Start April 2013 - October 2014• Project Launch 15 March 2013 at Europe

House, Westminster3

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Background /1• Grandparents play crucial role in family life• Evidence of the impact of childcare on

grandparents’ health is mixed: Custodial/primary grandchild carers experience

poorer health and wellbeing; Higher quality of life, fewer depressive symptoms

among grandparents providing grandchild care (vs no care).

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Background /2• Most studies are cross-sectional and samples

consist mostly of US grandparents;• Focus on primary and custodial care;• Few studies have studied the link between

grandchild care and grandparents’ health using a cumulative advantage/disadvantage framework.

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Aim and objectivesExamine the effects of caring for grandchildren on health among European grandparents using:i) Longitudinal dataii) Life history data, and controlling for

cumulative experiences across the life course (e.g. paid work histories; health and socio-economic position in childhood).

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Data/ 13 waves of multidisciplinary comparable surveys, representative of individuals 50+– Survey of Health, Ageing and Retirement in Europe

(SHARE) (N~27,000);France, Austria, Germany, Sweden, Denmark, Switzerland,The Netherlands, Italy, Spain, Greece, Belgium

– Household response rate: 62%, with individual response rates higher than 85%;

– First wave collected in 2004/05.

Focus on grandparents

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Data /2 Waves 1, 2 provide information on

grandparents, including demographic and socio-economic characteristics, health, and household characteristics.

Wave 3 collects retrospective life history information about childhood conditions, and life events in adulthood.

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Data /3«During the last 12 months,

have you looked after your grandchild[ren] without the presence of the parents?»

If so i) «how often?» [daily, weekly, monthly, less often]

ii) «about how many hours?»

Intensive grandparental childcare if grandchildren were looked after by grandparents on a daily basis or at least 15 hours per week

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Overview of Analysis

Latent Health w2Baseline Characteristics (w1)

Age; Gender; Education;Household type, Country;Wealth quintiles;Number & Age of grandchildren;Grandchild care;Paid work and social engagement;

Latent Health;Health behaviour (BMI, smoking);Depression; Cognitive function;

Latent Class Childhood

Disadvantage (w3)

Number of unions;In paid work 1-75%; Never worked;Has suffered: i. Hunger; ii. ‘Adverse’ event; iii. Long periods of ill health(w3)

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Measures Used Latent Class Analysis to classify

respondents by childhood conditions into advantaged/ disadvantaged subgroups;

[By age 10: Experienced parental difficulties; at least one parent died; Occupation of breadwinner; Books in HH; Toilet; Hot water; Bath; Heating; Poor/fair health; In hospital or bed for one month or more; With severe illness]

Used Latent Variable to represent ‘somatic’ health;

[Self-rated health, Self-report of conditions - cancer, lung, heart, stroke, diabetes, Self-report of limiting disability, Activities of Daily Living, Instrumental Activities of Daily Living]

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Sample and MethodsSample:• ~16,000 grandparents aged 50+ at baseline;• ~ 9,700 grandparents at 24-month follow-up;• ~ 7,200 with history data.• ~ 6,500 complete cases (~41%)

AnalysisLinear regression of latent health at follow-up, controlling for baseline and life history socio-economic and demographic characteristics.

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Results – descriptive /1

Grandparental childcare Wave 1 Wave 2

Not looking after 50.2 50.2

Not intensive 36.1 36.8

Intensive 13.7 13.0

Total 15,887 9,644

Distribution of grandparent childcare, by wave

Source: SHARE 2004/05, 2006Countries: France, Austria, Germany, Sweden, Denmark, Switzerland, The Netherlands, Italy, Spain, Greece, Belgium

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Results – descriptive /2Not looking

afterNot

intensive Intensive

SRH fair/poor 46.9 30.5 36.7ADL limitations 16.9 6.9 7.4Depressive symptoms 30.5 20.7 27.2

In couple >80% 71.0 78.9 83.2Never-worked (W) 27.9 14.4 29.1Suffered hunger 13.6 8.9 9.5

Advantaged & good health at 10 19.2 33.5 17.3Disadvantaged & good health at age 10 73.5 58.7 75.8

Distribution of selected grandparent characteristics, by childcare

Results – linear regression /1Beta coefficients from models of ‘good’ health at wave 2

• Younger grandparents, with higher educational levels, and in higher wealth quintiles at baseline more likely to report good health at wave 2;

• No gender differences;• No differences by household composition; age and

number of grandchildren not significant;• Social engagement at baseline not significant.• Positive effect of grandchild care (not intensive &

intensive on health).

Results – linear regression /2Latent health 0.558 < 0.001In lowest cognitive quintile – 0.049 0.005Depressive symptoms – 0.094 < 0.001Obese – 0.077 < 0.001Smoking – 0.009 0.543     

2 or more marital unions – 0.018 0.352In paid work for 1-75% of working life – 0.022 0.114 Has never worked – 0.046 0.019Has suffered long periods of ill health – 0.154 <0.001Has suffered hunger – 0.022 0.228Has suffered any ‘adverse’ event – 0.019 0.298     

Disadvantaged & good health at age 10 0.001 0.932Disadvantaged & poor health at age 10 – 0.039 0.054     

Not intensive 0.033 0.010Intensive 0.033 0.019

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ConclusionsUsing waves 1, 2 and life history data i) Grandchild care – both intensive and non-

intensive – positively associated with good health over time;

ii) Relationship remains even when taking into account childhood and adulthood disadvantage;

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Limitations & Future work• Separate models by gender to account for differences in life

histories• Attrition can bias results, especially in the older population

where the most ‘disadvantaged’ have a higher probability of dropping out of the study;

Multiple Imputations, Sensitivity analysis• “Selection effect” of grandparents who look after

grandchildren. Unmeasured factor?• ELSA and quality of life.

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Thanks for your attention!

Questions, comments and feedback are welcome.