How Do Pre-Retirement Job Characteristics ShapeOne’s Post-Retirement Cognitive Performance?
Dawn C. Carr, PhD[1]
Stanford University
Melissa Castora-Binkley, PhD
University of South Florida
Ben Lennox Kail, PhD
Georgia State University
Robert Willis, PhD
University of Michigan
Laura Carstensen, PhD
Stanford University
November 9, 2015
ABSTRACT
Objectives: This study seeks to examinewhether pre-retirement occupational characteristics impact cognitive changes associated with retirement.
Method: Using data from the Health and Retirement Study, we examined a sample of adults age 50 years or older with normal cognitive function over four waves who, at baseline, were working full-time andsubsequently either retire (n=721) or remain full time (n=1,296). We adjusted for potential selection bias using propensity scores. Exploratory factor analysis was used to identify two key job factors –intellectual and mechanical – which were coded as low, moderate, or high.
Results: Among retirees, the lowest cognitively complex jobs were related to a significantly greater level of cognitive decline relative to both those who retired from moderate or the highest cognitively complex jobs. Among retirees, low compared to high mechanically complex jobs were associated with significantly less decline. Remaining in full-time work was related to consistent levels of cognitive decline regardless of cognitive or mechanical complexity of one’s job. Among those in the highest cognitively complex and those in moderately mechanical jobs, there were no differences in cognitive decline between continuous full-time workers and retirees.
Discussion: These findings contribute to the growing base of research helping explainhow occupational factorsinfluence cognitive changes that occur with aging and retirement. We suggest that scaffolding theory, a recent theory from cognitive psychology and neuroscience, in combination with human capital theory may explain the mechanism underlying our findings.
Key Terms: cognitive performance, retirement, propensity score weighting, Health and Retirement Study
Running Head:Pre-Retirement Job Characteristics and Cognitive Decline
INTRODUCTION
At a population level, there is growing evidence that retirement has a significant, negative impact on one’s cognitive performance in later life. This finding is not merely because those with declining cognition retire while those with more robust cognitive performance continue to work. Rather, several papers find that the negative impact of early retirement on cognition, measured by a test of episodic memory, is causal (Rohwedder & Willis, 2010; Bonsang, Adam, & Perelman, 2012;Celidoni, Bianco, & Weber, 2013). These findings have been interpreted in the context of the long standing “use it or lose it” hypothesis that holds that cognitive declines associated with aging can be reduced by engaging in mental exercise. The negative impact of retirement on cognition then follows from the further hypotheses that the work environment provides more mental stimulation than the home environment and, possibly, that the expectation of early retirement reduces the incentive older workers to exert the mental effort needed to maintain their skills.
While evidence is accumulating that leaving work has a negative impact on the cognitive performance of older people, the mechanisms that underlie this effect have not been fully clarified. In this paper, we build on findings of several recent studies of older adults which suggest that pre-retirement job characteristics shape the degree to which retirement influences changes in cognitive performance. This paper adds to this line of research by estimating how retirement impacts change in cognitive performance over a six-year time span among workers whose jobs vary in complexity in both cognitive and mechancial dimensions.
To help develop hypotheses about the impact of occupational complexity, we draw on recent advances in cognitive psychology and neuroscience that are embodied in the “scaffolding theory of aging and cognition” (STAC) proposed by Park and Reuter-Lorenz 2009). The STAC is motivated by noting that while many components of cognition such as working memory, ability to learn and recall new information and fluid intelligence (i.e., reasoning ability) decline with age, most older adults continue to be able to function quite well despite these declines. Park and Reuter-Lorenz argue that the aging brain develops compensatory scaffolding (i.e. recruitment of additional neural circuitry) to shore up the deteriorating components whose function has become noisy, inefficient or both. Experimental evidence shows that sustained cognitive effort in learning a new complex task has a postive effect on episodic memory(Park et al. 2014)
We argue that the scaffolding theory is consistent with human capital theory. In that theory, an individual’s productivity in a given task depends on reasoning ability (Gf: fluid inteligence) and on the extent of knowledge relevant for that task (Gc: crystallized inteligence) where Gf and Gc tend to be complementary. Early in life, Gf increases the productivity of people in acquiring useful knowledge through schooling, job experience and and other activities (e.g., managing finances, rearing children). Later in life, accumulated knowledge increases the productivity of persons whose reasoning ability has declined. When asked to solve a novel problem, brain imaging studies show that the left pre-frontal cortex of young people lights up, suggesting that Gf is primarly involved in finding a solution. For older people confronted with the same problem, both the left and right lobes light up, suggesting that retreival of knowledge through memory processes as well as reasoning are involved. In addition, the studies find that higher performing older adults show a greater degree of bi-lateral activity than lower performing adults.Cognitively complex jobs plausibly require more mental exercise in order to maintain skills and perform more challenging tasks. This, in turn, stimulates compensatory scaffolding which serves to reduce the decline of episodic memory (Li, Baldassi, Johnson, Weber, 2012) . Moreover, greater scaffolding may enhance performance in non-work environments, thus lessening the effect of retirement on cognition.
Estimating the effect on cognition of stopping work versus the alternative of continuing to work inherently involves dealing with missing data on the unobserved alternative. Since any given individual can follow only one alternative, it is impossible to know what that person’s cognitive score would have been had he or she followed the other alternative. If it were possible to randomly assign people to a “treatment” consisting of a given pattern of work and retirement, we could estimate the average treatment effect (ATE) by calculating the difference in the mean cognitive change experienced by people who follow each alternative. However, individuals (or their employers) choose which path will be followed; hence, the assignment to a given treatment is non-random.
In this paper, we employ a counterfactual framework involving a comparison of potential outcomes—i.e., meanchange in cognition over a six year period—for persons who are are fully employed during their first two waves in the Health and Retirement Study and are fully retired during the next two waves compared to a second group who who work full time during all four waves. Under the assumption that selection into these two groups is random, conditional on observable characteristics measured at baseline, the difference in potential outcomes provides an unbiased measure of the causal average treatment effect of retirement on cognition. We discuss the plausibility of this assumption in the context of describing our econometric model.
Previous Literature
Three recent papers have begun to examine how the complexity of the work environment is related to cognitive change. The first, using data from the Swedish Adoption/Twin Study of Aging(Finkel, Andel, Gatz, & Pedersen, 2009) examined complexity of occupation on cognitive trajectory at retirement.This study found that individuals with occupations involving “high engagement with people” experienced greater improvement in verbal skills up until retirement, but experienced a faster rate of decline following retirement. The authors proposed that taking away work from one’s lifestyle as a key source of mental exercise, i.e., engaging with people, had a detrimental effect on cognitive aging.
A second study of US adultsshowed that those who engaged in more mentally demanding jobs had higher cognitive function prior to retirement, andexperienced lessdecline in cognitive performance following retirement (Fisher et al., 2014). The authors proposed that these results might stem from individuals with more cognitively complex jobs accumulating greater cognitive resilience through their pre-retirement job from which to off-set the effects of cognitive aging following retirement.
Finally, a study using National Survey of Japanese Elderly longitudinal data (Kajitani, Sakata, & McKenzie, 2013)similarly found that men who have careers that require high mathematical development, reasoning development, and language development experience less decline in memory following retirement. They also observed that jobs high in physical engagement related to greater deterioration in memory loss after retirement.
In combination, these three studies offer compelling evidence that the characteristics of one’s work environment and associated lifestyle play critical roles in one’s cognitive functioning prior to and following the retirement transition. However, these studies did not take into consideration the alternative to retirement – the expected cognitive trajectory had those individuals continued working. Notably, some individuals may experience a hastening of age-related cognitive decline despite continued employment, which may be unrelated to a retirement transition per se and perhaps related instead to pre-retirement occupational factors.Other individuals alternatively may experience little or no decline with or without a retirement transition. In fact, our recent research showsthat theeffects of work-retirement patterns on cognitive performance are not universal. For some social groups, the retirement transition offers no better or worse effect on cognitive performance than does continuous full-time work (Carr et al., under review). As a result, the effect attributed to retirement in previous research may be related to other factors. The current study seeks to address this by examining the effect of retirement relative to not retiring on cognitive change for those with similar occupational characteristics.
Theoretical Framework
One reason working may offer a better cognitive trajectory relative to retirement is that working provides a more cognitively beneficial lifestyle (Rohwedder & Willis, 2010). In other words, when people retire and stop working, they stop “using it,” and subsequently “lose it,” or rather, they experience more rapidcognitive decline(Foster & Taylor, 1920). It isnot necessarily just the capacity to learn that impacts cognitive performance, but the motivation to seek out cognitively engaging opportunities. Being removed from a complex environment, as occurs with retirement, may modify one’s cognitive trajectory because an individual is no longer required to engage in cognitively complex tasks. Some people do not seek out opportunities to maintain their cognitive function after they retire(Schooler, 1984, 1990; Schooler, Mulatu, & Oates, 2004).
One potential mechanism related to the beneficial effects of cognitively complex environmentslike work could be the building of cognitive capacity throughout one’s life span (even into later life). That is, spending many years in intellectually stimulating or mechanically complex environments– likely related to both educational attainment and occupation factors (Potter, Plassman, Helms, Foster, & Edwards, 2006) – leads to greater neuronal development, and that accumulation of excess neuronal resources, or cognitive reserve, may help people stave off the cognitive losses that come with aging(Fratiglioni & Wang, 2007).
Regardless of the specific mechanisms at play, an individual’s cognitive aging process appears to be influenced by a combination of mental stimulation across the life span (i.e., the tendency of those with greater cognitive function to pursue more complex jobs and activities leading to more significant accumulation of cognitive resources), and the individual and environmental factors that impact one’s cognitive engagement in later life (i.e., the extent to which an individual is capable and motivated to maintain cognitive function in spite of changes to the environment) (Salthouse, 2012; Salthouse, 2006; Salthouse, Atkinson, & Berish, 2003; Salthouse, Berish, & Miles, 2002). Thus, the potential relation between retirement and cognitive decline might be thought of as a response to the way pre-retirement cognitive engagement “habits” adapt to a non-work lifestyle and environment.
To understand this process, we rely on the Scaffolding Theory of Cognitive Engagement (STAC).According to STAC,brains respond to changes associated with aging through utilization of “scaffolding,” or the development of effective adaptive responses (Park & Reuter-Lorenz, 2009). They write:
Scaffolding is a normal process present across the lifespan that involves use and development of complementary, alternative neural circuits to achieve a particular cognitive goal. Scaffolding is protective of cognitive function in the aging brain, and available evidence suggests that the ability to use this mechanism is strengthened by cognitive engagement, exercise, and low levels of default network engagement.
It is plausible that certain job characteristics, particularly intellectual and mechanical tasks, shape one’s ability to cognitively adapt to age- and environment-related changes. The skills, abilities, and behaviors utilized whileengaging in work-related tasks, or during certain job-related training, skills, and education,can be thought of as a form of “scaffolding” that can be honed during one’s careerand tapped into during the post-work period. So-called cognitive maintenance following retirement (despite disengagement from work) could also be thought of as cognitive “resilience” because the effects of retirement on cognition are less than expected (Mukherjee et al., 2014). Alternatively, in some cases, a job may be cognitively stimulating enough to maintain cognitive function while working, but not offer sufficient cognitive scaffolding to adapt to the deficit of work-related stimulation in retirement, yielding significant cognitive loss.To that end, it is important to account for level of complexity and the effect on retirement by occupational characteristics between those who retire and those who continue to work when studying cognition as it relates to the retirement process.
Research Question and Hypotheses
Specifically, this research is designed to address the following research question: How do pre-retirement occupational characteristics (i.e., intellectual and mechanical) impact cognitive changes associated with retiring relative to staying engaged in full-time work? Based on empirical evidence and the STAC, we propose three hypotheses. First, we hypothesize that the relationship between retirement and cognitive decline is dependent on the cognitive stimulation of the pre-retirement job. Specifically, those with jobs that require more intellectual engagement will be more resilient and thus,experience less cognitive decline relative to those with jobs that require less intellectual engagement. However, those with jobs that require more mechanical engagement will be less resilient and thus, experience more cognitive decline relative to those with jobs that require less mechanical engagement. Second, we hypothesize that the effect of intellectual and mechanical complexity of work will be less significant for those who continue to engage in full-time work than for those who go on to retire. In other words, we expect that the work “lifestyle” will facilitate maintenance of cognitive performancewhen people retire, but the absence of a worklifestyle will increase the importance ofnon-work lifestyles in determining the impact of retirement on cognitive performance.
DESIGN AND METHOD
Our study uses the Health and Retirement Study (HRS),a nationally representative longitudinal survey of individuals over age 50 (and their spouses, regardless of the spousal age). We use data from biennial waves of the HRS from 1992 to 2010. These data are ideal for this study because they offer the most comprehensive nationally representative paneldata on US older adults available, including information about cognitive performance and work behaviors(Lachman & Weaver, 1997; RAND Center for the Study of Aging, 2008; Smith et al., 2012). For the current study, we include only individuals older than 50.
Selection of Full-Time Workers and Retirees
To test our hypotheses, we selected two samples: full-time workers and retirees. First, to evaluate the effect of pre-retirement job complexity on change in cognitive performance, we began by identifying full-time workers – i.e.,those who worked 35 hours or more and self-identified as not retired. From this group, we identified two samples –those who transition from full-time work in wavet to retirement in wavet+1and those who stay working full-time in both waves. We exclude retirees who engage in paid work for two reasons. First, given the focus of this study on the lasting cognitive impact on departing from paid work,those engaging in paid work in retirement are still participating in a “work lifestyle.”While itmay be helpful to assess the effect of variations in pathways to retirement on the cognitive decline trajectory, individuals whose labor force status was recorded as “retired” (even if they did engage in part-time paid work) were not consistently asked about their occupation, preventing us from taking into consideration how work tasks changed post-retirement. Additionally, recent research suggests that regardless of how retirement is defined, the relative effect of characteristics of pre-retirement work on post-retirement cognitive performance does not change (Kajitani et al., 2013). Thus, for this study, we choose a conservative definition for retirement, limiting our retiree sample to those individuals whotransition fromfull-time workto completeretirement (i.e., for the first time while participating in the HRS, self-identifyingas being retired andworking 0 hours per week).
Second, in order to accurately measure cognitive changes in association with a potential retirement transition, we selected specific pre- and post-retirement cognitive performance measures. First, there is evidence that people may begin cognitively disengaging from work inpreparation for retirement, and this may result in cognitive decline while working in the period leading up to retirement(Bonsang et al., 2012; Willis, 2013). Thus, to avoid this complication, our baseline cognitive performance occurs two waves prior to retirement, limiting our sample only to those working full-time for two consecutive waves prior to retirement. Second, the long-term adjustment to retirement,with regard to a shift in the cognitive performance trajectory, does not occuruntil at least one full year following retirement(Bonsang et al., 2012). Thus, to ensure that our post-retirement cognitive performance is observed with an appropriate lag, our post-retirement measure derives from cognitive status at the wave following reported retirement, limiting our sample to only those retirees who continuously remain fully retired in the wave following reported retirement.