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The Effects of Retirement on Health and Health Behaviour among Retirees and their Partners: Evidence from the English Longitudinal Study of Ageing

Abstract

Retirement from paid work is a major transitional point and can have large impacts on lifestyle choices and subsequent health. Using eight waves of data from the English Longitudinal Study of Ageing (ELSA), this paper assesses impacts of both own and partner’s retirement on health and health behaviour by examining heterogeneous effects. We focus on individuals who retired from paid work and estimate fixed effects regression using state pension age (SPA) as an instrumental variable. Our results suggest that whilst own retirement improves health outcomes and increases the probability of engaging in more physical activity, the retirement of a partner does not influence the health or health behaviour of the other partner. The results from sub-sample regressions focusing on differences by sex, education, wealth, and occupation are consistent with these main findings, and find no significant impacts of partner retirement on own health or health behaviour in these sub-groups. Our results for the full sample and the sub-groups are mostly robust to changes in sample restriction and model specification, with only a small number of changes in absolute coefficient size. The results may suggest a role for targeted interventions, particularly amongst those with fewer years of education, lower wealth and some occupational groups.

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Fig. 1

Data Availability

The ELSA data that support the findings of this study are available from the UK data service.

Code Availability

Not applicable.

Notes

  1. Currently, we do not control for the order of retirement between the couple but it can be extended from this model.

  2. State Pension Age (SPA) for Men in our sample is 65 years old in all waves. SPA for women is 60 for wave 1 – 4, whereas in wave 5 - 8, women born on or after 6 April 1950 in our sample were affected by a gradual increase in the SPA between April 2010 and November 2018. However, due to too few women affected by the change in wave 5 and confidentiality regarding their exact of birth, ELSA only provides information on SPA of these women in wave 6 onwards.

  3. The reason why the proportions of female in wave 5-8 reported that they were retired are higher than female in wave 1-4 in every age group is due to the restriction imposed to construct the main sample, i.e. the reference person must retire at some point in order to be included in our sample. For persons who were in ELSA since wave 1-4, they could either retire in wave 1-4 or later in wave 5-8. But the refresh sample who entered ELSA after wave 4 had to retire during wave 5-8, otherwise they would not be included in our sample.

  4. Including total income of the couples in the controls implies that our model focus on the effects of own and partner’s retirement on health and health behaviours through channels other than changes in income due to retirement.

  5. We use non-housing financial wealth rather than total assets so as to avoid the issues of housing value and remaining mortgage debt.

  6. The survey asked respondents to identify the level of physical efforts needed in their occupation. We used the information from the wave prior to their retirement.

  7. Due to similarity in pattern of significance among all four measures for alcoholic drinking behaviour, only the number of drinks per week are presented - results for the remaining three measures are available upon request.

  8. Further, we explore if the effects of own retirement on health outcomes and behaviours are varied between the reference persons whose partner made a transition into retirement during the sample periods (accounting for two-third of our sample) and those with a partner who either worked or retired in all periods (the remaining one-third). The overall results for the retirees whose partner moved into retirement (See Appendix Table 10) are very similar to main results in Table 3, while the retirement of those whose partner made no transition only affects the chance to engage in more vigorous physical activity but not other outcomes or behaviours.

  9. The sample size and number of unique respondents in the low wealth group is slightly lower than the high wealth group. This could be a result of unbalanced panel data and how we generate the threshold. We compute median non-housing financial wealth among our sample in each wave. Then we assign a person to the low wealth group if his/her total couple non-housing financial wealth in the wave prior to retirement is less than such a median. Given that there are attritions to the survey and inclusions of refreshment sample, this strategy would not equally divide the sample for every wave into half.

  10. It is possible that such a finding is partly driven by the fact that more than 65% of those with physical or heavy manual work prior to their retirement are men where the p value of the own retirement effect is smaller than 0.1.

  11. Both of us use the same Instrumental Variable: State Pension Age in the UK.

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Acknowledgements

The authors would like to thank Matt Sutton, conference participants at HESG 2017, Nordic HESG 2017, Health Studies User Conference 2018 and seminar participants at University of Wollongong for their helpful comments and suggestions.

Core funding from the Chief Scientist Office of the Scottish Government Health and Social Care Directorates is gratefully acknowledged. The views expressed in this paper are those of the authors only and not those of the funding bodies.

Funding

The Health Economics Research Unit is funded by the Chief Scientist Office of the Scottish Government Health and Social Care Directorates. The views expressed in the paper reflect those of the authors and not necessarily those of the funders.

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All authors contributed to the study conception. Attakrit Leckcivilize performed data analysis, undertook data interpretation and wrote drafts of the manuscript. Paul McNamee undertook data interpretation, wrote drafts of the manuscript and edited the manuscript prior to publication. All authors read and approved the final manuscript.

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Correspondence to Attakrit Leckcivilize.

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Appendix

Appendix

Table 8 Full results for the main model based on FE-IV models
Table 9 Full results for the first-stage regressions of the main model based on FE-IV models with all sample
Table 10 Results for the FE-IV models between subgroups of retirees whose partner made a transition into retirement during the sample periods and those with a partner who either worked or retired in all periods
Table 11 Results for the FE-IV models among the reference persons (who made a transition from work to retirement) with 50 - 75 years of age in all study periods
Table 12 Results for the FE-IV models with own age squared and partner’s age
Table 13 Unbalanced panel selection
Fig. 2
figure 2

Proportion of the sample with Year of education fewer than 11 in all waves who classified themselves as retiring by gender and age

Fig. 3
figure 3

Proportion of the sample with Year of education 11 – 13 in all waves who classified themselves as retiring by gender and age

Fig. 4
figure 4

Proportion of the sample with Year of education 16 or more in all waves who classified themselves as retiring by gender and age

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Leckcivilize, A., McNamee, P. The Effects of Retirement on Health and Health Behaviour among Retirees and their Partners: Evidence from the English Longitudinal Study of Ageing. Population Ageing 15, 381–412 (2022). https://doi.org/10.1007/s12062-021-09337-3

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