My PhD research estimating Healthy Working Life Expectancy in England

Marty Parker, Health and Wellbeing, Keele University, 2017 Cohort

Over the last few years I’ve been using advanced quantitative methods to research health and paid work participation in older age groups. Countries all over the world are experiencing population ageing and increasing life expectancy. There are more and more older adults compared to those of working-age, and people are being expected to work until they are older.

Here in the UK, the State Pension age (SPa) is the age of eligibility to claim a regular pension payment from the government (if you have paid National Insurance contributions for enough years). SPa used to be lower for women than men but was recently equalised at age 65 regardless of gender. By the end of this year, people won’t be able to claim their State Pension until they turn 66, and this age of eligibility will keep gradually increasing. The idea behind these increases is that people are receiving their pensions for longer than ever before (because of living until older ages) and, for each retiree, there are fewer employed people paying taxes and funding the system. There’s also an expectation that, under the right circumstances, extended working lives shouldn’t be harmful but instead promote wellbeing (for example through societal engagement). But while the State Pension age is linked to life expectancy, it’s not clear whether people are healthy enough to work for longer. Increasing the retirement age as an isolated policy change may not make a big difference to the number of people working past age 65 if there are high levels of poor health. For these policies to be successful, there need to be as many people as possible who are both healthy and in employment.

I wanted to know whether populations are ready for extended working lives, so I carried out a systematic review to identify existing estimates of the number of years that people are healthy and in work from age 50. There were no up-to-date estimates, but the search did identify an indicator called Healthy Working Life Expectancy (HWLE), which seemed like a suitable metric for population monitoring and to support evidence-based policy making: HWLE is defined as the average number of years that people are expected to be both healthy and in work from age 50. If you want to know more about the review, it has been published by Social Indicators Research journal and is freely available online1.

The systematic review led to the first quantitative study of my PhD, which was to estimate HWLE in England as well as for population subgroups: separately for men and women; for people with different levels of educations; for people living in different regions within England; for people working in (or who previously worked in) manual, non-manual or self-employed occupations; and for people living in areas of higher or lower deprivation. I used data from six waves (longitudinal time points) of the English Longitudinal Study of Ageing, which I merged, cleaned, and reformatted for analysis using a method called multi-state interpolated Markov chain modelling. To estimate HWLE, I categorised each person, at each interview time point, into one of four health and work-related states: healthy and working; healthy and not working; not healthy but in work; or not healthy and not in work. I did all the data preparation in statistical software Stata. Although I had previously coded in other programming languages (including R for statistics), Stata was new to me and the logic behind the commands that you type was quite different. The Stata course that I was able to attend was a huge help and a big time-saver! Unfortunately, there are generally no courses for the other piece of software that I needed to use for the main analyses (specifically designed for health expectancy research and without any frills such as a graphical user interface) so I had to figure that one out myself.

The health expectancy software that I used to carry out the multi-state interpolated Markov chain modelling (that is, to estimate HWLE) uses a maximum likelihood estimation procedure to model the probabilities associated with people’s movements between the health and work states. Although I was analysing a large sample size of over 15 thousand people, sometimes there were convergence problems; the software ‘couldn’t find’ the right values for the models. Sometimes there were additional analyses that could help inform ‘where to look’, but – even with thousands of study participants – certain transitions were observed very infrequently. For example, not many unhealthy and not-working people reported being both healthy and working at their next survey. (This challenge limits the complexity and depth of analyses that can be feasibly carried out using existing data sources.)

Ageing trajectories are diverse but the results of this study showed that, on average, people in England are not healthy and in work until the current State Pension age. These findings are a starting point for evaluating the potential for success of policies to extend working lives of older workers in England, and I am in the process of publishing this study so the numerical results should be available online in due course (hopefully!).

I will be submitting my thesis this year (which also contains two further quantitative studies relating to HWLE not described in this blog). As I consider post-PhD career options, I am aware of how much more research is needed on HWLE, population health expectancy inequalities, and methodological development to overcome the constraints of existing data sources. I have had meetings with the Department for Work and Pensions throughout this ESRC Case Studentship to discuss my work and share findings; this has been invaluable to enhance the application of this research in policy. Getting a glimpse into the world of policymaking has also been very helpful to me as I think through ideas for postdoctoral research to address important questions in a way that is practicably useful for potential users of the work.

1Parker, M., Bucknall, M., Jagger, C. et al. Extending Working Lives: A Systematic Review of Healthy Working Life Expectancy at Age 50. Soc Indic Res (2020).

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