Healthy and unhealthy working-life expectancy: opportunities and challenges
Authors: Christian Dudel
Journal: The Lancet Healthy Longevity (2021)

In many high-income countries, populations are ageing rapidly. In the coming years, the proportion of individuals of retirement age will increase, while the size of the workforce will decrease. This raises concerns about the sustainability of social security systems in general and of pension systems in particular. In response to these concerns, many countries have introduced measures aimed at increasing the length of working life. In the context of population ageing, healthy and unhealthy working-life expectancy are key policy indicators. Healthy working-life expectancy measures the total lifetime spent working while in good health, whereas unhealthy working-life expectancy captures the lifetime spent working in poor health. These measures are part of a larger family of indicators that also include active life expectancy and (total) working-life expectancy. Following these indicators over time and comparing them across countries shows the extent to which the policy goal of increasing the length of working life has been achieved and whether this progress has been made at the cost of reduced health. In their Article in The Lancet Healthy Longevity, Michaël Boissonneault and Paola Rios1Boissonneault M Rios P Changes in healthy and unhealthy working-life expectancy over the period 2002–17: a population-based study in people aged 51–65 years in 14 OECD countries.Lancet Healthy Longev. 2021; 2: e629-e638Summary Full Text Full Text PDF Scopus (1) Google Scholar provide an important contribution to the literature on healthy and unhealthy working-life expectancy. Based on the observation that countries are not monitoring healthy and unhealthy working-life expectancy continuously, the authors used data from the Health and Retirement Study in the USA, the English Longitudinal Study of Ageing, and the Survey on Health, Ageing, and Retirement in Europe to study trends in 14 countries within the Organisation for Economic Co-operation and Development. The findings of Boissonneault and Rios 1Boissonneault M Rios P Changes in healthy and unhealthy working-life expectancy over the period 2002–17: a population-based study in people aged 51–65 years in 14 OECD countries.Lancet Healthy Longev. 2021; 2: e629-e638Summary Full Text Full Text PDF Scopus (1) Google Scholar show that there is substantial cross-country variation in trends of working-life expectancy between 2002 and 2017. For instance, healthy working-life expectancy increased for men in England but decreased for men in the USA. Another key finding is that unhealthy working-life expectancy has increased in most countries. Potential explanations for this important finding, which need to be confirmed, are that unhealthy individuals can remain in work for longer because of improved treatment, or that unhealthy individuals are increasingly forced to remain in the labour market for longer because of financial obligations. The Article by Boissonneault and colleagues1Boissonneault M Rios P Changes in healthy and unhealthy working-life expectancy over the period 2002–17: a population-based study in people aged 51–65 years in 14 OECD countries.Lancet Healthy Longev. 2021; 2: e629-e638Summary Full Text Full Text PDF Scopus (1) Google Scholar presents the first comprehensive and comparative study of healthy and unhealthy working-life expectancy and highlights the usefulness of measuring these indicators. It also points to some of the opportunities and challenges for future research. These opportunities and challenges can be broadly classified into three categories: measurement, estimation, and the determinants of working-life expectancy. Approaches to the measurement of working-life expectancy often use what demographers call the period perspective. The period perspective assumes that the conditions of one period, such as a period of 1 year or a few years, persist throughout the lives of a hypothetical cohort, and results are derived for this hypothetical cohort. Thus, the results do not necessarily describe the experiences of any real cohorts.2Leinonen T Myrskylä M Martikainen P Working life and retirement expectancies at age 50 by social class: period and cohort trends and projections for Finland.J Gerontol. 2018; 73: 302-313Crossref Scopus (17) Google Scholar When estimating the results for real cohorts, data demands are much higher. However, longitudinal datasets that allow for such analyses are becoming increasingly available, and future work could leverage these data to better understand the work and health trajectories of real cohorts. Another point related to measurement is that the definition of health and work used in an analysis, and the age range considered, can have a major effect on the results. For instance, the findings provided by Boissonneault and Rios1Boissonneault M Rios P Changes in healthy and unhealthy working-life expectancy over the period 2002–17: a population-based study in people aged 51–65 years in 14 OECD countries.Lancet Healthy Longev. 2021; 2: e629-e638Summary Full Text Full Text PDF Scopus (1) Google Scholar in table 2 of their Article show that a large share of working-life expectancy is spent in poor health.1Boissonneault M Rios P Changes in healthy and unhealthy working-life expectancy over the period 2002–17: a population-based study in people aged 51–65 years in 14 OECD countries.Lancet Healthy Longev. 2021; 2: e629-e638Summary Full Text Full Text PDF Scopus (1) Google Scholar By contrast, the findings of Parker and colleagues3Parker M Bucknall M Jagger C Wilkie R Population-based estimates of healthy working life expectancy in England at age 50 years: analysis of data from the English Longitudinal Study of Ageing.Lancet Public Health. 2020; 5: e395-e403Summary Full Text Full Text PDF PubMed Scopus (13) Google Scholar indicate that only a small share of working-life expectancy is spent in poor health. These conflicting results are probably caused by differences in the measurement of health (diagnosis of chronic conditions vs work-limiting long-standing illness) and by discrepancies in the age range of the samples (51 years to 65 years vs 50 years and older). Given the sensitivity of results to the measurements used, great care is needed when comparing results. For estimating working-life expectancy, Sullivan's method is commonly used.4Sullivan DF A single index of mortality and morbidity.HSMHA Health Rep. 1971; 86: 347-354Crossref PubMed Scopus (657) Google Scholar This method combines survival probabilities with rates of employment and rates of good or poor health. Technically speaking, this method is based on prevalence rates of employment and health to measure what state individuals are in at a given point in time. By contrast, multistate models provide an alternative approach that uses incidence rates instead (ie, the probability of transitioning between states between two time points). Prevalence-based and incidence-based methods will lead to similar results when the process under investigation changes slowly.5Mathers CD Robine JM How good is Sullivan's method for monitoring changes in population health expectancies.J Epidemiol Comm Health. 1997; 51: 80-86Crossref PubMed Scopus (101) Google Scholar However, this is not the case for the labour market, which can change drastically within a short period of time. In this case, Sullivan's method can produce severely biased results.6Dudel C Lopez Gomez MA Benavides FG Myrskylä M The length of working life in Spain: levels, recent trends, and the impact of the financial crisis.Eur J Pop. 2018; 34: 769-791Crossref PubMed Scopus (16) Google Scholar Multistate models have higher data demands and are more complex but should be used whenever possible. Finally, determinants of working-life expectancy are rarely explored, and analyses are often descriptive or associational, rather than causal. Thus, little is known about the factors that shape working-life expectancy, although some research on this question has emerged in the past 10 years. Among the potential factors of working-life expectancy are the institutional setting and economic conditions at the macro level, the job and company characteristics at the meso level, and the individual health behaviours and preferences at the micro level. All these factors also influence socioeconomic inequalities in working-life expectancy, which have been less explored, even though they can be substantial.2Leinonen T Myrskylä M Martikainen P Working life and retirement expectancies at age 50 by social class: period and cohort trends and projections for Finland.J Gerontol. 2018; 73: 302-313Crossref Scopus (17) Google Scholar, 3Parker M Bucknall M Jagger C Wilkie R Population-based estimates of healthy working life expectancy in England at age 50 years: analysis of data from the English Longitudinal Study of Ageing.Lancet Public Health. 2020; 5: e395-e403Summary Full Text Full Text PDF PubMed Scopus (13) Google Scholar, 6Dudel C Lopez Gomez MA Benavides FG Myrskylä M The length of working life in Spain: levels, recent trends, and the impact of the financial crisis.Eur J Pop. 2018; 34: 769-791Crossref PubMed Scopus (16) Google Scholar Knowledge about these inequalities will be crucial for the design of equitable policies aimed at increasing the length of working life. I declare no competing interests. Changes in healthy and unhealthy working-life expectancy over the period 2002–17: a population-based study in people aged 51–65 years in 14 OECD countriesAcross countries, increases in the total number of years spent working were systematically accompanied by increases in the number of years spent working with a chronic disease. The burden of chronic diseases will probably continue to increase among older workers as countries plan to further increase their pension ages, but prevention of hypertension and arthritis could mitigate this trend. Full-Text PDF Open Access