research on job satisfaction during middle adulthood has found

Job Satisfaction Tends to Increase with Age

• Industrial/Organizational Psychology
• Life Satisfaction

“We demonstrated that age and tenure have opposite relationships with job satisfaction, such that job satisfaction increased as people aged yet decreased as tenure advanced — and received a boost when people moved to a new organization, thus starting the cycle anew,” writes psychological scientists Shoshana Dobrow Riza (London School of Economics and Political Science), Yoav Ganzach (Tel Aviv University), and Yihao Liu (University of Florida).

The core result, the researchers explain, was that job satisfaction somewhat paradoxically increased with age yet decreased with tenure.

Previous research has suggested that as people age –and gain better pay and benefits – job satisfaction tends to increase. However, studies looking at job tenure (how long someone has been at an organization), often find that job satisfaction declined over time. That is, whether or not job satisfaction increases over time seems to depend on which time metric researchers are using: age in years or the number of years someone has been at a specific job.

Riza and colleagues hypothesized that as people get older, they gain more experience in the labor market and obtain better, higher-paying jobs, thus leading to higher job satisfaction. But, as job tenure increases, individuals may receive fewer opportunities for advancement, or become bored.

The 1979 and 1997 cohorts of the National Longitudinal Survey of Youth are two long-running studies conducted by the US Department of Labor’s Bureau of Labor Statistics. Both studies included a wide range of questions about background characteristics, education, and employment collected over a long period of time (29 years and 12 years, respectively).

“These characteristics enable us to untangle the effects of age and tenure simultaneously, unlike previous cross-sectional and shorter-term longitudinal research,” the researchers explain.

The 1979 cohort includes a nationally representative sample of 12,686 Americans born between 1957 and 1964. Participants were interviewed about their lives over the course of 29 years, providing 22 waves of interview responses from adolescence (i.e., ages 14–22 in 1979) through mature adulthood (i.e., ages 43–51 in 2008). The 1997 cohort included 8,984 Americans born between 1980 and 1984. Participants were interviewed annually beginning when they were 12 to 16 years old in 1997 through 2008, when they were between ages 23 and 27.

Both studies included a single question asking participants to rate their current level of satisfaction at work using either a 4- or 5-point scale. Both studies also included detailed information about wages and income.

Both datasets showed the same paradoxical correlations: “As people grew older, they became increasingly satisfied with their jobs, while during employment in a given organization, they became decreasingly satisfied as time advanced.”

Job satisfaction seemed to follow a cyclical pattern where people experienced a boost in job satisfaction when they first started “the honeymoon period” at a new organization. However, this boost tended to decrease over time until an individual moved on to the next organization. But after each change in employment, the overall boost in the job satisfaction cycle started out a little higher on average.

“Overall, the results regarding age indicate that as employees became older and moved between different organizations, they tended to experience an increase in job satisfaction, which can be partially explained by earning higher pay in the new job,” Riza and colleagues write.

The researcher team cautions that they were not able to test a causal theory directly, and that future research would benefit from looking at a wider array of job benefits beyond just pay. To counteract the expected decline in job satisfaction from veteran employees, the researchers suggest that managers look for ways to change things up a bit, providing opportunities for job rotations, temporary relocation assignments, or sabbaticals.

Dobrow Riza, S., Ganzach, Y., & Liu, Y. (2016). Time and job satisfaction: a longitudinal study of the differential roles of age and tenure. Journal of Management . doi: 10.1177/0149206315624962

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Middle Adulthood: Generativity, Intelligence, Personality

Learning Objectives: Middle Adulthood

• Describe how the perception of time changes as we age.
• Explain why “midlife crisis” is not an appropriate interpretation of middle adulthood.
• Define crystallized and fluid intelligence.
• Explain how intelligence changes with age.
• Discuss how creativity changes with age, and how we can promote creativity.
• Identify expertise and describe why it is important.
• Explain the importance of everyday problem-solving in work competence.
• Describe how ageism shows up at work and discuss research findings on ageism in the workplace.
• Describe how personality develops over time.
• Explain the stability that is often found in personality over time.
• Describe the causes of personality change over time.

Developmental Task of Middle Age: Generativity vs. Stagnation

According to Erikson (1950, 1982) generativity encompasses procreativity, productivity, creativity, and legacy. This stage includes the generation of new beings, new ideas or creations, and lasting contributions, as well as self-generation concerned with further identity development. Erikson believed that the stage of generativity, which lasts from the 40s to the 60s, during which one established a family and career, was the longest of all the stages. Individuals at midlife are primarily concerned with leaving a positive legacy of themselves, and parenthood is the primary generative type. Erikson understood that work and family relationships may be in conflict due to the obligations and responsibilities of each, but he believed it was overall a positive developmental time. In addition to being parents and working, Erikson also described individuals as being involved in the community during this stage, for example, providing mentoring, coaching, community service, or taking leadership in church or other community organizations. A sense of stagnation occurs when one is not active in generative matters, however, stagnation can motive a person to redirect energies into more meaningful activities.

Erikson identified “virtues” for each of his eight stages, and the virtue emerging when one achieves generativity is “care”. Erikson believed that those in middle adulthood should “take care of the persons, the products, and the ideas one has learned to care for” (Erikson, 1982, p. 67). Further, Erikson believed that the strengths gained from the six earlier stages are essential for the generational task of cultivating strength in the next generation. Erikson further argued that generativity occurred best after the individual had resolved issues of identity and intimacy (Peterson & Duncan, 2007).

Research has demonstrated that generative adults possess many positive characteristics, including good cultural knowledge and healthy adaptation to the world (Peterson & Duncan, 2007). Using the Big 5 personality traits, generative women and men scored high on conscientiousness, extraversion, agreeableness, openness to experience, and low on neuroticism (de St. Aubin & McAdams, 1995; Peterson, Smirles, & Wentworth, 1997). Additionally, women scoring higher on generativity at age 52, were rated higher in positive personality characteristics, reported higher satisfaction with marriage and motherhood, and showed more successful aging at age 62 (Peterson & Duncan, 2007). Similarly, men rated higher on generativity at midlife also showed stronger global cognitive functioning (e.g., memory, attention, calculation), stronger executive functioning (e.g., response inhibition, abstract thinking, cognitive flexibility), and lower levels of depression in late adulthood (Malone, Liu, Vaillant, Rentz, & Waldinger, 2016).

Erikson (1982) indicated that at the end of this demanding stage, individuals may withdraw as generativity is no longer expected in late adulthood. This releases elders from the task of caretaking or working. However, not feeling needed or challenged may result in stagnation, and consequently one should not fully withdraw from generative tasks as they enter Erikson’s last stage in late adulthood.

Challenges at Midlife

There are many socioemotional changes that occur in how middle-aged adults perceive themselves. While people in their early 20s may emphasize how old they are to gain respect or to be viewed as experienced, by the time people reach their 40s they tend to emphasize how young they are. For instance, few 40-year olds cut each other down for being so young stating: “You’re only 43? I’m 48!” A previous focus on the future gives way to an emphasis on the present. Neugarten (1968) notes that in midlife, people no longer think of their lives in terms of how long they have lived. Rather, life is thought of in terms of how many years are left.

Midlife Crisis? Daniel Levinson’s 1978 book entitled The Seasons of a Man’s Life presented a theory of development in adulthood. Levinson’s work was based on in-depth interviews with 40 men between the ages of 35-45. Levinson (1978) indicated that adults go through stages and have an image of the future that motivates them. This image is called “the dream” and for the men interviewed, it was a dream of how their career paths would progress and where they would be at midlife. According to Levinson the midlife transition (40-45) was a time of reevaluating previous commitments; making dramatic changes if necessary; giving expression to previously ignored talents or aspirations; and feeling more of a sense of urgency about life and its meaning. By the time these men entered middle adulthood (45-50), they generally had committed to the new choices they made and channeled their energies into these commitments.

Levinson believed that a midlife crisis was a normal part of development as the person is more aware of how much time has gone by and how much time is left. The future focus of early adulthood gives way to an emphasis on the present in midlife, and the men interviewed had difficulty reconciling the “dream” they held about the future with the reality they currently experienced . Consequently, they felt impatient and were no longer willing to postpone the things they had always wanted to do. Although Levinson believed his research demonstrated the existence of a midlife crisis, his work has been criticized for its research methodology, including its focus on men only, its small sample size, narrow age range, and concerns about a cohort effect. In fact, other research does not support his theory of the midlife crisis.

Vaillant (2012) believed that it was the cross-sectional design of Levinson’s study that led to the erroneous conclusion of an inevitable midlife crisis . Instead, he believed that the longitudinal study of an individual’s entire life was needed to determine the factors associated with optimum health and potential. Vaillant was one of the main researchers in the 75 year long Harvard Study of Adult Development, and he considered a midlife crisis to be a rare occurrence among the participants (Vaillant, 1977). Additional findings of this longitudinal study will be discussed in the next chapter on late adulthood.

Most research suggests that the majority of people in the United States today do not experience a midlife crisis . Results of a 10-year longitudinal study conducted by the MacArthur Foundation Research Network on Successful Midlife Development, based on telephone interviews with over 3,000 midlife adults, suggest that the years between 40 and 60 are typically marked by a sense of well-being. Only 23% of their participants reported experiencing a midlife crisis. The crisis tended to occur among highly educated men and was typically triggered by a major life event rather than out of a fear of aging (Research Network on Successful Midlife Development, 2007).

Intelligence in Middle Adulthood

The brain at midlife has been shown to not only maintain many of the abilities of young adults, but also gain new ones. Some individuals in middle age actually have improved cognitive functioning (Phillips, 2011). The brain continues to demonstrate plasticity and rewires itself in middle age based on experiences. Research has demonstrated that older adults use more of their brains than younger adults. In fact, older adults who perform the best on tasks are more likely to demonstrate bilateralization than those who perform worst. Additionally, the amount of white matter in the brain, which is responsible for forming connections among neurons, increases into the 50s before it declines.

Emotionally, the middle-aged brain is calmer, less neurotic, more capable of managing emotions, and better able to negotiate social situations (Phillips, 2011). Older adults tend to focus more on positive information and less on negative information than do younger adults. In fact, they also remember positive images better than those younger. Additionally, the older adult’s amygdala responds less to negative stimuli. Lastly, adults in middle adulthood make better financial decisions, a capacity which seems to peak at age 53, and show better economic understanding. Although greater cognitive variability occurs among middle aged adults when compared to those both younger and older, those in midlife who experience cognitive improvements tend to be more physically, cognitively, and socially active.

Crystalized versus Fluid Intelligence.  Intelligence is influenced by heredity, culture, social contexts, personal choices, and certainly age. One distinction in specific intelligences noted in adulthood, is between fluid intelligence , which refers to the capacity to learn new ways of solving problems and performing activities quickly and abstractly , and crystallized intelligence , which refers to the accumulated knowledge of the world we have acquired throughout our lives (Salthouse, 2004). These intelligences are distinct, and show different developmental pathways as pictured in Figure 9.2. Fluid intelligence tends to decrease with age (staring in the late 20s to early 30s), whereas crystallized intelligence generally increases all across adulthood (Horn, Donaldson, & Engstrom, 1981; Salthouse, 2004).

Fluid intelligence, sometimes called the mechanics of intelligence, tends to rely on perceptual speed of processing, and perceptual speed is one of the primary capacities that shows age-graded declines starting in early adulthood, as seen not only in cognitive tasks but also in athletic performance and other tasks that require speed. In contrast, research demonstrates that crystallized intelligence, also called the pragmatics of intelligence, continues to grow all during adulthood, as older adults acquire additional semantic knowledge, vocabulary, and language. As a result, adults generally outperform younger people on tasks where this information is useful, such as measures of history, geography, and even on crossword puzzles (Salthouse, 2004). It is this superior knowledge, combined with a slower and more complete processing style, along with a more sophisticated understanding of the workings of the world around them, that gives older adults the advantage of “wisdom” over the advantages of fluid intelligence which favor the young (Baltes, Staudinger, & Lindenberger, 1999; Scheibe, Kunzmann, & Baltes, 2009).

These differential changes in crystallized versus fluid intelligence help explain why older adults do not necessarily show poorer performance on tasks that also require experience (i.e., crystallized intelligence), although they show poorer memory overall. A young chess player may think more quickly, for instance, but a more experienced chess player has more knowledge to draw upon.

Seattle Longitudinal Study.  The Seattle Longitudinal Study has tracked the cognitive abilities of adults since 1956. Every seven years the current participants are evaluated, and new individuals are also added. Approximately 6000 people have participated thus far, and 26 people from the original group are still in the study today. Current results demonstrate that middle-aged adults perform better on four out of six cognitive tasks than those same individuals did when they were young adults. Verbal memory, spatial skills, inductive reasoning (generalizing from particular examples), and vocabulary increase with age until one’s 70s (Schaie, 2005; Willis & Shaie, 1999). In contrast, perceptual speed declines starting in early adulthood, and numerical computation shows declines starting in middle and late adulthood (see Figure 9.3).

Cognitive skills in the aging brain have been studied extensively in pilots, and similar to the Seattle Longitudinal Study results, older pilots show declines in processing speed and memory capacity, but their overall performance seems to remain intact. According to Phillips (2011) researchers tested pilots age 40 to 69 as they performed on flight simulators. Older pilots took longer to learn to use the simulators but subsequently performed better than younger pilots at avoiding collisions.

Tacit knowledge is knowledge that is pragmatic or practical and learned through experience rather than explicitly taught, and it also increases with age (Hedlund, Antonakis, & Sternberg, 2002). Tacit knowledge might be thought of as “know-how” or “professional instinct.” It is referred to as tacit because it cannot be codified or written down. It does not involve academic knowledge, rather it involves being able to use skills and to problem-solve in practical ways. Tacit knowledge can be seen clearly in the workplace and underlies the steady improvements in job performance documented across age and experience, as seen for example, in the performance of both white and blue collar workers, such as carpenters, chefs, and hair dressers.

Middle Adults Returning to College.  Midlife adults in the United States often find themselves in university classrooms. In fact, the rate of enrollment for older Americans entering college, often part-time or in the evenings, is rising faster than that of traditionally aged students. Students over age 35, accounted for 17% of all college and graduate students in 2009, and are expected to comprise 19% of that total by 2020 (Holland, 2014). In some cases, older students are developing skills and expertise in order to launch a second career, or to take their career in a new direction. Whether they enroll in school to sharpen particular skills, to retool and reenter the workplace, or to pursue interests that have previously been neglected, older students tend to approach the learning process differently than younger college students (Knowles, Holton, & Swanson, 1998).

The mechanics of cognition, such as working memory and speed of processing, gradually decline with age. However, they can be easily compensated for through the use of higher order cognitive skills, such as forming strategies to enhance memory or summarizing and comparing ideas rather than relying on rote memorization (Lachman, 2004). Although older students may take a bit longer to learn material, they are less likely to forget it as quickly. Adult learners tend to look for relevance and meaning when learning information. Older adults have the hardest time learning material that is meaningless or unfamiliar. They are more likely to ask themselves, “Why is this important?” when being introduced to information or when trying to memorize concepts or facts.

Older adults are more task-oriented learners and want to organize their activity around problem-solving or making contributions to real world issues. Rubin et al. (2018) surveyed university students aged 17-70 regarding their satisfaction and approach to learning in college. Results indicated that older students were more independent, inquisitive, and intrinsically motivated compared to younger students. Additionally, older women processed information at a deeper learning level and expressed more satisfaction with their education. Just as at younger ages, during middle adulthood, more women than men are likely to attend and graduate from college.

To address the educational needs of those over 50, The American Association of Community Colleges (2016) developed the Plus 50 Initiative that assists community colleges in creating or expanding programs that focus on workforce training and new careers for the plus-50 population . Since 2008 the program has provided grants for programs in 138 community colleges affecting over 37, 000 students. The participating colleges offer workforce training programs that prepare 50 plus adults for careers such as early childhood educators, certified nursing assistants, substance abuse counselors, adult basic education instructors, and human resources specialists. These training programs are especially beneficial because 80% of people over the age of 50 say they will retire later in life than their parents or continue to work in retirement, including work in a new field.

Erikson defined the developmental task of generativity as one that included creativity. But what is creativity? Better yet, what do you think creativity is? Perhaps take a second and reflect on cultural monuments, architecture, artworks, music, theatre, and literature. Take the Mona Lisa and then compare it to the Starry Night, in the figure below. Is one of these more creative than the other? If so, what makes one piece more creative than the other?

There are many definitions of creativity, both scientific and non-scientific. Franken (2001) defines creativity as “the tendency to generate or recognize ideas, alternatives, or possibilities that may be useful in solving problems… and entertaining ourselves and others.” Does this definition change your answer to the question posed in the previous paragraph?

Psychologists who study creativity largely agree on three components. First, creativity involves a great deal of divergent thinking , that is, the ability to look at things from different perspectives . Secondly, creativity involves a unique perspective or some element of originality . Finally, creativity must have functionality in that a creative work serves some function or some value . While paintings such as the Mona Lisa and Starry Night both display various degrees of originality and divergent thinking, their functionality may not be as transparent as other creative works, such as unique architectural designs.

Aside from the elements of creativity, researchers are also interested in the creative process . There are four steps to this process that are generally agreed upon. First is the period of preparation , that is, the conscious and effortful practice of studying and gathering information on a creative endeavor. A second step is the incubation period; a largely unconscious process whereby the mind makes new connections and processes knowledge ‘behind the scenes.’ A third step is illumination , or the ‘Aha!’ moment, that is, an insight generated from conscious and unconscious processes. Finally, revision refers to the part of the processes whereby a creative work is revisited before it is finalized in order to ensure it accomplishes its original goals.

Developmental scientists have found common trajectories in the development of creativity. Generally, we see creativity increase into the 30’s and middle adulthood, as we are developing expertise, motivation, and cognition. This is not to say that creative output follows the same patterns across all fields of work and study. In mathematics heavy disciplines, for example, creativity generally peaks soon after formal training and at a very young age. This makes sense when we consider the early decreases in working memory capacity and processing speed, which are two elements of math heavy work such as physics and engineering.

Developmental trajectories in creativity in mathematics are opposite to those in fields such as the humanities, social sciences, and the arts, where we find that creativity often peaks later in life, as more life experience and knowledge accumulate. Nevertheless, typical trajectories for the development of creativity are just that – average experiences. This is not to say that there are not exceptions to these rules. For example, engineers such as Elon Musk make some of their most creative contributions later in life, whereas social scientists, such as Jean Piaget, made contributions to their fields at exceedingly early ages. As with most areas of development, the study of creativity is not without its mysteries and there is much room for theoretical development and empirical study.

Work and Careers in Middle Adulthood

Expertise refers to specialized skills and knowledge that pertain to a particular topic or activity . In contrast, a novice is someone who has limited experiences with a particular task . Everyone develops some level of “selective” expertise in vocational activities or other areas that are personally meaningful to them, such as making bread, quilting, gardening, computer programming, or caring for children. Expert thought is often characterized as intuitive, automatic, strategic, and flexible.

• Intuitive.  Novices follow particular steps and rules when problem solving, whereas experts can call upon a vast amount of knowledge and past experience. As a result, their actions appear more intuitive than formulaic. Novice cooks may slavishly follow the recipe step by step, while chefs may glance at recipes for ideas and then follow their own procedure.
• Automatic.  Complex thoughts and actions become more routine for experts. Their reactions appear instinctive over time, and this is because expertise allows us to process information faster and more holistically and effectively (Crawford & Channon, 2002).
• Strategic.  Experts have more effective strategies than non-experts. For instance, while both skilled and novice doctors generate several hypotheses within minutes of an encounter with a patient, the more skilled clinicians’ conclusions are likely to be more accurate. In other words, they generate better hypotheses than the novice. This is because they are able to discount misleading symptoms and other distractors and hone in on the most likely problem the patient is experiencing (Norman, 2005). Consider how your note taking skills may have changed after being in school over a number of years. Chances are you do not write down everything the instructor says, but instead extract and note the most central ideas. You may have even come up with your own short forms for commonly mentioned words in a course, allowing you to take down notes faster and more efficiently than someone who may be a novice academic note taker.
• Flexible.  Experts in all fields are more curious and creative. They enjoy a challenge and experiment with new ideas or procedures. The only way for experts to grow in their knowledge is to take on more challenging, rather than routine tasks.

Gaining Expertise. Developing expertise takes time. It is a long process, resulting from repeated experience and protracted practice (Ericsson, Feltovich, & Prietula, 2006). When they are faced with a problem, middle-aged adults often find that, with their store of knowledge and experience, they have encountered something similar before. This allows them to ignore the irrelevant and focus on the important aspects of the issue. The development of expertise is one reason why many people often reach the top of their career in middle adulthood.

However, expertise cannot fully make-up for all losses in general cognitive functioning as we age. The superior performance of older adults in comparison to younger novices appears to be task specific (Charness & Krampe, 2006). As we age, we also need to be more deliberate in our practice of skills in order to maintain them. Charness and Krampe (2006) in their review of the literature on aging and expertise, also note that the rate of return for our effort diminishes as we age. In other words, increasing practice does not recoup the same advances in older adults as similar efforts do at younger ages.

Climate in the Workplace for Middle-aged Adults.  A number of studies have found that job satisfaction tends to peak in middle adulthood (Besen, Matz-Costa, Brown, Smyer, & Pitt-Catsouphers, 2013; Easterlin, 2006). This satisfaction stems not only from higher wages, but also often from greater involvement in decisions that affect the workplace as middle aged adults move up from worker to supervisor or manager. Job satisfaction is also influenced by being able to do the job well, and after years of experience at a job many people are more effective and productive. Another reason for this peak in job satisfaction is that at midlife many adults lower their expectations and goals (Tangri, Thomas, & Mednick, 2003). Middle-aged employees may realize that they have arrived at the highest level they are likely to reach in their career. This satisfaction at work translates into lower absenteeism, greater productivity, and less job hopping in comparison to younger adults (Easterlin, 2006).

However, not all middle-aged adults are happy in the workplace. Women may find themselves bumping up against the glass ceiling. This may explain why females employed at large corporations are twice as likely to quit their jobs as are men (Barreto, Ryan, & Schmitt, 2009). Another problem older workers may encounter is job burnout , defined as unsuccessfully managed workplace stress (World Health Organization, 2019). Burnout consists of:

• Feelings of energy depletion or exhaustion
• Increased mental distance from one’s job, or feelings of job negativism or cynicism
• Reduced feelings of professional effectiveness or efficacy

American workers may experience burnout more often than workers in many other developed nations, because most developed nations guarantee by law a set number of paid vacation days (International Labour Organization, ILO, 2011), whereas the United States does not (U.S. Department of Labor, 2016).

In addition, in comparision to workers in many other developed nations, American workers work more hours per year (Organisation for Economic Cooperation and Development, OECD, 2016). Not all employees in the US are covered under overtime pay laws (U.S. Department of Labor, 2016). This is important when you considered that the 40-hour work week is a myth for most Americans. Only 4 in 10 U.S. workers work the typical 40-hour work week. The average work week for many is almost a full day longer (47 hours), with 39% working 50 or more hours per week (Saad, 2014). As can be seen in Figure 9.5, Americans work more hours than most European nations, especially western and northern Europe, although they work fewer hours than workers in other nations, especially Mexico.

Challenges in the Workplace for Middle-aged Adults.  In recent years middle aged adults have been challenged by economic downturns, starting in 2001, and again in 2008 and 2020. During the recession of 2008, fifty-five percent of adults reported some problems in the workplace, such as fewer hours, pay-cuts, having to switch to part-time, etc. (Pew Research Center, 2010a). While young adults took the biggest hit in terms of levels of unemployment, middle-aged adults also saw their overall financial resources suffer as their retirement nest eggs disappeared and house values shrank, while foreclosures increased (Pew Research Center, 2010b). Not surprisingly, this age group, especially those age 50-64, reported that the recession hit them worse than did other age groups.

Middle-aged adults who find themselves unemployed are likely to remain so longer than those in early adulthood (U.S. Government Accountability Office, 2012). Agism is a common complaint in the workplace. For example, in the eyes of employers, it may seem more cost effective to hire a young adult, despite their limited experience, as they would be starting out at lower levels on the pay scale. In addition, hiring someone who is 25 and has many years of work ahead of them versus someone who is 55 and will likely retire in 10 years may also be part of the decision to hire a younger worker (Lachman, 2004).  It may surprise employers to learn that older workers typically stay on the job longer, as younger workers are more geographically mobile and more likely to switch jobs as more attractive opportunities appear. Older adults also demonstrate lower rates of absenteeism and greater investment in their work. American workers are also competing with global markets and changes in technology. Those who are able to keep up with all these changes or are willing to uproot and move around the country or even the world have a better chance of finding work. The decision to move may be easier for people who are younger and have fewer obligations to others.

Personality

If you remember from our study of infancy, temperament is defined as the innate characteristics of the infant, including mood, activity level, and emotional reactivity, noticeable soon after birth . Does one’s temperament remain stable through the lifespan? Do shy and inhibited babies grow up to be shy adults, while the sociable child continues to be the life of the party? Like most developmental research the answer is more complicated than a simple yes or no. Chess and Thomas (1987), who identified children as easy, difficult, or slow-to-warm-up, found that children identified as easy grew up to became well-adjusted adults, while those who exhibited a difficult temperament were not as well-adjusted as adults.

Kagan (2002) studied the temperamental category of “inhibition to the unfamiliar” in young children. Inhibited infants exposed to unfamiliarity reacted strongly to the stimuli and cried loudly, pumped their limbs, and had an increased heart rate. Research has indicated that these highly reactive children show temperamental stability into early childhood, and Bohlin and Hagekull (2009) found that shyness in infancy was linked to social anxiety in adulthood. An important aspect of the research on inhibition was looking at the response of the amygdala, which is important for fear and anxiety, especially when confronted with possible threatening events in the environment. Using functional magnetic resonance imaging (FMRIs) young adults identified as strongly inhibited when they were toddlers showed heightened activation of the amygdala when compared to those identified as uninhibited when toddlers (Davidson & Begley, 2012).

This research does seem to indicate that temperamental stability holds for many individuals through the lifespan, yet we know that one’s environment can also have a significant impact. Recall from our discussion on epigenesis  that  environmental factors modify gene expression by switching genes on and off. Many cultural and environmental factors can affect one’s temperament, including exposure to teratogens in utero , early exposure to harsh parenting, adversity, or child abuse, supportive child-rearing, stable homes, illnesses, socioeconomic status, etc. Additionally, individuals often choose environments that align with their temperaments, which in turn further strengthens them (Cain, 2012). Individuals are also active in other ways. As they get older, adults can choose how they wish to express their temperaments, deciding for example, that they will not let an inhibited temperament stop them from experiencing adventures, such as travel. In summary, because temperament is neurophysiological, biology appears to be a main reason why temperament remains stable into adulthood. In contrast, the environment appears mainly responsible for changes or modifications in temperament (Clark & Watson, 1999).

Everybody has their own unique personality,  that is, their characteristic manner of thinking, feeling, behaving, and relating to others (John, Robins, & Pervin, 2008). Personality traits refer to these characteristic, routine ways of thinking, feeling, and relating to others. Personality integrates one’s temperament with cultural and environmental influences. Consequently, there are signs or indicators of these traits in childhood, but they become particularly evident when the person is an adult. Personality traits are integral to each person’s sense of self, as they involve what people value, how they think and feel about things, what they like to do, and, basically, what they are like most every day throughout much of their lives.

Table 9.1 Descriptions of the Big Five Personality Traits

adapted from Lally & Valentine-French (2019) and John, Naumann, & Soto (2008)

Five-Factor Model.  There are hundreds of different personality traits, and all of these traits can be organized into the broad dimensions referred to as the Five-Factor Model (John, Naumann, & Soto, 2008). These five broad domains include: Openness, Conscientiousness, Extraversion, Agreeableness, and Neuroticism. (You can use “OCEAN” as a mnemonic to remember them.) This applies to traits that you may use to describe yourself.

Does personality change throughout adulthood? Previously the answer was no, but contemporary research shows that although some people’s personalities are relatively stable over time, others are not (Lucas & Donnellan, 2011; Roberts & Mroczek, 2008). Longitudinal studies reveal average changes during adulthood in the expression of some traits (e.g., neuroticism and openness decrease with age and conscientiousness increases) and individual differences in these patterns due to idiosyncratic life events (e.g., divorce, illness). Longitudinal research also suggests that adult personality traits, such as conscientiousness, predict important life outcomes including job success, health, and longevity (Friedman et al., 1993; Roberts, Kuncel, Shiner, Caspi, & Goldberg, 2007).

Research in the Harvard Health Letter (2012) documents  correlations between conscientiousness and many positive health outcomes, such as lower blood pressure, lower rates of diabetes and stroke, fewer joint problems, being less likely to engage in harmful behaviors, and being more likely to stick to healthy behaviors and avoid stressful situations. Conscientiousness also appears positively related to career choices, friendships, and stability of marriage. Lastly, a person possessing both self-control and organizational skills, both of which are related to conscientiousness, may withstand the effects of aging better and have stronger cognitive skills than one who does not possess these qualities.

Supplemental Materials

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• This Ted Talk discusses ways to cultivate inclusion and encourage diversity in the workplace.
• This podcast interviews Dr. Pauline Boss on her concept of ambiguous loss.

https://podcasts.apple.com/us/podcast/pauline-boss-navigating-loss-without-closure/id150892556?i=1000485211124

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“Lifespan Development: A Psychological Perspective, Second Edition” by Martha Lally and Suzanne Valentine-French is licensed under a CC-BY-NC-SA-3.0

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32 Work and Leisure in Middle Adulthood

Workforce participation in canada and the u.s..

The Organization for Economic Cooperation and Development (OECD) defines workforce participation as the proportion of people ages  15 to 64 that is employed (OECD, 2019). Economic cycles change quickly. Workforce participation of one cohort can differ dramatically from that of another cohort. In 2019 workforce participation in Canada was estimated to be 74.5% and in the United States, 71.1% (OECD).

Climate in the Workplace for Middle-aged Adults

A number of studies have found that job satisfaction tends to peak in middle adulthood (Besen, Matz-Costa, Brown, Smyer, & Pitt- Catsouphers, 2013; Easterlin, 2006). This satisfaction stems from not only higher wages, but often greater involvement in decisions that affect the workplace as they move from worker to supervisor or manager.  Job satisfaction is also influenced by being able to do the job well, and after years of experience at a job many people are more effective and productive.  Another reason for this peak in job satisfaction is that at midlife many adults lower their expectations and goals (Tangri, Thomas, & Mednick, 2003).  Middle-aged employees may realize they have reached the highest they are likely to in their career.  This satisfaction at work translates into lower absenteeism, greater productivity, and less job hopping in comparison to younger adults (Easterlin, 2006).

However, not all middle-aged adults are happy in the work place.  Women may find themselves up against the glass ceiling , organizational discrimination in the workplace that limits the career advancement of women .  This may explain why females employed at large corporations are twice as likely to quit their jobs as are men (Barreto, Ryan, & Schmitt, 2009).  Another problem older workers may encounter is job burnout , becoming disillusioned and frustrated at work . U.S. workers may experience more burnout than do workers in many other developed nations, because most developed nations guarantee by law a set number of paid vacation days (International Labour Organization, ILO, 2011), the United States had neither federally-required paid holidays or paid vacation does  (Maye, 2019; U.S. Department of Labor, 2016). Canada in contrast requires 10 paid vacations days and 9 paid holidays. Recent statistics (Maye) show growing disparity with time allotted remaining the same for Canada and the U.S., while Japan now mandates 15 paid holidays in addition to 10 paid vacation days.

Not all employees are covered under overtime pay laws (U.S. Department of Labor, 2016). This is important when you considered that the 40-hour work week is a myth for most Americans. Only 4 in 10 U.S. workers work the typical 40-hour work week.  The average work week for many is almost a full day longer (47 hours), with 39% working 50 or more hours per week (Saad, 2014). In comparison to workers in many other developed nations, Canadian and American workers work more hours per year (Organisation for Economic Cooperation and Development, OECD, 2016). As can be seen in Figure 8.19, North Americans work more hours than most European nations, especially western and northern Europe, although they work less hours than workers in other nations, especially Mexico.

Challenges in the Workplace for Middle-Aged Adults

In recent years middle aged adults have been challenged by economic downturns, starting in 2001, and again in 2008.  Fifty-five percent of adults reported some problems in the workplace, such as fewer hours, pay-cuts, having to switch to part-time, etc., during the most recent economic recession (see Figure 8.20, Pew Research Center, 2010a). While young adults took the biggest hit in terms of levels of unemployment, middle-aged adults also saw their overall financial resources suffer as their retirement nest eggs disappeared and house values shrank, while foreclosures increased (Pew Research Center, 2010b). Not surprisingly this age group reported that the recession hit them worse than did other age groups, especially those age 50-64. Middle aged adults who find themselves unemployed are likely to remain unemployed longer than those in early adulthood (U.S. Government Accountability  Office, 2012).

In the eyes of employers, it may be more cost effective to hire a young adult, despite their limited experience, as they would be starting out at lower levels of the pay scale.  In addition, hiring someone who is 25 and has many years of work ahead of them versus someone who is 55 and will likely retire in 10 years may also be part of the decision to hire a younger worker (Lachman, 2004).  American workers are also competing with global markets and changes in technology.  Those who are able to keep up with all these changes, or are willing to uproot and move around the country or even the world have a better chance of finding work. The decision to move may be easier for people who are younger and have fewer obligations to others.

In Canada, the recession of 2008 was a bit less severe than in the U.S. for a number of reasons. One is thought to have been Canadian employers’ practice of relying equally on reducing hours and eliminating jobs (Grant, 2018).

As most developed nations restrict the number of hours an employer can demand that an employee work per week, and require employers to offer paid vacation time, what do middle aged adults do with their time off from work and duties , referred to as leisure ?  Around the world the most common leisure activity in both early and middle adulthood is watching television (Marketing Charts Staff, 2014).  On average, middle aged adults spend 2-3 hours per day watching TV (Gripsrud, 2007) and watching TV accounts for more than half of all the leisure time (see Figure 8.21).

In the United States, men spend about 5 hours more per week in leisure activities, especially on weekends, than do women (Drake, 2013; U.S. Bureau of Labor Statistics, 2016).  The leisure gap between mothers and fathers is slightly smaller, about 3 hours a week, than among those without children under age 18 (Drake, 2013).  Those age 35-44 spend less time on leisure activities than any other age group, 15 or older (U.S. Bureau of Labor Statistics, 2016). This is not surprising as this age group are more likely to be parents and still working up the ladder of their career, so they may feel they have less time for leisure.

Americans have less leisure time than people in many other developed nations.  As you read earlier, there are no laws in many job sectors guaranteeing paid vacation time in the United States (see Figure 8.22). Ray, Sanes and Schmitt (2013) report that several other nations also provide additional time off for young and older workers and for shift workers. In the United States, those in higher paying jobs and jobs covered by a union contract are more likely to have paid vacation time and holidays (Ray & Schmitt, 2007).

But do Canadian and U.S. workers take their time off?  

A survey by a Canadian payroll management company indicated that only a third of Canadian workers took the 2 weeks annual vacation they are allotted, and an additional 28% said they took less than half of the 2 weeks (Desjardins, 2018). According to Project Time-Off (2016), 55% of U.S. workers in 2015 did not take all of their paid vacation and holiday leave. A large percentage of this leave is lost.  It cannot be rolled-over into the next year or paid out. A total of 658 million vacation days, or an average of 2 vacation days per worker was lost in 2015. The reasons most often given for not taking time off was worry that there would be a mountain of work to return to (40%), concern that no one else could do the job (35%), not being able to afford a vacation (33%), feeling it was harder to take time away when you have or are moving up in the company (33%), and not wanting to seem replaceable (22%).  Since 2000, more American workers are willing to work for free rather than take the time that is allowed to them. A lack of support from their boss and even their colleagues to take a vacation is often a driving force in deciding to forgo time off.  In fact, 80% of the respondents to the survey above said they would take time away if they felt they had support from their boss.  Two-thirds reported that they hear nothing, mixed messages, or discouraging remarks about taking their time off.  Almost a third (31%) feel they should contact their workplace, even while on vacation.

The benefits of taking time away from work

Several studies have noted the benefits of taking time away from work.  It reduces job stress burnout (Nimrod, Kleiber, & Berdychevesky, 2012), improves both mental health (Qian, Yarnal, & Almeida, 2013) and physical health (Stern & Konno, 2009), especially if that leisure time also includes moderate physical activity (Lee et al., 2015). Leisure activities can also improve productivity and job satisfaction (Kühnel & Sonnentag, 2011) and help adults deal with balancing family and work obligations (Lee, et al., 2015).

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16.2 Work and Careers in Adulthood

Learning objectives.

• Describe work-related issues in midlife
• Explain the role of volunteering in well-being in later adulthood
• Describe the process of retirement

Work and Careers in Middle Adulthood

Climate in the workplace for middle-aged adults.

A number of studies have found that job satisfaction tends to peak in middle adulthood (Besen et al., 2013; Easterlin, 2006). This satisfaction stems not only from higher wages, but also often from greater involvement in decisions that affect the workplace as middle aged adults move up from worker to supervisor or manager. Job satisfaction is also influenced by being able to do the job well, and after years of experience at a job many people are more effective and productive. Another reason for this peak in job satisfaction is that at midlife many adults lower their expectations and goals (Tangri et al., 2003). Middle-aged employees may realize that they have arrived at the highest level they are likely to reach in their career. This satisfaction at work translates into lower absenteeism, greater productivity, and less job hopping in comparison to younger adults (Easterlin, 2006).

However, not all middle-aged adults are happy in the workplace. Women may find themselves bumping up against the glass ceiling. This may explain why females employed at large corporations are twice as likely to quit their jobs as are men (Barreto et al., 2009). Another problem older workers may encounter is job burnout , defined as unsuccessfully managed workplace stress (World Health Organization, 2019). Burnout consists of:

• Feelings of energy depletion or exhaustion
• Increased mental distance from one’s job, or feelings of job negativism or cynicism
• Reduced feelings of professional effectiveness or efficacy

American workers may experience burnout more often than workers in many other developed nations, because most developed nations guarantee by law a set number of paid vacation days (International Labour Organization, ILO, 2011), whereas the United States does not (U.S. Department of Labor, 2016).

In addition, in comparision to workers in many other developed nations, American workers work more hours per year (Organisation for Economic Cooperation and Development, OECD, 2016). Not all employees in the US are covered under overtime pay laws (U.S. Department of Labor, 2016). This is important when you considered that the 40-hour work week is a myth for most Americans. Only 4 in 10 U.S. workers work the typical 40-hour work week. The average work week for many is almost a full day longer (47 hours), with 39% working 50 or more hours per week (Saad, 2014). As can be seen in Figure 16.3, Americans work more hours than most European nations, especially western and northern Europe, although they work fewer hours than workers in other nations, especially Mexico.

This Ted Talk discusses how working-class people can organize and own the businesses they work for, making decisions for themselves and enjoying the fruits of their labor.

You can view the transcript for “When Workers Own Companies, the Economy is More Resilient” here (opens in new window)

Challenges in the Workplace for Middle-aged Adults

In recent years middle aged adults have been challenged by economic downturns, starting in 2001, and again in 2008 and 2020. During the recession of 2008, fifty-five percent of adults reported some problems in the workplace, such as fewer hours, pay-cuts, having to switch to part-time, etc. (Pew Research Center, 2010a). While young adults took the biggest hit in terms of levels of unemployment, middle-aged adults also saw their overall financial resources suffer as their retirement nest eggs disappeared and house values shrank, while foreclosures increased (Pew Research Center, 2010b). Not surprisingly, this age group, especially those age 50-64, reported that the recession hit them worse than did other age groups.

Middle-aged adults who find themselves unemployed are likely to remain so longer than those in early adulthood (U.S. Government Accountability Office, 2012). Agism is a common complaint in the workplace. For example, in the eyes of employers, it may seem more cost effective to hire a young adult, despite their limited experience, as they would be starting out at lower levels on the pay scale. In addition, hiring someone who is 25 and has many years of work ahead of them versus someone who is 55 and will likely retire in 10 years may also be part of the decision to hire a younger worker (Lachman, 2004).  It may surprise employers to learn that older workers typically stay on the job longer, as younger workers are more geographically mobile and more likely to switch jobs as more attractive opportunities appear. Older adults also demonstrate lower rates of absenteeism and greater investment in their work. American workers are also competing with global markets and changes in technology. Those who are able to keep up with all these changes or are willing to uproot and move around the country or even the world have a better chance of finding work. The decision to move may be easier for people who are younger and have fewer obligations to others.

This Ted Talk discusses ways to cultivate inclusion and encourage diversity in the workplace.

You can view the transcript for “How to Get Serious About Diversity and Inclusion in the Workplace” here (opens in new window)

Work, Volunteering, and Retirement in Late Adulthood

Productivity in work.

Some older people continue to be productive in work. Mandatory retirement is now illegal in the United States. However, many do choose retirement by age 65. Most people leave work by choice, and the primary factors that influence decisions about when to retire are health status, finances, and satisfaction at work. Those who do leave by choice adjust to retirement more easily. Chances are, they have prepared for a smoother transition by gradually giving more attention to an avocation or interest as they approach retirement. And they are more likely to be financially ready to retire. Those who must leave abruptly for health reasons or because of layoffs or downsizing have a more difficult time adjusting to their new circumstances. Men, especially, can find unexpected retirement difficult.

Women may feel less of an identify loss after retirement because much of their identity may have come from family roles as well. At the same time, however, women tend to have poorer retirement funds accumulated from work and if they take their retirement funds in a lump sum (be that from their own or from a deceased husband’s funds), are more at risk of outliving those funds. Because they will on average live longer, women need better financial planning in retirement. Nearly nine percent of adults over 75 were in the labor force in 2020, and this percentage is expected to increase to 11.7% in 2030 (Bureau of Labor Statistics, 2021). Many adults 65 and older continue to work either full-time or part-time either for income or pleasure or both. In 2003, 39% of full-time workers over 55 were women over the age of 70; 53% were men over 70. This increase in numbers of older adults is likely to mean that more will continue to part of the workforce in years to come (He, et al., 2005).

Volunteering: Face-to-face and Virtually

About 40% of older adults are involved in some type of structured, face-to-face, volunteer work. But many older adults, about 60%, engage in a sort of informal type of volunteerism, helping out neighbors or friends rather than working in an organization (Berger, 2005). They may help a friend by taking them somewhere or shopping for them, etc. Some do participate in organized volunteer programs but interestingly enough, those who do tend to work part-time as well. Those who retire and do not work are less likely to feel that they have a contribution to make. (It’s as if when one gets used to staying at home, one’s confidence to go out into the world diminishes.) And those who have recently retired are more likely to volunteer than those over 75 years of age. New opportunities exist for older adults to serve as virtual volunteers by dialoguing online with others from around their world and sharing their support, interests, and expertise. According to an article from the American Association of Retired Persons (AARP), virtual volunteerism has increased from 3,000 participants in 1998 to over 40,000 in 2005. These volunteer opportunities range from helping teens with their writing to communicating with ‘neighbors’ in villages in developing countries. Virtual volunteering is available to those who cannot engage in face-to-face interactions and opens up a new world of possibilities and ways to connect, maintain identity, and be productive (Uscher, 2006).

Transitioning into Retirement

For most Americans, retirement is a process and not a one-time event (Quinn & Cahill, 2016). Sixty percent of workers transition straight to bridge jobs, which are often part-time, and occur between a career and full retirement. About 15% of workers get another job after being fully retired. This may be due to not having adequate finances after retirement or not enjoying their retirement. Some of these jobs may be in encore careers, or work in a different field from the one in which they retired. Approximately 10% of workers begin phasing into retirement by reducing their hours. However, not all employers will allow this due to pension regulations.

Retirement age changes

Looking at retirement data, the average age of retirement declined from more than 70 in 1910 to age 63 in the early 1980s. However, this trend has reversed and the current average age is now 65. Additionally, 18.5% of those over the age of 65 continue to work (US Department of Health and Human Services, 2012) compared with only 12% in 1990 (U. S. Government Accountability Office, 2011). With individuals living longer, once retired the average amount of time a retired worker collects social security is approximately 17-18 years (James et al., 2016).

When to retire

Laws often influence when someone decides to retire. In 1986 the Age Discrimination in Employment Act (ADEA) was amended, and mandatory retirement was eliminated for most workers (Erber & Szuchman, 2015). Pilots, air traffic controllers, federal law enforcement, national park rangers, and fire fighters continue to have enforced retirement ages. Consequently, for most workers they can continue to work if they choose and are able. Social security benefits also play a role. For those born before 1938, they can receive full social security benefits at age 65. For those born between 1943 and 1954, they must wait until age 66 for full benefits, and for those born after 1959 they must wait until age 67 (Social Security Administration, 2016). Extra months are added to those born in years between. For example, if born in 1957, the person must wait until 66 years and 6 months. The longer one waits to receive social security, the more money will be paid out. Those retiring at age 62, will only receive 75% of their monthly benefits. Medicare health insurance is another entitlement that is not available until one is aged 65.

Delayed Retirement

Older adults primarily choose to delay retirement due to economic reasons (Erber & Szchman, 2015). Financially, continuing to work provides not only added income, but also does not dip into retirement savings which may not be sufficient. Historically, there have been three parts to retirement income; that is, social security, a pension plan, and individual savings (Quinn & Cahill, 2016). With the 2008 recession, pension plans lost value for most workers. Consequently, many older workers have had to work later in life to compensate for absent or minimal pension plans and personal savings. Social security was never intended to replace full income, and the benefits provided may not cover all the expenses, so elders continue to work. Unfortunately, many older individuals are unable to secure later employment, and those especially vulnerable include persons with disabilities, single women, the oldestold, and individuals with intermittent work histories. Some older adults delay retirement for psychological reasons, such as health benefits and social contacts. Recent research indicates that delaying retirement has been associated with helping one live longer. When looking at both healthy and unhealthy retirees, a one-year delay in retiring was associated with a decreased risk of death from all causes (Wu et al., 2016). When individuals are forced to retire due to health concerns or downsizing, they are more likely to have negative physical and psychological consequences (Erber & Szuchman, 2015).

Retirement Stages

Atchley (1994) identified several phases that individuals ago through when they retire:

• Remote pre-retirement phase includes fantasizing about what one wants to do in retirement
• Immediate pre-retirement phase when concrete plans are established
• Actual retirement
• Honeymoon phase when retirees travel and participate in activities they could not do while working
• Disenchantment phase when retirees experience an emotional let-down
• Reorientation phase when the retirees attempt to adjust to retirement by making less hectic plans and getting into a regular routine

Not everyone goes through every stage, but this model demonstrates that retirement is a process.

Post-Retirement

Those who look most forward to retirement and have plans are those who anticipate adequate income (Erber & Szuchman, 2015). This is especially true for males who have worked consistently and have a pension and/or adequate savings. Once retired, staying active and socially engaged is important. Volunteering, caregiving and informal helping can keep seniors engaged. Kaskie et al. (2008) found that 70% of retirees who are not involved in productive activities spent most of their time watching TV, which is correlated with negative affect. In contrast, being productive improves well-being.

Atchley, R. C. (1994). Social forces and aging (7th ed.). Wadsworth

Barreto, M., Ryan, M. K., & Schmitt, M. T. (2009).  The glass ceiling in the 21 st century: Understanding the barriers to gender equality . Washington, DC: American Psychological Association.

Berger, K. S. (2005). The developing person through the life span (6th ed.). Worth.

Besen, E., Matz-Costa, C., Brown, M., Smyer, M. A., & Pitt-Catsouphers, M. (2013). Job characteristics, core self-evaluations, and job satisfaction.  International Journal of Aging & Human Development, 76(4) , 269-295.

Bureau of Labor Statistics, U.S. Department of Labor,  The Economics Daily , Number of people 75 and older in the labor force is expected to grow 96.5 percent by 2030 at  https://www.bls.gov/opub/ted/2021/number-of-people-75-and-older-in-the-labor-force-is-expected-to-grow-96-5-percent-by-2030.htm  (visited  July 20, 2023 ).

Easterlin, R. A. (2006). Life cycle happiness and its sources: Intersections of psychology, economics, and demography.  Journal of Economic Psychology, 27 , 463-482.

Erber, J. T., & Szuchman, L. T. (2015). Great myths of aging.   John Wiley & Sons.

He, W., Sengupta, M., Velkoff, V., & DeBarros, K. (2005.).  U. S. Census Bureau, Current Popluation Reports, P23-209, 65+ in the United States: 2005  (United States, U. S. Census Bureau). Retrieved from http://www.census.gov/prod/1/pop/p23- 190/p23-190.html

International Labour Organization. (2011).  Global Employment Trends: 2011.  Retrieved from  http://www.ilo.org/wcmsp5/groups/public/@dgreports/@dcomm/@publ/documents/publication/wcms_150440.pdf

James, J. B., Matz-Costa, C., & Smyer, M. A. (2016). Retirement security: It’s not just about the money. American Psychologist, 71 (4), 334-344.

Kaskie, B., Imhof, S., Cavanaugh, J., & Culp, K. (2008). Civic engagement as a retirement role for aging Americans. The Gerontologist, 48 , 368-377.

Lachman, M. E. (2004). Development in midlife.  Annual Review of Psychology ,  55 (1), 305-331.

Organisation for Economic Cooperation and Development. (2016).  Average annual hours actually worked per worker.  OECD Stat. Retrieved from  http://stats.oecd.org/Index.aspx?DataSetCode=ANHRS

Pew Research Center. (2010a).  How the great recession has changed life in America . Retrieved from http://www.pewsocialtrends.org/2010/06/30/how-the-great-recession-has-changed-life-in-america/

Pew Research Center. (2010b).  Section 5: Generations and the great recession.  Retrieved from  http://www.people-press.org/2011/11/03/section-5-generations-and-the-great-recession/

Quinn, J. F., & Cahill, K. E. (2016). The new world of retirement income security in America. American Psychologist, 71 (4), 321-333.

Saad, L. (2014). The 40 hour work week is actually longer – by 7 hours.  Gallop . Retrieved from http://www.gallup.com/poll/175286/hour-workweek-actually-longer-seven-hours.aspx

Social Security Administration. (2016). Retirement planner: Benefits by year of birth. Retrieved from https://www.ssa.gov/planners/retire/agereduction.html

Tangri, S., Thomas, V., & Mednick, M. (2003). Prediction of satisfaction among college-educated African American women.  Journal of Adult Development, 10 , 113-125.

United States Census Bureau. (2018, April 10). The Nation’s Older Population Is Still Growing, Census Bureau Reports. Retrieved from https://www.census.gov/newsroom/press-releases/2017/ cb17-100.html

United States Census Bureau. (2018, August 03). Newsroom. Retrieved from https://www.census.gov/newsroom/facts-for-features/2017/cb17-ff08.html

U.S. Department of Labor (2016).  Vacation Leave . Retrieved from  https://www.dol.gov/general/topic/workhours/vacation_leave

United States Department of Health and Human Services. (2012). A profile of older Americans: 2012. Retrieved from http://www.aoa.gov/Aging_Statistics/Profile/2012/docs/2012profile.pdf

United States Government Accountability Office. (2011). Income security: Older adults and the 2007-2009 recession. Washington, DC: Author. United States, National Center for Health Statistics. (2002). National Vital Statistics Report, 50(16). Retrieved May 7, 2011, from http://www.cdc.gov/nchs/data/dvs/LCWK1_2000.pdf

U.S. Government Accountability Office. (2012). Unemployed older workers: Many experience challenges regaining employment and face reduced retirement security. Retrieved from  http://www.gao.gov/products/GAO-12-445

Uscher, J. (2006, January). How to make a world of difference-without leaving home. AARP The Magazine – Feel Great. Save Money. Have Fun. Retrieved May 07, 2011, from  http://www.aarpmagazine.org/lifestyl…unteering.html

World Health Organization. (2019).  Burn-out an “occupational phenomenon” . Retrieved from https://www.who.int/standards/classifications/frequently-asked-questions/burn-out-an-occupational-phenomenon (visited February 2, 2024).

Wu, C., Odden, M. C., Fisher, G. G., & Stawski, R. S. (2016). Association of retirement age with mortality: a population-based longitudinal study among older adults in the USA. Journal of Epidemiology and Community Health. doi:10.1136/jech2015-207097

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Chapter 8: Middle Adulthood

Work at midlife.

Who is the U.S. workforce? The civilian, non-institutionalized workforce; that is the population of those aged 16 and older, who are employed has steadily declined since it reached its peak in the late 1990s, when 67% of the civilian workforce population was employed. In 2012 the rate had dropped to 64% and by 2022 it is projected to decline to 62%. The U.S. population is expected to grow more slowly based on census projections for the next few years. Those new entrants to the labor force, adults age 16 to 24, are the only population of adults that will shrink in size over the next few years by nearly half a percent, while those age 55 and up will grow by 2.3% over current rates, and those age 65 to 74 will grow by nearly 4% (Monthly Labor Review (MLR), 2013). In 1992, 26% of the population was 55+, by 2022 it is projected to be 38%. Table 8.8 shows the rates of employment by age. In 2002, baby boomers were between the ages of 38 to 56, the prime employment group. In 2012, the youngest baby boomers were 48 and the oldest had just retired (age 66). These changes might explain some of the steady decline in work participation as this large population cohort ages out of the workforce.

In 2012, 53% of the workforce was male. For both genders and for most age groups the rate of participation in the labor force has declined from 2002 to 2012, and it is projected to decline further by 2022. The exception is among the older middle-age groups (the baby boomers), and especially for women 55 and older.

Table 8.8 Percentage of the non-institutionalized civilian workforce employed by gender & age.

*Projected rates of employment (adapted from Monthly Labor Review, 2013).

Hispanic males have the highest rate of participation in the labor force. In 2012, 76% of Hispanic males, compared with 71% of White, 72% of Asian, and 64% of Black men ages 16 or older were employed. Among women, Black women were more likely to be participating in the workforce (58%) compared with almost 57% of Hispanic and Asian, and 55% of White females. The rates for all racial and ethnic groups are expected to decline by 2022 (MLR, 2013).

Climate in the Workplace for Middle-aged Adults: A number of studies have found that job satisfaction tends to peak in middle adulthood (Besen, Matz-Costa, Brown, Smyer, & Pitt- Catsouphers, 2013; Easterlin, 2006). This satisfaction stems from not only higher wages, but often greater involvement in decisions that affect the workplace as they move from worker to supervisor or manager. Job satisfaction is also influenced by being able to do the job well, and after years of experience at a job many people are more effective and productive. Another reason for this peak in job satisfaction is that at midlife many adults lower their expectations and goals (Tangri, Thomas, & Mednick, 2003). Middle-aged employees may realize they have reached the highest they are likely to in their career. This satisfaction at work translates into lower absenteeism, greater productivity, and less job hopping in comparison to younger adults (Easterlin, 2006).

However, not all middle-aged adults are happy in the work place. Women may find themselves up against the glass ceiling , organizational discrimination in the workplace that limits the career advancement of women . This may explain why females employed at large corporations are twice as likely to quit their jobs as are men (Barreto, Ryan, & Schmitt, 2009). Another problem older workers may encounter is job burnout , becoming disillusioned and frustrated at work . American workers may experience more burnout than do workers in many other developed nations, because most developed nations guarantee by law a set number of paid vacation days (International Labour Organization, ILO, 2011), the United States does not (U.S. Department of Labor, 2016).

Figure 8.19 Average Annual Hours Actually Worked per Worker

Not all employees are covered under overtime pay laws (U.S. Department of Labor, 2016). This is important when you considered that the 40-hour work week is a myth for most Americans. Only 4 in 10 U.S. workers work the typical 40-hour work week. The average work week for many is almost a full day longer (47 hours), with 39% working 50 or more hours per week (Saad, 2014). In comparision to workers in many other developed nations, American workers work more hours per year (Organisation for Economic Cooperation and Development, OECD, 2016). As can be seen in Figure 8.19, Americans work more hours than most European nations, especially western and northern Europe, although they work less hours than workers in other nations, especially Mexico.

Challenges in the Workplace for Middle- aged Adults: In recent years middle aged adults have been challenged by economic downturns, starting in 2001, and again in 2008. Fifty-five percent of adults reported some problems in the workplace, such as fewer hours, pay-cuts, having to switch to part-time, etc., during the most recent economic recession (see Figure 8.20, Pew Research Center, 2010a). While young adults took the biggest hit in terms of levels of unemployment, middle-aged adults also saw their overall financial resources suffer as their retirement nest eggs disappeared and house values shrank, while foreclosures increased (Pew Research Center, 2010b).

Figure 8.20

Not surprisingly this age group reported that the recession hit them worse than did other age groups, especially those age 50-64. Middle aged adults who find themselves unemployed are likely to remain unemployed longer than those in early adulthood (U.S. Government Accountability Office, 2012). In the eyes of employers, it may be more cost effective to hire a young adult, despite their limited experience, as they would be starting out at lower levels of the pay scale. In addition, hiring someone who is 25 and has many years of work ahead of them versus someone who is 55 and will likely retire in 10 years may also be part of the decision to hire a younger worker (Lachman, 2004). American workers are also competing with global markets and changes in technology. Those who are able to keep up with all these changes, or are willing to uproot and move around the country or even the world have a better chance of finding work. The decision to move may be easier for people who are younger and have fewer obligations to others.

• Authored by : Martha Lally and Suzanne Valentine-French. Provided by : College of Lake County Foundation. Located at : http://dept.clcillinois.edu/psy/LifespanDevelopment.pdf . License : CC BY-NC-SA: Attribution-NonCommercial-ShareAlike

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How our longitudinal employment patterns might shape our health as we approach middle adulthood—US NLSY79 cohort

Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Resources, Software, Validation, Visualization, Writing – original draft, Writing – review & editing

* E-mail: [email protected]

Affiliation Silver School of Social Work, New York University, New York, NY, United States of America

• Wen-Jui Han

• Published: April 3, 2024
• https://doi.org/10.1371/journal.pone.0300245
• Reader Comments

Recent labor market transformations brought on by digital and technological advances, together with the rise of the service economy since the 1980s, have subjected more workers to precarious conditions, such as irregular work hours and low or unpredictable wages, threatening their economic well-being and health. This study advances our understanding of the critical role employment plays in our health by examining how employment patterns throughout our working lives, based on work schedules, may shape our health at age 50, paying particular attention to the moderating role of social position. The National Longitudinal Survey of Youth-1979 (NLSY79), which has collected 30+ years of longitudinal information, was used to examine how employment patterns starting at ages 22 (n ≈ 7,336) might be associated with sleep hours and quality, physical and mental functions, and the likelihood of reporting poor health and depressive symptoms at age 50. Sequence analysis found five dominant employment patterns between ages 22 and 49: “mostly not working” (10%), “early standard hours before transitioning into mostly variable hours” (12%), “early standard hours before transitioning into volatile schedules” (early ST-volatile, 17%), “mostly standard hours with some variable hours” (35%), and “stable standard hours” (26%). The multiple regression analyses indicate that having the “early ST-volatile” schedule pattern between ages 22 and 49 was consistently, significantly associated with the poorest health, including the fewest hours of sleep per day, the lowest sleep quality, the lowest physical and mental functions, and the highest likelihood of reporting poor health and depressive symptoms at age 50. In addition, social position plays a significant role in these adverse health consequences. For example, whereas non-Hispanic White women reported the most hours of sleep and non-Hispanic Black men reported the fewest, the opposite was true for sleep quality. In addition, non-Hispanic Black men with less than a high school education had the highest likelihood of reporting poor health at age 50 if they engaged in an employment pattern of “early ST-volatile” between ages 22 and 49. In comparison, non-Hispanic White men with a college degree or above education had the lowest likelihood of reporting poor health if they engaged in an employment pattern of stable standard hours. This analysis underscores the critical role of employment patterns in shaping our daily routines, which matter to sleep and physical and mental health as we approach middle adulthood. Notably, the groups with relatively disadvantaged social positions are also likely to be subject to nonstandard work schedules, including non-Hispanic Blacks and people with low education; hence, they were more likely than others to shoulder the harmful links between nonstandard work schedules and sleep and health, worsening their probability of maintaining and nurturing their health as they approach middle adulthood.

Citation: Han W-J (2024) How our longitudinal employment patterns might shape our health as we approach middle adulthood—US NLSY79 cohort. PLoS ONE 19(4): e0300245. https://doi.org/10.1371/journal.pone.0300245

Editor: Emiko Usui, Hitosubashi University, JAPAN

Received: April 6, 2023; Accepted: February 23, 2024; Published: April 3, 2024

Copyright: © 2024 Wen-Jui Han. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: The data set used for this study, NLSY79, is publicly available at https://www.bls.gov/nls/nlsy79/using-and-understanding-data/home.htm .

Funding: The author received no specific funding for this work.

Competing interests: The author has declared that no competing interests exist.

Introduction

Since the 1980s, the rise of the technological and digital age has transformed how people around the globe live and work, carrying significant consequences for our overall well-being [ 1 ]. For instance, innovations in medicine and public health have increased life expectancy in the United States from 48 years in 1900 to 76 years in 2000 [ 2 ]. However, since the 1990s, health improvements might have been blunted by the increased prevalence of precarious employment [ 3 ]. Precarious jobs are defined as those with poor working conditions and weak power relations, including low wages, unpredictable or unstable hours, few or no benefits, and weak or no bargaining power. One of the essential indicators of a precarious job is working outside of traditional 9:00 to 5:00 hours, such as during early mornings, evenings, or nights, or having irregular hours (e.g., rotating, split, or unpredictable hours). Such work patterns are sometimes called nonstandard work schedules [ 4 ] or shiftwork [ 5 ]. Prior research has found that these jobs have physically exhausted and emotionally drained U.S. workers [ 3 ]. Recently, the COVID-19 crisis has heightened existing inequalities, as people engaging in shiftwork (ironically labeled “essential” work) experience greater exposure to infection and higher death tolls [ 6 ].

Approximately one-third of the workforce globally has a work schedule considered nonstandard or shiftwork [ 7 ]. Dr. Harriet Presser [ 8 ] was among the first to extensively document this labor force transformation. Her seminal works provide insights into not only the prevalence of such work schedules but also their potential implications for the well-being of individuals and their families [ 4 , 8 ]. Subsequent studies have demonstrated that nonstandard work schedules dictate when we can sleep, with implications for our sleep quality and overall physical and mental health [ 5 ]. Studies using samples from different occupations (e.g., nurses, truck drivers) [ 9 , 10 ] and countries (e.g., Canada, European countries, Singapore, South Korea, and the United States) [ 1 , 5 , 11 – 13 ] have consistently documented significantly worse health outcomes, including shorter sleep and a lower quality of sleep, among those with nonstandard work schedules compared to their counterparts. A growing line of scholarship has also documented well-established adverse associations between nonstandard work schedules, particularly night shifts, and a higher likelihood of poor physical health (e.g., cardiovascular disease) and mental health (e.g., anxiety, depression) [ 1 , 5 , 8 ].

Missing from the extant scholarship are longer term longitudinal studies using a life-course perspective with sequence analysis to examine how work schedule patterns might be associated with our sleep and health as we approach middle adulthood [ 14 ]. This study extends our knowledge by using the National Longitudinal Study of Youth-1979, a nationally representative sample of about 7,000 people in the U.S. over 30 years, from ages 22 to 50. I focus on work schedule patterns in the United States throughout individuals’ working lives to underscore the critical role of employment in our daily experience and thus our health. This study also fills a literature gap by paying attention to how such a link might differ by social position, as reflected by race-ethnicity, gender, and education. This study, therefore, provides new insights into factors shaping our well-being on a global scale given that nonstandard work schedules are increasingly becoming a global phenomenon [ 15 ].

Life-course approach using a cumulative advantage and disadvantage (CAD) lens

This study builds on the life-course perspective [ 16 , 17 ] to conceptualize the association between employment throughout adulthood and sleep and health at age 50. Specifically, firstly, drawing on a fundamental principle of the life-course perspective—that human development and aging are lifelong processes, with the appreciation that the past shapes the future—this study uses longitudinal data to conceptualize and empirically examine how work patterns during one’s working life between ages 22 and 49 may shape sleep and physical and mental health at age 50. Importantly, our health is shaped by daily events occurring to and around us but may not manifest their effects until years later. Hence, studying working lives over substantial periods allows one to identify and investigate long-term associations between changes in our employment concerning work schedules and our health. For example, we can never be certain that no association between employment patterns and our sleep and health exists merely based on short-term null effects. Building upon this principle, this study answers the following research question: How might lifetime work trajectories shape future health outcomes? Secondly, drawing on the principle of timing—that the health consequences of event transitions and patterns vary according to their timing in a person’s life—this study uses longitudinal data spanning more than 30 years of an individual’s life to understand how transitions between work schedules over time may shape sleep and health at age 50. By examining work trajectories, this study, thus, pays attention to the paths of changes in individuals’ employment patterns and transitions that might shape their health, taking a long view of the life course. Building upon this principle, this study also answers the following research question: How might transitions between schedules (for example, daytime hours to evening or night hours) be associated with our sleep (hours and quality) and our future physical and mental health? Overall, examining the constraints imposed by employment patterns, particularly work schedules, with a life-course lens allows us to understand how favorable work conditions from early adulthood to old age contribute to better health in an individual’s lifetime, with significant implications for the well-being of future generations.

Furthermore, I pay special attention to how the links between employment patterns throughout one’s working life and sleep health at age 50 might vary by social position, identified in this study through race-ethnicity, gender, and education. I adopt the cumulative advantage and disadvantage (CAD) framework [ 18 , 19 ], which assumes our social positions (e.g., race, ethnicity, gender) interact with macro systems and institutions (e.g., employment) to shape our opportunities and constraints throughout our lifetime, influencing our health by generating increasing disparities in resources between those who have and those who have not [ 16 , 18 , 19 ]. Importantly, some work schedules (e.g., daytime hours) are more likely than others (e.g., irregular hours) to benefit our sleep and health [ 1 , 5 ]. By considering social position in this investigation, I shed light on the prevalent health disparities among different social position groups that might partly result from work schedule patterns over time.

Health consequences of work schedules

Since the late 1990s, studies using both US and non-US samples have examined the links between work schedules and social, psychological, and physical well-being of individuals [ 1 , 8 , 20 ] and family members, including children [ 4 , 21 , 22 ]. These studies have largely found weak to moderate adverse associations between working nonstandard hours and the well-being of workers and their families, particularly when such a schedule was chosen involuntarily (e.g., a job requirement). One of the immediate adverse health consequences is a decline in the amount and quality of sleep for workers with nonstandard hours because these schedules (e.g., night shifts) counter our circadian rhythm, which is critical for maintaining and sustaining good health [ 5 ]. Health issues stemming from severe sleep deprivation and low sleep quality due to nonstandard work schedules have been labeled Shift Work Sleep Disorder (SWSD) by academics and experts in the medical field [ 5 ]. People with SWSD tend to report the following symptoms: trouble sleeping, excessive sleepiness, and tiredness. These symptoms compromise one’s overall physical and mental functions, leading to poor general health [ 5 ]. Regarding other health consequences, one study showed that 38% of people working an 8-hour night shift had a BMI ≥30 versus 26% of people working an 8-hour day shift ( p < .05) [ 23 ]. Another study found that people with nonstandard work schedules are also 42% more likely to suffer from depressive symptoms than those with standard schedules [ 24 ].

Our understanding of the links between work schedules and sleep and health has also been refined through increasingly sophisticated data, including from small cross-sectional samples [ 12 , 25 ], nationally representative samples [ 1 , 26 ], and panel data [ 27 , 28 ]. For example, using two-year longitudinal data on approximately 1,500 Norweigan nurses, Waage and colleagues found that nurses working night hours the prior year were more likely to report acute sleepiness or insomnia related to shiftwork in the current year [ 27 ]. Importantly, those who stopped working night shifts were more likely to report a reduction in excessive sleepiness and less insomnia. A recent study using panel data from 2002 to 2018 in Germany found that individuals who perceived their work as involving nonstandard work schedules, high job insecurity, and low social rights were more likely to have poorer physical and mental health than their counterparts, and chronic exposure to or transitioning into such work might predict poorer health than otherwise [ 28 ]. This study builds on this emerging literature to advance our knowledge by using sequence analysis to document the changes in work trajectories and then examining how those changes/trajectories might be associated with sleep and health.

The importance of social position.

Another line of studies has shown that social position shapes our likelihood of having jobs requiring nonstandard work schedules [ 3 , 8 ]. For example, Presser extensively documented that in the United States, young workers, Blacks, and people with a high school or lower education are particularly subject to working nonstandard schedules [ 8 ]. In addition, whereas men are more likely than women to have nonstandard schedules, the distribution can vary greatly by occupation. Nurses are a prime example of a female-dominated occupation requiring nonstandard work schedules, particularly night shifts. A substantial line of scholarship has documented that, compared to their counterparts, female workers with nonstandard work schedules, particularly night shifts, have substantially higher odds of experiencing sleep disturbance and fatigue [ 26 ], stroke [ 29 ], and breast cancer [ 30 ]. In addition, studies have shown that both shift work and being an African American independently increase the odds of having high blood pressure [ 31 ]. A growing body of evidence has also found that people of racial-ethnic minority groups are more likely to get insufficient or low-quality sleep. Adverse sleep issues, such as insomnia, may also help account for increasing health disparities, such as higher rates of cardiovascular disease among racial-ethnic minority groups [ 32 ]. The higher share of African Americans with jobs requiring nonstandard schedules than their counterparts does not help and may indeed further intensify the high prevalence of sleep issues among people of color.

Hence, employment carries long-lasting implications for the social, psychological, physical, and economic well-being of workers and their families, with significant implications for inequality across generations, a central CAD tenet. The rise in precarious jobs, particularly among those in relatively disadvantaged social positions, motivates the need to investigate whether engaging in nonstandard work schedules over time may translate into long-term health consequences. A previous study [ 33 ] using the same data as the current analysis found that individuals in various social positions such as men, Blacks, and people with low educational attainment (e.g., high school or less) were more likely to have ever worked nonstandard hours between ages 18 and 39 than were their corresponding counterparts. Importantly, compared to men, women were more likely to have either never or always had nonstandard work schedules by age 39. This finding reflects the reality that women-dominated occupations often require nonstandard hours (e.g., nurses, home health aides).

The present study

The field has established a decent set of scholarship on the associations between work schedules and sleep and health, including the consequences for family and child well-being. The implication is thus clear. People in the U.S. and around the world are increasingly subject to nonstandard work schedules, creating work-induced health disparities [ 1 , 3 , 4 , 12 ]. However, we have yet to understand how employment patterns over the life-course may shape our health as we approach middle adulthood. Furthermore, a long line of extant research has shown how some social positions may act as vulnerabilities, putting people on a disadvantaged trajectory throughout their lifetime [ 3 , 17 , 20 ]. Hence, drawing upon the CAD framework, this study pays attention to three markers representing social position—race-ethnicity, gender, and education—to highlight how the intersectionality between employment and social position may accumulate advantages and disadvantages throughout a lifetime, manifested in our sleep behaviors and general health. By using a nationally representative sample of youths aged 14–22 in 1979 in the United States, this analysis addresses this evidence gap by building upon the life-course and CAD lens to answer the following research questions: how might lifetime work trajectories (between ages 22 and 49) be associated with health outcomes as we approach middle adulthood (at age 50), and how might such an association differ due to the intersectionality between work and social position? Notably, the longitudinal data used in this analysis allow researchers to track employment patterns during a period when working nonstandard hours was on the rise [ 7 , 12 ].

Materials and methods

This study used the National Longitudinal Survey of Youth-1979 (NLSY79), which comprises a nationally representative sample of Americans between the ages of 14 and 22 in 1979 (N = 12,686). NLSY79 interviewed respondents every year until 1994 and biennially thereafter. The current analysis excludes two discontinued oversamples: non-Black non-Hispanic disadvantaged youths, discontinued in 1990 (n = 1,643), and military youth, discontinued in 1984 (n = 1,280). A total of 9,763 respondents served as the starting point after excluding these two discontinued oversamples. The response rates of NLSY79 have been remarkably high, ranging from 96% in the early survey years to about 77% in recent years [ 34 , 35 ]. The NYLS79 is well suited to this study due to its rich data on longitudinal sociodemographic characteristics (e.g., education, marriage, number of children) and work schedules.

I use outcome measures at age 50 and begin the sample at age 22. I chose age 50 for two primary reasons. First, as this study was built upon a life-course lens, focusing on age 50 allowed me to examine employment patterns over an extended period of time, from ages 22 to 49. Second, NLSY79 collects health outcomes in the health modules at ages 40, 50, and 60. By 2018 (the most updated data as of this analysis), most participants had reached age 50 but only a small proportion (10%) had reached age 60. Therefore, using age 50 meant the sample comprised the majority of the participants. I also had two primary reasons for selecting age 22 as the starting point for the employment patterns. First, NLSY79 did not collect information on ages 14–18 for those who were 19–22 in 1979, the first interview year. Second, more than 30% of the NLSY79 participants were in college between ages 18 and 22. During this period, their jobs, if they had one, were more likely to be temporary or part time [ 33 ]. Therefore, age 22 is a plausible beginning point for establishing a career for many participants, particularly the college graduates in the sample.

Participants

The final analysis excluded participants who were missing information on the sleep outcome at age 50 (n = 2,052) or on employment between ages 22 and 49 (n = 6). Furthermore, approximately 5% of cases (n = 369) were missing information on sociodemographic characteristics (e.g., from < 0.01% on education to about 4% on parental education). The final analyzed samples after these exclusions were 7,336 for the dependent variable of sleep quality, 7,324 for average sleep hours per day over a week, 7,334 for general health status, 7,262 for physical and mental functions, and 7,271 for depression symptoms. Following previous research, missing values for the dependent variables were not imputed to avoid measurement noise [ 36 ]. The pattern of missing values on these dependent variables suggests that the older participants (e.g., 19 or older in 1979) were more likely than the younger participants to have missing values on the dependent variables. This missing pattern suggests a positive selection bias; younger or healthier participants more likely to remain in the longitudinal study. No other significant differences in sociodemographic variables were found between those with and without missing outcome measures.

Hours . As part of the age 50+ health modules, the NLSY79 asked how many hours of sleep the participant typically gets at night on a weekday, and a separate question asked about the weekend. Using both questions, I created a new variable to represent the average number of hours a participant gets per day across a 7-day week. As a robustness check, the analysis was also run using three individual variables as the outcomes: average number of hours of sleep on a weekday, average number of hours of sleep on the weekend, and average number of hours of sleep per day across a 7-day week. The results were similar to those presented here. Note that information about sleep was not collected before the participants turned 50.

Quality . As part of age 50+ health modules, participants were asked how frequently they had experienced the following four issues over the last month: “have trouble falling asleep,” “wake up and have trouble falling back asleep,” “wake up too early and have trouble falling back asleep,” and “feel unrested during the day despite the amount of sleep.” Respondents answered using a 4-point Likert scale ranging from “almost always (4+ times per week)” to “rarely or never (once a month or less).” These four questions are commonly used in studies examining sleep quality or disturbance [ 37 ]. A standardized score with a mean of 0 and a standard deviation of 1 was created from these four questions with excellent reliability (α = 0.84). The higher the score, the better the sleep quality was.

Poor health.

The NLSY79 collects information on general health status by asking participants to assess their general health, ranging from excellent (1) to poor (5). I created a dichotomous variable that received a value of 1 if the participant reported having either “poor” or “fair” health, and 0 otherwise.

SF12 physical and mental health.

The NLSY79 adopted the 12-Item Short-Form Health Survey (SF-12 v1) to rate self-reported mental and physical health. The NLSY79 administered this scale as part of the 50+ health modules to those who had turned 50 since their last interview. These data were collected between the interview years of 2008 and 2016. Specifically, the respondents were asked 12 questions about the past 4 weeks, including whether pain had interfered with normal work, whether their health had limited their moderate activities, and their frequency of feeling downhearted or blue. The possible responses, given the nature of the question, include a 3-point Likert scale (not limited at all, limited a little, limited a lot) and a 5-point Likert scale (ranging from “all the time” to “none of the time”). This study used the global scores representing physical and mental functions created by the NLSY79, following the scoring established by Ware, Kosinski, and Keller [ 38 ]. The SF-12 has been shown to have good reliability (e.g., 0.89) and validity [ 38 ] and can detect active and recent depressive disorders [ 39 ]. NLSY79 standardized the scores to have a mean of 50 and a standard deviation of 10; a score of 50 corresponds to the U.S. average, and a one-point difference is one-tenth of a standard deviation [ 40 ]. Previous research has shown that the NLSY79 sample tends to have a higher-than-average score on SF-12 mental function and just about the average score on SF-12 physical function [ 40 ]. The higher the score, the better the function is.

Depressive symptoms.

As part of the age 50+ health modules, NLSY79 used seven items from the Center for Epidemiologic Studies Depression Scale (CES-D) [ 41 ] to collect data on respondents’ depressive symptoms [ 42 ]. Respondents were asked how they felt during the past week through prompts such as “I felt depressed” and “I felt lonely," with possible responses on a scale of 0 (rarely/none of the time/1 day) to 3 (most/all of the time/5–7 days). The NLSY79 created a total CES-D score (ranging from 0 to 21) by summing the responses of all seven questions. A higher score indicates more depressive symptoms. The scale score was coded as missing if one item was missing. Compared to the original 20-item CES-D, this short form has similar or higher reliability and validity [ 43 ]. Prior studies have found a score of 8 or greater to have acceptable specificity and modest sensitivity with the standard CES-D cutoff score of 16 [ 43 ]; this study thus used this cutoff score to identify individuals with symptoms putting them at clinical risk of depression.

Work schedules.

At every survey year, the NLSY79 asked participants about their work schedules. This study followed NLSY’s definitions and responses to create five work statuses. Specifically, a “standard” work schedule was defined as work beginning at 6 a.m. or later and ending by 6 p.m., “evenings” as work beginning at 2 p.m. or later and ending by midnight, “nights” as work beginning at 9 p.m. or later and ending by 8 a.m., and “variable” if the participant had either split or rotating shift or irregular hours. “Not working” was used when participants answered “not working at any job.” These five work statuses were used in the sequence analysis to arrive at possible clusters describing individuals’ employment patterns and trajectories.

Social position.

This study used three indicators to define social position independent of employment patterns: gender, race-ethnicity, and education. The choice of these three indicators is to avoid reverse causality. For example, low-income status during adulthood tends to be highly associated with working nonstandard hours. However, nonstandard work schedules could lead to low-income status instead of vice versa. In this case, low-income status might be better conceptualized as a mediator instead of a moderator in the association between employment and health. The year 1979 was used as the data point to identify gender as either woman or man (as the reference group). In 1979, separate questions were asked about race and ethnicity. These two pieces of information were used to define four racial-ethnic groups: non-Hispanic White (reference group; Whites hereafter), non-Hispanic Black (Blacks hereafter), Hispanic, and others. Participants’ highest educational degree completed by age 23 was used to determine educational achievement with four dichotomous groups: less than a high school degree (<12 years of schooling), a high school degree (12 years of schooling, reference group), some college (13–15 years of schooling), and college or higher (16+ years of schooling).

Sociodemographic characteristics.

A rich set of sociodemographic characteristics was considered in all analyses to address the potential unobserved heterogeneity between participants and selection bias that might explain the associations between employment patterns and sleep and health [ 1 , 8 ]. These variables include age in 1979; background characteristics at age 14, including not living with both biological parents, parental education (i.e., less than high school, high school as the reference group, some college, or college or higher), and living location (suburban, rural, versus urban); region of residence at age 22 (Northeast, Midwest, West, versus South); any health issues that limited the ability to work by age 22; being a parent by age 22; ever experiencing poverty before age 23; ever receiving welfare before age 23; the number of years living in poverty between ages 22 and 49; the number of years receiving welfare between ages 22 and 49; number of marriages by age 49; number of children by age 49; average weekly working hours between ages 22 and 49; and occupations between ages 22 and 49. I defined poverty as family income at 100% of or under the federal poverty threshold. Welfare receipt was defined as receiving any assistance, including low-income cash transfers (e.g., AFDC or TANF), food assistance (e.g., food stamps or SNAP), or supplemental security income (SSI). Of note, to avoid reverse causality, I did not control for annual wages or income given the high correlation between these two variables and the type of work; instead, education, experiences with poverty and welfare receipt, and occupations were considered as proxies for resources available and accessible to respondents.

I created three dichotomous variables to measure average weekly working hours with a value of 1 and 0 otherwise to categorize participants as having (1) “mostly or only full-time hours” if they worked 35+ hours a week for at least half of the survey years (i.e., proportion of 0.50–0.99) between 22 and 49 (the reference group), (2) “mostly or only part-time hours” if they worked fewer than 35 hours a week for at least half of the survey years between 22 and 49, or (3) “mixed” if the participants worked about an equal share of survey years at full- and part-time hours between 22 and 49. Similarly, data on occupation were collected at each interview between ages 22 and 49. I created five occupational categories: mostly professional/managerial, mostly sales-related, mostly service-related (the reference group), mostly other occupations, and mixed. I used dichotomous variables to classify each participant’s primary occupation between 22 and 49. A person was considered mostly professional/managerial if they worked at least half the survey years between ages 22 and 49 in such an occupation. The “mixed” occupation category comprised participants who worked about an equal share of the survey years in at least two of the five occupation categories between 22 and 49.

Data analysis.

Stata v.15 was used to perform the analyses in two steps. I first used sequence analysis to identify work schedule patterns between ages 22 and 49. I then conducted multiple regression analyses to examine the association between work schedule patterns (found in the sequence analysis) and the following health outcomes: sleep hours and quality, having poor health, SF-12 physical and mental functions, and having depressive symptoms.

When using a life-course perspective and focusing on the principles of lifespan development and timing, a sequence analysis is a well-suited statistical tool to chronologically classify the transitions between work schedule statuses over time [ 44 ]. To document the changes or transitions chronologically, this analysis used each year between the ages of 22 and 49 as the time axis, and the five work schedule statuses as the state or categorical variable tracked over time. I followed two steps to portray the work schedule trajectories over the working years (i.e., sequences) and then cluster the trajectories into groups. First, I calculated the similarity and dissimilarity between sequences using an optimal matching algorithm by setting the “costs” of turning one sequence into another [ 45 , 46 ]. Following the sequence analysis literature, I set the insertion and deletion costs to be 1 and used the Needleman-Wunsch algorithm to calculate the substitution costs based on the transition rates between work schedule categories; when the transition is rare, the substitution cost is higher [ 47 , 48 ]. I conducted additional sensitivity analyses using alternative theoretical-driven substitution (such as 2, 3, or other theoretically driven cost structures) to ensure the cluster solutions are not sensitive to cost-setting decisions [ 49 ]. The results affirm that they are not.

The next step was to cluster similar sequences into a finite number of groups using Ward’s hierarchical fusion algorithm [ 45 ]. The stopping rules based on the Calinski and Harabasz pseudo-F index and the Duda-Hart index, as well as the conceptual meaning of clusters, were used to determine the ideal number of clusters [ 50 ]. Fig 1 presents the five sequence cluster solutions obtained, and S1 Table presents these diagnostic tests.

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In the second step of the analysis, I used ordinary least squares (OLS) models to examine the associations between employment patterns and sleep hours and quality and SF-12 physical and mental functions, and I used logistic regression models to assess the associations between employment patterns and the likelihood of reporting poor health and having depressive symptoms (CES-D score > = 8). I then conducted post-estimations based on each multiple regression model to assess whether the regression estimates for the dependent variables were statistically significantly different between the five employment patterns. Next, I conducted interaction analyses to evaluate whether the associations between employment patterns and sleep and health might vary by social position. I conducted separate analyses by interacting the employment patterns with the following social position markers one at a time: race-ethnicity, gender, and education.

Due to the overwhelming number of combinations of employment patterns and the three social position markers, for brevity and for illustrative purposes, based on the interaction analyses, Figs 2 – 7 plot the predicted estimates of the number of sleep hours, sleep quality, poor health, SF-12 physical function, SF-12 mental function, and depressive symptoms against the work schedule patterns and the joint characteristics of race-ethnicity, gender, and education. The predicted probabilities in Figs 2 – 7 were produced by using the “margins” command in Stata based on the multivariate regression analyses. Of note, results for Hispanics were similar to but weaker than those comparing non-Hispanic Whites and non-Hispanic Blacks. Results for "Other" respondents were insignificant, primarily due to extremely small sample sizes. Therefore, the comparison between racial-ethnic groups in the Results section focuses on the Black–White differences.

Note: ST: standard hours; VH: variable hours; NW: not working. The box plot displays the 95% confidence interval of each predicted estimate.

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Descriptive picture

Table 1 displays all analyzed variables for the total sample (n = 7,336) and by employment cluster patterns between ages 22 and 49. Table 1 also presents the results of bivariate statistical tests to gauge differences between employment patterns in regard to sociodemographic characteristics. The focal independent variable in this analysis is employment patterns between ages 22 and 49. Fig 1 presents the distribution plot of the sequence analysis clusters of employment patterns between ages 22 and 49. About 60% of the NLSY79 participants had employment patterns involving mostly standard hours (ST) throughout their working years: 35% worked "mostly ST with some variable hours (VH)," and 26% worked "stable ST." A decent share of participants (17%) had an employment pattern characterized as working standard hours early in their careers (20s) but transitioning into a variety of work schedules (during their early 30s). This group is labeled "early ST-volatile." Another 12% of respondents had a similar employment pattern of working standard hours during their early working years but switched into mainly variable hours (labeled "early ST-mostly VH"). Finally, About 11% of respondents had an employment pattern characterized as "mostly not working (NW)."

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Table 1 also shows sociodemographic characteristics of the sample. NLSY79 contains slightly more women than men. Approximately half of the participants were non-Hispanic White, with another third identified as non-Hispanic Black, 19% as Hispanic, and about 1% as some other racial group. The majority were U.S.-born. In addition, at age 14, more than 70% of the NLSY79 respondents had parents with a high school degree or less, one-third were not living with both biological parents, and almost 80% lived in urban areas. Nearly 10% of these young adults reported health issues that limited work capacity by age 22. By age 23, for about 20% of these young adults, less than high school was their highest educational attainment, 43% had a high school degree, 23% had some college, and 14% had a college or above education. Roughly 30% of the participants were married at age 22, and about 29% had become parents by age 22. Finally, before age 23, about 44% of the participants had experienced poverty, and about 21% had received welfare assistance.

Furthermore, between ages 22 and 49, participants experienced an average of one marriage and had an average of two children. In addition, participants spent an average of two to three years experiencing poverty and received welfare assistance for an average of over two years. More than three-fourths of the participants mainly worked full-time (i.e., 35 or more hours per week). About a quarter of the participants mostly worked in professional/managerial occupations, more than one-third had primarily service-related occupations, and another 30% had jobs primarily in occupations other than professional/managerial, sales-, or service-related.

Regarding the outcome variables considered in this analysis, the average number of sleep hours per day on a weekday was 6.62 (SD = 1.41) and 7.21 (SD = 1.64) on the weekend; combined, across a 7-day week, participants slept an average of 6.92 hours (SD = 1.39). The average sleep quality of the analyzed sample was at the mean value. About 20% of the participants reported their general health status was either fair or poor. The average SF-12 physical function was 49.28 (SD = 10.14), slightly below the national average, and the average SF-12 mental function was 52.96 (SD = 8.81), slightly above the national average. These findings are consistent with the NLSY79’s reported statistics [ 34 ]. Approximately 17% of the respondents reported having depressive symptoms (CES-D scores > = 8) at age 50.

The bivariate statistical analyses shown in Table 1 suggest that people with employment patterns of “stable ST” had comparatively advantaged characteristics in terms of being non-Hispanic White, having a college or above education by age 23, being less likely to have been exposed to poverty or welfare assistance by age 22, and having a lower-than-average percentage of health issues limiting their ability to work. The next groups with somewhat advantaged sociodemographic characteristics were participants with an employment pattern of either “early ST-mostly VH” or “mostly ST with some VH;” the notable differences between these two groups were the former being more likely to be a man and non-Hispanic White and the latter being more likely to be a female and Hispanic. In contrast, being a man, being non-Hispanic Black, and having a high school degree were more likely to be associated with the “early ST-volatile” employment pattern. Of importance, participants with an employment pattern of “mostly NW” tended to have somewhat disadvantaged sociodemographic backgrounds. For instance, they were likely to be either non-Hispanic Black or Hispanic, to have less than a high school education, to have health issues limiting work, to have become parents by age 22, to have been exposed to poverty or welfare by age 22, and to experience more years of poverty and welfare assistance after age 22. Given these differences in sociodemographic backgrounds for the employment patterns, it is not surprising to find that, generally, people with the “stable ST” employment pattern between ages 22 and 49 had the most favorable sleep and health outcomes, and that people with the “mostly NW” employment pattern had the worst sleep and health outcomes. Those with the “early ST-volatile” employment pattern had the second-worst sleep and health outcomes.

Multiple regression estimates of work schedule patterns on sleep and health

Tables 2 and 3 report multiple regression estimates of employment patterns on sleep and health outcomes, with Table 2 reporting the hours and quality of sleep (OLS regression) along with the likelihood of self-reporting poor health (logistic regression) and Table 3 reporting SF-12 physical and mental functions (OLS regression) along with the likelihood of self-reporting depressive symptoms (logistic regression). All sociodemographic characteristics detailed in the Measures section were considered in all analyses. On the whole, results in Tables 2 and 3 indicate that employment patterns matter to sleep and health. Specifically, compared to the pattern of mostly stable standard hours (“stable ST”), having an employment pattern of working standard hours during early career years (age 20s) but transitioning into volatile schedules after age 30 (“early ST-volatile”) was statistically significantly associated with fewer hours of sleep per day, lower quality of sleep, a higher likelihood of self-reporting poor health at age 50, lower scores on SF-12 physical and mental functions, and a higher likelihood of having depressive symptoms. Compared to the “stable ST” pattern, people with an employment pattern of working mostly standard hours but with some variable hours (“mostly ST with some VH”) also had significantly worse sleep and health outcomes, except for a nonsignificant effect on SF-12 mental function. People with an employment pattern of having standard hours during their 20s but transitioning into mostly variable hours after age 30 (“early ST-mostly VH”) had significantly fewer hours of sleep per day and significantly lower SF-12 physical function scores than those with the “stable ST” pattern. Lastly, people with an employment pattern of mostly not working (“mostly NW”) reported a significantly higher likelihood of poor health and significantly lower SF-12 physical function than those with the “stable ST” pattern. In addition, post-estimation Wald test results (not shown, available upon request) indicate that individuals with the “early ST-volatile” employment pattern (1) slept significantly fewer hours (b = -0.24 vs. b = -0.10, χ 2 = 7.42, p < .01), reported significantly lower SF-12 physical function (b = -1.42 vs. b = -0.62, χ 2 = 5.53, p < .05), and were more likely to report poor health (b = 0.45 vs. b = 0.18, χ 2 = 9.08, p < .01) than those with the “mostly ST with some VH” pattern and (2) were more likely to report poor health than those with the “early ST-mostly VH” pattern (b = 0.45 vs. b = 0.08, χ 2 = 9.39, p < .01). Furthermore, individuals with the employment pattern of “early ST-mostly VH” had significantly fewer hours of sleep per day during the week compared to those with the “mostly ST with some VH” pattern (b = -0.23 vs. b = -0.10, χ 2 = 6.28, p < .01). The post-estimation Wald tests detected no other statistically significant differences among employment patterns.

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As expected, age, gender, race-ethnicity, education, marital status, health issues limiting work capacity, years of receiving welfare or living in poverty, number of marriages and children, weekly working hours, and occupations were by and large significantly associated with hours and quality of sleep and other health outcomes. However, gender and race-ethnicity did not make a difference in the likelihood of self-reporting poor health. Specifically, people occupying vulnerable social positions (e.g., women, less than a high school education, previously married, having health limitations, multiple marriages, more experiences of poverty and welfare, not having full-time work status) tended to report lower sleep quality and lower SF-12 physical and mental functions, and were more likely to self-report poor health and having depressive symptoms. Note that, compared to men, women reported significantly more hours of sleep but substantially lower sleep quality. Moreover, compared to non-Hispanic White peers, non-Hispanic Black respondents reported considerably fewer hours of sleep yet better sleep quality.

For ease of interpretation, Table 4 presents the predicted estimates of how sleep and health outcomes might vary by employment patterns based on the results reported in Tables 2 and 3 . Across all outcomes, among those employed, individuals engaged in the “early ST-volatile” pattern between 22 and 49 had fewer (if not the fewest) hours of sleep (6.80 hrs/day), the lowest quality of sleep (-0.02), the highest likelihood of self-reporting poor health (0.23), the lowest SF-12 physical and mental functions scores (48.62 and 52.45), and the highest likelihood of having depressive symptoms (0.19). In contrast, individuals engaged in the “stable ST” pattern had the best outcomes, followed by those with the pattern of “mostly ST with some VH.”

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Variations in links between employment patterns and outcomes by social position

Prior research suggests that social position influences employment patterns, with vital implications for our health [ 3 , 5 , 6 , 17 , 18 ]. Figs 2 – 7 display the predicted estimates of the six outcomes by intersecting employment patterns, gender, race, and education. S2 – S7 Tables present the predicted estimates in detail. Several findings are worth highlighting. First, education serves an important cushion for better sleep (hours and quality) and health outcomes regardless of employment pattern, race, or gender. Second, the significantly poorer sleep and health outcomes observed in Tables 2 and 3 were concentrated among people with vulnerable positions, such as females, racial minorities (with some exceptions detailed below), and those with less than a college degree. For example, Black males with the “early ST-mostly VH” employment pattern slept the least regardless of education; their average sleep hours were 6.39, 6.44, 6.44, and 6.50, respectively, for less than a high school degree, high school, some college, and college and above. On the other spectrum are White females, who tended to have the most sleep hours, particularly if they had the employment pattern of stable standard hours (7.14, 7.19, 7.19, and 7.25 for the educational groups of less than a high school degree to college or above) ( Fig 2 and S2 Table ).

In contrast with the sleep hours results, Black males reported the best and White females the worst sleep quality. These findings are particularly true for those with either the “early ST-volatile” or the “mostly ST with some VH” employment pattern regardless of educational attainment ( Fig 3 and S3 Table ).

The health outcomes also varied by employment pattern and social position. In general, “early ST-volatile” reported the poorest health outcomes across all educational groups and all racial/ethnic and gender pairings. Specifically, across all education categories, Black females who had the "early ST-volatile" employment pattern reported the highest likelihood of having poor health among all groups examined. Despite White males in the “early ST-volatile” group also reporting a high likelihood of having poor health, the difference in the likelihood of reporting poor health between Black females (.34) and White males (.27) with this employment pattern is about .07 among those with less than a high school education ( Fig 4 and S4 Table ). In addition, Black females with the “early ST-volatile” employment pattern had the lowest SF-12 physical function score, whereas males, regardless of race, reported the highest SF-12 physical function ( Fig 5 and S5 Table ). In regard to SF-12 mental function, Black males and females generally reported better scores than White males and females. In addition, White females with the “early ST-volatile” employment pattern reported the lowest SF-12 mental function; this is particularly true if they had a less than high school education ( Fig 6 and S6 Table ).

Similar to the SF-12 mental health results, Black males and females generally reported a lower likelihood of having depressive symptoms than their White counterparts. In addition, White females with the “early ST-volatile” employment pattern reported the highest likelihood of having depressive symptoms, particularly among those with less than a high school education ( Fig 7 and S7 Table ). The difference in the likelihood of having depressive symptoms between this group and White males in the highest education group with the “stable ST” employment patterns is striking: .32 versus .07.

Discussion and conclusion

Since the 1980s, our employment has been shaped by global technological and digital advances, together with the rise and dominance of the service economy. These changes have produced undesirable health consequences, including disrupting our sleep routines, an aspect of our daily life critical to nurturing our health. Decades of research has established that sleep, both duration and quality, matters to our health [ 5 ]. This paper contributes two crucial insights to advance our knowledge of how work may have become a vulnerability for our sleep and health. Specifically, nonstandard work schedules, a central indicator of precarious employment, have become a widespread job characteristic in the increasingly unequal and globalized labor market [ 3 , 15 ]. Moreover, the strains and harm caused by the recent devastating public health crisis (the COVID-19 pandemic) were disproportionately carried by those without resources and those with precarious jobs [ 51 ], particularly in the United States [ 6 ]. This study thus examines the extent to which having a nonstandard work schedule throughout one’s working life in the United States might make a difference in both sleep hours and quality and health outcomes. I paid particular attention to the relationship between employment patterns, sleep, and health outcomes among the groups most likely to be subject to working nonstandard hours. Below I highlight a few significant findings.

Using a nationally representative, longitudinal sample of U.S. individuals interviewed since 1979, this study finds that employment patterns over our working lives matter to our sleep and health, consistent with prior research [ 1 , 5 , 12 , 52 ]. Importantly, this study approaches this issue from a life-course perspective, examining how employment patterns over our working lives might be linked to our sleep and health by shaping our daily routines. My empirical results suggest that individuals engaged in volatile work schedule patterns—a combination of evening, night, and variable hours—could anticipate sleeping significantly fewer hours per day, getting lower sleep quality, perceiving lower SF-12 physical and mental functions, and reporting a higher likelihood of poor health and depressive symptoms at age 50 than people working regular daytime hours. In fact, any employment pattern involving nonstandard hours (such as evening, night, or variable hours) for most of one’s working years may be associated with adverse sleep and health outcomes. These results suggest that a job requiring constant changes between daytime, evenings, nights, and irregular hours could significantly interfere with daily routines, affecting when a person sleeps, eats, and socializes with family members and friends. Furthermore, night shifts require a waking state during night hours when our bodies need rest, disrupting our circadian rhythm and thus sleep routines, including sleep quality. The lack of (good quality) sleep, physical fatigue, and emotional exhaustion stemming from a volatile employment pattern exemplifies how our work has made us vulnerable to an unhealthy life. Indeed, in regard to the SF-12 physical and mental function scores and the likelihood of having depressive symptoms, the effect sizes associated with the “early ST-volatile” employment pattern were similar to, if not larger than, having less than a high school education (see Table 3 ). This adverse health consequence of nonstandard work schedule patterns is alarming given that the extant research has shown that getting an inadequate amount of sleep and having poor sleep quality can have myriad short- and long-term health consequences, ranging from somatic issues and increased stress responsivity, which can lead to increased anxiety and depression [ 53 ], to a high prevalence of hypertension, obesity, and stroke [ 5 ].

The picture becomes grimmer if we further disentangle these links by social position. For example, as shown in Table 1 , Blacks were more likely than their White peers to have an employment pattern of starting with standard hours but soon transitioning into volatile schedules for most of their working years. Importantly, the intersectionality between employment patterns and social position only underscores the substantial health disparities between those with resources and those without: those without disproportionately shoulder the adverse consequences of employment patterns characterized by volatility, confirming that advantages and disadvantages produced by our work can accumulate throughout a lifetime, with powerful implications for our health and well-being. The empirical evidence reported here shows that White females with a college or above education who had an employment pattern of stable standard-hour schedules (“stable-ST”) got on average six more hours of sleep a week ((7.25–6.39) x 7) than Black males with less than a high school degree who worked variable hours for most of their working years (“early ST-mostly VH”). Even within the group with less than a high school education, White females with the “stable-ST” employment pattern got on average five more hours of sleep a week ((7.14–6.39) x 7) than Black males with the “early ST-mostly VH” employment pattern. Similarly, the likelihood of reporting poor health was .09 among White males with a college or above education and an employment pattern of stable standard hours versus .34 (the highest likelihood) among Black females with a less than high school education and the “early ST-volatile” employment pattern. The former also reported significantly better SF-12 physical function than the latter, with an effect size of five-tenths of one standard deviation (51.61–46.44 = 5.17) (see S5 Table ).

However, the opposite is true regarding gender differences in sleep quality and mental health. Specifically, females generally reported more hours of sleep but also poorer sleep quality than their male counterparts, which is consistent with the established scholarship in this area [ 54 , 55 ]. Studies have examined whether gender differences in sleep quality might be related to biological (e.g., genetics) and sociological (e.g., family responsibilities, work) factors [ 54 ]. The extant research suggests that family responsibilities and work characteristics are the most important factors explaining why women experience sleep disorders more than men [ 54 ]. Specifically, among those who work nonstandard schedules, women are more likely to have sleep disorders than men [ 54 ]. In line with the literature, my analyses show that (see S3 Table ) White and Black females with less than a high school degree who had volatile employment patterns between ages 22 and 49 reported a sleep quality of -.29 and -.12, respectively. In contrast, the corresponding estimates were -.10 and .05 for White and Black males with that same educational level and employment pattern. As the sleep quality variable is a standardized score with a mean of 0 and a standard deviation of 1, the differences between White women and Black men amount to a one-third of a standard deviation (e.g., -.29 –(.05) / 1 = .34) among those with less than a high school degree and the employment pattern of “early ST-volatile.” Further, when comparing White and Black males with a college degree and the “stable ST” employment pattern, the corresponding estimates were .18 and .25. The difference between White females with a less than a high school degree and an employment pattern of “early ST-volatile” and Black males with a college or above education and a “stable ST” employment pattern is even larger, amounting to slightly over half of a standard deviation (e.g., -.29 –(.25) / 1 = .54). These differences are considered medium to large effect sizes [ 55 , 56 ].

In regard to mental health, extant studies have shown that males are less likely to report mental health symptoms than females, a finding echoed in my analysis. Prior research indicates that although males and females were equally likely to experience emotional stress, males were less likely than females to express stress in ways that are measured through items in the SF-12 or CES-D instruments [ 57 ]. In addition, studies have found that females are more likely than males to report mild-moderate depression, but males report severe depression and suicidal thoughts more often than females [ 58 ]. Because the measures used in this study assess mild to moderate depressive symptoms, my findings that females reported poorer mental functions and a higher likelihood of having at-risk depressive symptoms than males are in line with previous empirical evidence. Furthermore, prior research has indicated that gender differences in symptom phenotypes (e.g., atypical symptoms in male depression) or in coping style (e.g., males tend not to seek help) are mechanisms that might explain why studies tend to observe a higher incidence of depression among females than males [ 58 ].

In contrast, and importantly, the racial differences in sleep hours and quality, and in health outcomes found in my analyses are nuanced and far from straightforward. Although Black males and, to a lesser extent, Black females tended to report similar physical and mental health as their White counterparts, the contrasts are striking when looking at sleep-related results. Specifically, Black males reported the fewest hours of sleep yet the best sleep quality, whereas White females tended to report more sleep hours but much poorer sleep quality. Although the extant research suggests that Blacks tend to sleep fewer hours (e.g., < 7 hrs) and have poorer sleep quality than their White counterparts, the Black–White disparities in sleep quality previously documented are somewhat mixed [ 59 ]. For example, studies that use objective measurements to assess sleep quality tend to confirm the Black–White disparities in sleep quality [ 59 ]. However, the results are less definitive when a subjective measure such as self-reports are used [ 59 ], which is how sleep quality was collected in the NLSY79. Prior studies have also shown that the Black–White disparities in sleep quality might have to do with socioeconomic status or environmental factors (e.g., neighborhood quality) [ 59 – 61 ]. In other words, the Black–White disparities in sleep quality might disappear once we consider these factors. Indeed, the raw data of this analysis indicated that Blacks in the NLSY79 sample reported the lowest sleep quality among all respondents, but this disparity disappeared in the multiple regression analysis when a rich set of sociodemographic characteristics were considered, including their work schedule trajectories.

Although beyond the scope of this paper, the scholarship on the “black–white health paradox” might also corroborate my findings that the Black respondents tended to report better sleep quality and similar if not better physical and mental functions despite shorter sleep duration [ 62 ]. Social stress theory, and related approaches, would predict that racial minority groups in the United States like Black Americans should be more likely than their White peers to develop poor physical and mental health due to discrimination-related experiences, in line with the core assumption of CAD [ 63 ]. However, prior studies using self-reported data (the same method as used with the NLSY79) have documented that Blacks display similar physical health and better mental health than their White counterparts [ 64 , 65 ]. Researchers have posited that experiencing discrimination, hardship, and stresses may increase resilience in the face of challenges [ 63 , 65 ]. If so, nonstandard work schedules, considered a disadvantage, might not directly translate into poor health for Blacks. However, caution is warranted when making any sweeping generalizations based on my results. After all, the predicted estimates shown in S3 Table suggest that Black males and females with less than a high school degree and a volatile employment pattern for most of their working lives had a high, if not the highest, likelihood of reporting poor health (.29 and .34, respectively) among all respondents. This association between perceived poor health and the joint forces of work and social position warrants attention in future research and policy advocacy endeavors.

Limitations

As with all observational studies, the current study has several limitations. First, the NLSY79 provided work schedule information annually until 1994 and biennially thereafter. For some, work schedules may have changed from month to month, let alone during the two-year windows, limiting my ability to depict more precise employment patterns over time. Thus, the present results may underestimate the true association between employment patterns and outcomes. However, the longitudinal approach has the advantage of reducing measurement noise. Specifically, longitudinal data allow more accuracy than cross-sectional data in recognizing, for example, individuals who have repeatedly reported nonstandard work schedules over the years versus those who might have only worked such a schedule a few times over 30 years.

Second, our daily routines and health are closely related to the type and amount of resources we can access; income and wages are the primary means of securing such resources. Ideally, the true association between employment patterns and sleep and health would be obtained after considering income and wages. However, the high correlation between employment and income and wages creates concerns about reverse causality. After all, our type of work determines how much income we can bring home. To address this potential reverse-causality issue, I controlled for the following variables likely to shape the type of work one may access at the start of their career and thus the wages and income they might bring home: the educational levels of the respondents and their parents and whether they had ever experienced poverty and/or received welfare before age 22. Nonetheless, our knowledge will benefit from a closer examination of how wages and income might play a critical role in the association between employment patterns and our sleep and health. For example, although it is beyond the scope of this analysis, future research might pursue this research question by utilizing a structural equation model to establish a proper temporal order between employment patterns (e.g., between ages 22 and 40), wages and income (e.g., between ages 41 and 49), and health outcomes (e.g., at age 50) to avoid reverse-causality issues. In this study, I did not adopt a structural equation modeling as specified above because my primary aim was to build upon a life-course lens to document the respondents’ work schedule trajectories using as many working years as possible (i.e., between ages 22 and 49 vs. between ages 22 and 39). Similarly, due to the data at hand, this analysis could not consider the number of hours respondents spent on household chores, which plays an important role not only in how many hours we can sleep but also in our physical and mental health. For example, women generally spend more time doing household work than men do despite potentially having the same number of working hours. These differences in household chores influence the number of hours a woman versus a man has for sleep and can impact their physical and emotional energy levels.

Third, individuals may switch from evening/night hours to standard daytime hours due to worsening health stemming from working nonstandard hours. If so, the estimates of the links between employment patterns and the sleep and health outcomes might be underestimated in this analysis. The sequence analysis adopted in this paper does not sufficiently answer such research questions. Although it is beyond the scope of this paper, future research might use other appropriate statistical analyses (e.g., latent transition analysis) to examine this crucial dynamic nature between employment patterns and sleep and health over time. Similarly, fixed-effect models might help answer research questions about how changes in employment patterns may shape changes in sleep and health over time. Such analyses would require at least three data points of health outcomes. This analysis relies on the 2018 NLSY79 data release, at which point only two such data points were available for the majority of its sample, as only about 10% of the respondents had reached age 60 to have three data points of health outcomes. In addition, the NLSY79 collected the sleep information analyzed here only in the health module at ages 50 and 60, thus limiting the ability to conduct the more sophisticated statistical analyses needed to answer more dynamic research questions.

Fourth, despite the sequence analysis accurately documenting the sequential changes in work trajectories, the analyses presented here at best represent associations instead of causation. While an experimental design study might allow one to detect a causal relationship between employment and sleep and health, randomly assigning individuals to different employment and various work schedule patterns would be neither feasible nor ethical. Hence, relying on quality longitudinal data with proper and sophisticated statistical analysis (e.g., fixed-effect modeling, instrumental variable) would allow us one step closer to causation.

Fifth, most of the NLSY79 health variables are self-reported, which likely influenced the outcomes identified here. Knowing how individuals perceive their sleep quality and health outcomes is critical as subjective perceptions significantly affect our well-being. However, the extant research using objective measurement tools consistently confirms a Black–White disparity in sleep quality and health outcomes, highlighting the importance of triangulating information to increase confidence in the findings.

Sixth, sample attrition is unavoidable with longitudinal data and could have affected some results. The positive selection bias associated with sample attrition might also bias the true association between employment patterns and sleep and health outcomes.

Seventh, although I used a separate racial-ethnic group named “other” that included Asian and other ethnicities, the estimates suffer from extremely small sample sizes, prohibiting me from drawing definitive interpretations about this group. This limitation warrants attention in future efforts to collect nationally representative data. Despite these limitations, the NLSY79 is the only dataset containing work schedule information for a nationally representative sample in the U.S. over three decades during a period when nonstandard work schedules were increasingly becoming prevalent throughout the country.

This study uses a life-course lens to shed much-needed light on how our employment patterns might shape our sleep and health as we approach middle adulthood. Employment is a crucial factor in the process of producing and accumulating resources and risks throughout our lives. Of importance, precarious employment has become increasingly typical in the globalized and polarized labor market, and nonstandard work schedules are a critical feature of precarious jobs. Examining employment patterns and work schedules through a longitudinal lens thus provides a deeper appreciation of how the impact of nonstandard work schedules might manifest through advantages and disadvantages accumulated throughout one’s working life. This approach also underscores that the health burden might be disproportionately shouldered by workers in vulnerable social positions (e.g., females, low education, Blacks). This study’s findings highlight the dual challenges facing workers in vulnerable social positions who have jobs requiring nonstandard work schedules, both of which limit their access to resources that would allow them to achieve decent sleep health and physical and mental health outcomes. This analysis thus calls attention to the reality of how employment as a social system may generate and perpetuate vulnerabilities and inequalities for particular groups over the life course.

Supporting information

S1 table. goodness-of-fit statistics for work arrangements sequence cluster solutions..

https://doi.org/10.1371/journal.pone.0300245.s001

S2 Table. Adjusted predictions of average sleep hours per day/week at age 50 by work schedule patterns, gender, race, and education.

https://doi.org/10.1371/journal.pone.0300245.s002

S3 Table. Adjusted predictions of sleep quality at age 50 by work schedule patterns, gender, race, and education.

https://doi.org/10.1371/journal.pone.0300245.s003

S4 Table. Adjusted predicted probabilities of self-reporting poor health at age 50 by work schedule patterns, gender, race, and education.

https://doi.org/10.1371/journal.pone.0300245.s004

S5 Table. Adjusted predictions of SF-12 physical function at age 50 by work schedule patterns, gender, race, and education.

https://doi.org/10.1371/journal.pone.0300245.s005

S6 Table. Adjusted predictions of SF-12 mental function at age 50 by work schedule patterns, gender, race, and education.

https://doi.org/10.1371/journal.pone.0300245.s006

S7 Table. Adjusted predicted probabilities of self-reporting depressive symptoms at age 50 by work schedule patterns, gender, race, and education.

https://doi.org/10.1371/journal.pone.0300245.s007

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Examining the mediating effect of job satisfaction on the relationship between job autonomy and life satisfaction in early adulthood: a five-year data analysis conducted through latent growth modeling

• Published: 08 August 2023
• Volume 43 , pages 8963–8971, ( 2024 )

Cite this article

• Jo-Eun Lee   ORCID: orcid.org/0000-0002-3380-4967 1 &
• Sung-Man Bae   ORCID: orcid.org/0000-0001-5762-4306 2  

This study aimed to verify the relationship between job autonomy, job satisfaction, and life satisfaction. In particular, we analyzed job satisfaction’s longitudinal mediating effect on the relationship between job autonomy and life satisfaction. This study analyzed the data of 1,035 participants, which were obtained from the Korean Educational Longitudinal Study 2005 panel data; these data are collected by the Korea Educational Development Institute from time to time. The results were as follows. First, job autonomy showed a significant positive effect on job satisfaction. Second, job satisfaction showed a significant positive effect on life satisfaction. Third, this study found that job satisfaction had a full mediating effect between job autonomy and life satisfaction. This study makes a significant contribution to the field of work and well-being by revealing the relationship between job autonomy, job satisfaction, and life satisfaction and by revealing the mediating effect of job satisfaction on the relationship between job autonomy and life satisfaction through its longitudinal analysis. These results are expected to aid in understanding the factors that enhance life satisfaction in early adulthood.

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This study analyzed data from ‘a 2005 longitudinal study of Korean education’ conducted by the Korea Educational Development Institute.

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Lee, JE., Bae, SM. Examining the mediating effect of job satisfaction on the relationship between job autonomy and life satisfaction in early adulthood: a five-year data analysis conducted through latent growth modeling. Curr Psychol 43 , 8963–8971 (2024). https://doi.org/10.1007/s12144-023-05044-8

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Psychosocial Development in Middle Adulthood

Diana Lang; Nick Cone; Martha Lally; Suzanne Valentine-French; and Ronnie Mather

In the popular imagination (and academic press) middle adulthood has been referenced in relation to a “mid-life crisis.” There is an emerging view that this may have been an overstatement—certainly, the evidence on which it is based has been seriously questioned. However, there is some support for the view that people do undertake a sort of emotional audit, reevaluate their priorities, and emerge with a slightly different orientation to emotional regulation and personal interaction in this time period. Why, and the mechanisms through which this change is affected, are a matter of some debate. We will examine the ideas of Erikson, Baltes, and Carstensen, and how they might inform a more nuanced understanding of this vital part of the lifespan. [1]

Psychosocial Development

What do you think is the happiest stage of life? [2] What about the saddest stages? Perhaps surprisingly, Blanchflower & Oswald [3] found that reported levels of unhappiness and depressive symptoms peak in the early 50s for men in the U.S., and interestingly, the late 30s for women. In Western Europe, minimum happiness is reported around the mid 40s for both men and women, albeit with some significant national differences. There is now a view that “older people” (50+) may be “happier” than younger people, despite some cognitive and functional losses. This is often referred to as “the paradox of aging.” Positive attitudes to the continuance of cognitive and behavioral activities, interpersonal engagement, and their vitalizing effect on human neural plasticity, may lead not only to more life, but to an extended period of both self-satisfaction and continued communal engagement.

Erikson’s Theory

As you know by now, Erikson’s theory is based on an idea called epigenesis, meaning that development is progressive and that each individual must pass through the eight different stages of life—all while being influenced by context and environment. Each stage forms the basis for the following stage, and each transition to the next is marked by a crisis which must be resolved. The sense of self, each “season”, was wrested, from and by, that conflict. The ages 40-65 are no different. The individual is still driven to engage productively, but the nurturing of children and income generation assume lesser functional importance. From where will the individual derive their sense of self and self-worth?

Generativity versus Stagnation is Erikson’s characterization of the fundamental conflict of adulthood. It is the seventh conflict of his famous “8 seasons of man” (1950) and negotiating this conflict results in the virtue of care.  Generativity is “primarily the concern in establishing and guiding the next generation.” [4] Generativity is a concern for a generalized other (as well as those close to an individual) and occurs when a person can shift their energy to care for and mentor the next generation. One obvious motive for this generative thinking might be parenthood, but others have suggested intimations of mortality by the self. John Kotre [5] theorized that generativity is a selfish act, stating that its fundamental task was to outlive the self. He viewed generativity as a form of investment. This form of investment can often be seen through volunteering. However, a commitment to a “belief in the species” can be taken in numerous directions, and it is probably correct to say that most modern treatments of generativity treat it as collection of facets or aspects—encompassing creativity, productivity, commitment, interpersonal care, and so on.

On the other side of generativity is stagnation . It is the feeling of lethargy and a lack of enthusiasm and involvement in both individual and communal affairs. It may also denote an underdeveloped sense of self, or some form of overblown narcissism. Erikson sometimes used the word “rejectivity” when referring to severe stagnation.

The Stage-Crisis View and the Midlife Crisis

In 1977, Daniel Levinson published an extremely influential article that would be seminal in establishing the idea of a profound crisis which lies at the heart of middle adulthood. The concept of a midlife crisis is so pervasive that over 90% of Americans are familiar with the term, although those who actually report experiencing such a crisis is significantly lower. [6]

Levinson based his findings about a midlife crisis on biographical interviews with a limited sample of 40 men (no women!), and an entirely American sample at that (Figure 1). Despite these severe methodological limitations, his findings proved immensely influential. Levinson [7]  identified five main stages or “seasons” of a man’s life as follows:

• Preadulthood: Ages 0-22 (with 17 – 22 being the Early Adult Transition years)
• Early Adulthood: Ages 17-45 (with 40 – 45 being the Midlife Transition years)
• Middle Adulthood: Ages 40-65 (with 60-65 being the Late Adult Transition years)
• Late Adulthood: Ages 60-85
• Late Late Adulthood: Ages 85+

Levinson’s theory is known as the stage-crisis view . He argued that each stage overlaps, consisting of two distinct phases—a stable phase, and a transitional phase into the following period. The latter phase can involve questioning and change, and Levinson believed that 40-45 was a period of profound change, which could only culminate in a reappraisal, or perhaps reaffirmation, of goals, commitments and previous choices—a time for taking stock and recalibrating what was important in life. Crucially, Levinson would argue that a much wider range of factors, involving, primarily, work and family, would affect this taking stock – what he had achieved, what he had not; what he thought important, but had brought only a limited satisfaction.

In 1996, two years after his death, the study he was conducting with his co-author and wife Judy Levinson, was published on “the seasons of life” as experienced by women. Again, it was a small-scale study, with 45 women who were professionals, academics, and homemakers, in equal proportion. The changing place of women in society was reckoned by Levinson to be a profound moment in the social evolution of the human species, however, it had led to a fundamental polarity in the way that women formed and understood their social identity. Levinson referred to this as the “dream.” For men, the “dream” was formed in the age period of 22-28, and largely centered on the occupational role and professional ambitions. Levinson understood the female “dream” as fundamentally split between this work-centered orientation, and the desire/imperative of marriage/family; a polarity that heralded both new opportunities, and fundamental angst.

Levinson found that the men and women he interviewed sometimes had difficulty reconciling the “dream” they held about the future with the reality they currently experienced. “What do I really get from and give to my wife, children, friends, work, community-and self?” a man might ask. [8] Tasks of the midlife transition include:

• ending early adulthood;
• reassessing life in the present and making modifications if needed; and
• reconciling “polarities” or contradictions in one’s sense of self.

Perhaps early adulthood ends when a person no longer seeks adult status but feels like a full adult in the eyes of others. This “permission” may lead to different choices in life—choices that are made for self-fulfillment instead of social acceptance. While people in their 20s may emphasize how old they are (to gain respect, to be viewed as experienced), by the time people reach their 40s, they tend to emphasize how young they are (few 40-year-olds cut each other down for being so young: “You’re only 43? I’m 48!!”).

This new perspective on time brings about a new sense of urgency to life. The person becomes focused more on the present than the future or the past. The person grows impatient at being in the “waiting room of life,” postponing doing the things they have always wanted to do. “If it’s ever going to happen, it better happen now.” A previous focus on the future gives way to an emphasis on the present. Neugarten [9] notes that in midlife, people no longer think of their lives in terms of how long they have lived. Rather, life is thought of in terms of how many years are left. If an adult is not satisfied at midlife, there is a new sense of urgency to start to make changes now.

Changes may involve ending a relationship or modifying one’s expectations of a partner. These modifications are easier than changing the self. [10] Midlife is a period of transition in which one holds earlier images of the self while forming new ideas about the self of the future. A greater awareness of aging accompanies feelings of youth, and harm that may have been done previously in relationships haunts new dreams of contributing to the well-being of others. These polarities are the quieter struggles that continue after outward signs of “crisis” have gone away.

Levinson characterized midlife as a time of developmental crisis. However, like any body of work, it has been subject to criticism. Firstly, the sample size of the populations on which he based his primary findings is too small. By what right do we generalize findings from interviews with 40 men and 45 women, however thoughtful and well conducted? Secondly, Chiriboga [11] could not find any substantial evidence of a midlife crisis, and it might be argued that this, and further failed attempts at replication, indicate a cohort effect. The findings from Levinson’s population indicated a shared historical and cultural situatedness, rather than a cross-cultural universal experience by all or even most individuals. Midlife is a time of revaluation and change, that may escape precise determination in both time and geographical space, but people do emerge from it, and seem to enjoy a period of contentment, reconciliation, and acceptance of self.

This video explains the research and controversy surrounding the concept of a midlife crisis.

You can view the transcript for “Does Everyone Have a ‘Midlife Crisis’?” here (opens in new window) .

Socio-Emotional Selectivity Theory (SST)

It is the inescapable fate of human beings to know that their lives are limited. As people move through life, goals and values tend to shift. What we consider priorities, goals, and aspirations are subject to renegotiation. Attachments to others, current and future, are no different. Time is not the unlimited good as perceived by a child under normal social circumstances; it is very much a valuable commodity, requiring careful consideration in terms of the investment of resources. This has become known in the academic literature as mortality salience.

Mortality salience posits that reminders about death or finitude (at either a conscious or subconscious level), fills us with dread. We seek to deny its reality, but awareness of the increasing nearness of death can have a potent effect on human judgement and behavior. This has become a very important concept in contemporary social science. It is with this understanding that Laura Carstensen developed the theory of socioemotional selectivity theory , or SST. The theory maintains that as time horizons shrink, as they typically do with age, people become increasingly selective, investing greater resources in emotionally meaningful goals and activities. According to the theory, motivational shifts also influence cognitive processing. Aging is associated with a relative preference for positive over negative information. This selective narrowing of social interaction maximizes positive emotional experiences and minimizes emotional risks as individuals become older. They systematically hone their social networks so that available social partners satisfy their emotional needs. An adaptive way of maintaining a positive affect might be to reduce contact with those we know may negatively affect us, and avoid those who might.

SST is a theory which emphasizes a time perspective rather than chronological age. When people perceive their future as open ended, they tend to focus on future-oriented development or knowledge-related goals. When they feel that time is running out, and the opportunity to reap rewards from future-oriented goals’ realization is dwindling, their focus tends to shift towards present-oriented and emotion or pleasure-related goals. Research on this theory often compares age groups ( e.g. , young adulthood vs. old adulthood), but the shift in goal priorities is a gradual process that begins in early adulthood. Importantly, the theory contends that the cause of these goal shifts is not age itself,  i.e. , not the passage of time itself, but rather an age-associated shift in time perspective. The theory also focuses on the types of goals that individuals are motivated to achieve. Knowledge-related goals aim at knowledge acquisition, career planning, the development of new social relationships and other endeavors that will pay off in the future. Emotion-related goals are aimed at emotion regulation, the pursuit of emotionally gratifying interactions with social partners, and other pursuits whose benefits which can be realized in the present.

This shift in emphasis, from long term goals to short term emotional satisfaction, may help explain the previously noted “paradox of aging.” That is, that despite noticeable physiological declines, and some notable self-reports of reduced life-satisfaction around this time, post- 50 there seems to be a significant increase in reported subjective well-being. SST does not champion social isolation, which is harmful to human health, but shows that increased selectivity in human relationships, rather than abstinence, leads to more positive affect. Perhaps “midlife crisis and recovery” may be a more apt description of the 40-65 period of the lifespan.

Watch Laura Carstensen in this TED talk explain how happiness actually increases with age.

You can view the transcript for “Older people are happier – Laura Carstensen” here (opens in new window) .

Selection, Optimization, Compensation (SOC)

Another perspective on aging was identified by German developmental psychologists Paul and Margret Baltes. Their text Successful Aging [12]  marked a seismic shift in moving social science research on aging from largely a deficits-based perspective to a newer understanding based on a holistic view of the life-course itself. The former had tended to focus exclusively on what was lost during the aging process, rather than seeing it as a balance between those losses and gains in areas like the regulation of emotion, experience and wisdom.

The Baltes’ model for successful aging argues that across the lifespan, people face various opportunities or challenges such as, jobs, educational opportunities, and illnesses. According to the SOC model, a person may select particular goals or experiences, or circumstances might impose themselves on them. Either way, the selection process includes shifting or modifying goals based on choice or circumstance in response to those circumstances. The change in direction may occur at the subconscious level. This model emphasizes that setting goals and directing efforts towards a specific purpose is beneficial to healthy aging. Optimization is about making the best use of the resources we have in pursuing goals. Compensation, as its name suggests, is about using alternative strategies in attaining those goals. [13]

The processes of selection, optimization, and compensation can be found throughout the lifespan. As we progress in years, we select areas in which we place resources, hoping that this selection will optimize the resources that we have, and compensate for any defects accruing from physiological or cognitive changes. Previous accounts of aging had understated the degree to which possibilities from which we choose had been eliminated, rather than reduced, or even just changed. As we select areas in which to invest, there is always an opportunity cost. We are masters of our own destiny, and our own individual orientation to the SOC processes will dictate “successful aging.” Rather than seeing aging as a process of progressive disengagement from social and communal roles undertaken by a group, Baltes argued that “successful aging” was a matter of sustained individual engagement, accompanied by a belief in individual self-efficacy and mastery.

The SOC model covers a number of functional domains—motivation, emotion, and cognition. We might become more adept at playing the SOC game as time moves on, as we work to compensate and adjust for changing abilities across the lifespan. For example, a soccer a player at 35 may no longer have the vascular and muscular fitness that they had at 20 but her “reading” of the game might compensate for this decline. She may well be a better player than she was at 20, even with fewer physical resources in a game which ostensibly prioritizes them. The work of Paul and Margaret Baltes was very influential in the formation of a very broad developmental perspective which would coalesce around the central idea of resiliency. [14]

Social Relationships and Stress

Research has shown that the impact of social isolation on our risk for disease and death is similar in magnitude to the risk associated with smoking regularly. [15] [16] In fact, the importance of social relationships for our health is so significant that some scientists believe our body has developed a physiological system that encourages us to seek out our relationships, especially in times of stress. [17] Social integration is the concept used to describe the number of social roles that you have. [18] For example, you might be a daughter, a basketball team member, a Humane Society volunteer, a coworker, and a student. Maintaining these different roles can improve your health via encouragement from those around you to maintain a healthy lifestyle. Those in your social network might also provide you with social support (e.g., when you are under stress). This support might include emotional help (e.g., a hug when you need it), tangible help (e.g., lending you money), or advice. By helping to improve health behaviors and reduce stress, social relationships can have a powerful, protective impact on health, and in some cases, might even help people with serious illnesses stay alive longer. [19]

Caregiving and stress

A disabled child, spouse, parent, or other family member is part of the lives of some midlife adults. According to the National Alliance for Caregiving [20] , 40 million Americans provide unpaid caregiving. The typical caregiver is a 49 year-old female currently caring for a 69 year-old female who needs care because of a long-term physical condition. Looking more closely at the age of the recipient of caregiving, the typical caregiver for those 18-49 years of age is a female (61%) caring mostly for her own child (32%) followed by a spouse or partner (17%). When looking at older recipients (50+) who receive care, the typical caregiver is female (60%) caring for a parent (47%) or spouse (10%).

Caregiving places enormous stress on the caregiver. Caregiving for a young or adult child with special needs was associated with poorer global health and more physical symptoms among both fathers and mothers. [21] Marital relationships are also a factor in how the caring affects stress and chronic conditions. Fathers who were caregivers identified more chronic health conditions than non-caregiving fathers, regardless of marital quality. In contrast, caregiving mothers reported higher levels of chronic conditions when they reported a high level of marital strain. [22] Age can also make a difference in how one is affected by the stress of caring for a child with special needs. Using data from the Study of Midlife in the Unites States, Ha, Hong, Seltzer and Greenberg [23] found that older parents were significantly less likely to experience the negative effects of having a disabled child than younger parents. They concluded that an age-related weakening of the stress occurred over time. This follows with the greater emotional stability noted at midlife.

Currently 25% of adult children, mainly baby boomers, provide personal or financial care to a parent. [24] Daughters are more likely to provide basic care and sons are more likely to provide financial assistance. Adult children 50+ who work and provide care to a parent are more likely to have fair or poor health when compared to those who do not provide care. Some adult children choose to leave the work force, however, the cost of leaving the work force early to care for a parent is high. For females, lost wages and social security benefits equals $324,044, while for men it equals $283,716. [25] This loss can jeopardize the adult child’s financial future. Consequently, there is a need for greater workplace flexibility for working caregivers.

Spousal care

Certainly caring for a disabled spouse would be a difficult experience that could negatively affect one’s health. However, research indicates that there can be positive health effect for caring for a disabled spouse. Beach, Schulz, Yee and Jackson [26] evaluated health related outcomes in four groups: Spouses with no caregiving needed (Group 1), living with a disabled spouse but not providing care (Group 2), living with a disabled spouse and providing care (Group 3), and helping a disabled spouse while reporting caregiver strain, including elevated levels of emotional and physical stress (Group 4). Not surprisingly, the participants in Group 4 were the least healthy and identified poorer perceived health, an increase in health-risk behaviors, and an increase in anxiety and depression symptoms. However, those in Group 3 who provided care for a spouse, but did not identify caregiver strain, actually identified decreased levels of anxiety and depression compared to Group 2 and were actually similar to those in Group 1. It appears that greater caregiving involvement was related to better mental health as long as the caregiving spouse did not feel strain. The beneficial effects of helping identified by the participants were consistent with previous research. [27] [28]

When caring for a disabled spouse, gender differences have also been identified. Female caregivers of a spouse with dementia experienced more burden, had poorer mental and physical health, exhibited increased depressive symptomatology, took part in fewer health- promoting activities, and received fewer hours of help than male caregivers. [29] This recent study was consistent with previous research findings that women experience more caregiving burden than men, despite similar caregiving situations. [30] [31] Explanations for why women do not use more external support, which may alleviate some of the burden, include women’s expectations that they should assume caregiving roles [32] and their concerns with the opinions of others. [33] Also contributing to women’s poorer caregiving outcomes is that disabled males are more aggressive than females, especially males with dementia who display more physical and sexual aggression toward their caregivers. [34] [35] Female caregivers are certainly at risk for negative consequences of caregiving, and greater support needs to be available to them.

Work at midlife

Who is the U.S. workforce?  The civilian, non-institutionalized workforce; that is the population of those aged 16 and older, who are employed has steadily declined since it reached its peak in the late 1990s, when 67% of the civilian workforce population was employed. In 2012 the rate had dropped to 64% and has declined to 58% in 2021. [36] However, these should also be considered within the lens of the COVID-19 pandemic occurring in 2020. In 1992, 26% of the population was 55+, in 2019, 29.3% of the population is 55+, and by 2040 it is projected to be 32.6%. [37] Table 1 shows the rates of employment by age. In 2021, ~64% of the workforce was male. For both genders and age groups the rate of participation in the labor force has improved from 2011 to 2021.

*Adapted from (adapted from Monthly Labor Review). [38]

Hispanic males have the highest rate of participation in the labor force. In 2021, 70.5% of Hispanic males, compared with 58.6% of White, 68.3% of Asian, and 57.7% of Black men ages 16 or older were employed. Among women, Black women were more likely to be participating in the workforce, 54.1%, compared with 53.9% of Asian, 52.8% of White, and 51.8% of Hispanic females. [39]

Climate in the workplace for middle-aged adults

A number of studies have found that job satisfaction tends to peak in middle adulthood. [40] [41] This satisfaction stems from not only higher wages, but often greater involvement in decisions that affect the workplace as they move from worker to supervisor or manager. Job satisfaction is also influenced by being able to do the job well, and after years of experience at a job many people are more effective and productive. Another reason for this peak in job satisfaction is that at midlife many adults lower their expectations and goals. [42] Middle-aged employees may realize they have reached the highest they are likely to in their career. This satisfaction at work translates into lower absenteeism, greater productivity, and less job hopping in comparison to younger adults. [43]

However, not all middle-aged adults are happy in the workplace. Women may find themselves up against the glass ceiling ,  organizational discrimination in the workplace that limits the career advancement of women . This may explain why females employed at large corporations are twice as likely to quit their jobs as are men. [44] Another problem older workers may encounter is job burnout ,  becoming disillusioned and frustrated at work . American workers may experience more burnout than do workers in many other developed nations because most developed nations guarantee by law a set number of paid vacation days [45] , the United States does not. [46]

Not all employees are covered under overtime pay laws. [47] This is important when you considered that the 40-hour work week is a myth for most Americans. Only 4 in 10 U.S. workers work the typical 40-hour work week. The average work week for many is almost a full day longer (47 hours), with 39% working 50 or more hours per week. [48] In comparison to workers in many other developed nations, American workers work more hours per year. [49] As can be seen in Figure 3, Americans work more hours than most European nations, especially in western and northern Europe, although they work fewer hours than workers in other nations, especially Cambodia and Mexico.

Challenges in the workplace for middle-aged adults

In recent years middle-aged adults have been challenged by economic downturns, starting in 2001, and again in 2008. Fifty-five percent of adults reported some problems in the workplace, such as fewer hours, pay cuts, having to switch to part-time, etc., during the most recent economic recession (see Figure 4). [50] While young adults took the biggest hit in terms of levels of unemployment, middle-aged adults also saw their overall financial resources suffer as their retirement nest eggs disappeared and house values shrank, while foreclosures increased. [51]

Not surprisingly, this age group reported that the recession hit them worse than did other age groups, especially those aged 50-64. Middle-aged adults who find themselves unemployed are likely to remain unemployed longer than those in early adulthood. [52] In the eyes of employers, it may be more cost-effective to hire a young adult, despite their limited experience, as they would be starting out at lower levels of the pay scale. In addition, hiring someone who is 25 and has many years of work ahead of them versus someone who is 55 and will likely retire in 10 years may also be part of the decision to hire a younger worker. [53] American workers are also competing with global markets and changes in technology. Those who are able to keep up with all these changes, or are willing to uproot and move around the country or even the world have a better chance of finding work. The decision to move may be easier for people who are younger and have fewer obligations to others.

As most developed nations restrict the number of hours an employer can demand that an employee work per week, and require employers to offer paid vacation time, what do middle-aged adults do with their time off from work and duties , referred to as  leisure ? Around the world, the most common leisure activity in both early and middle adulthood is watching television. [54] On average, middle-aged adults spend 2-3 hours per day watching TV [55] and watching TV accounts for more than half of all leisure time.

In the United States, men spend about 5 hours more per week in leisure activities, especially on weekends, than do women. [56] [57] The leisure gap between mothers and fathers is slightly smaller, about 3 hours a week, than among those without children under age 18. [58] Those age 35-44 spend less time on leisure activities than any other age group, 15 or older. [59] This is not surprising as this age group are more likely to be parents and still working up the ladder of their career, so they may feel they have less time for leisure.

Americans have less leisure time than people in many other developed nations. As you read earlier, there are no laws in many job sectors guaranteeing paid vacation time in the United States. Ray, Sanes and Schmitt [60] report that several other nations also provide additional time off for young and older workers and for shift workers. In the United States, those in higher-paying jobs and jobs covered by a union contract are more likely to have paid vacation time and holidays. [61]

Do U.S. workers take their time off?

According to Project Time-Off, [62] 55% of U.S. workers in 2015 did not take all of their paid vacation and holiday leave. A large percentage of this leave is lost. It cannot be rolled over into the next year or paid out. A total of 658 million vacation days, or an average of 2 vacation days per worker was lost in 2015. The reasons most often given for not taking time off was worry that there would be a mountain of work to return to (40%), concern that no one else could do the job (35%), not being able to afford a vacation (33%), feeling it was harder to take time away when you have or are moving up in the company (33%), and not wanting to seem replaceable (22%). Since 2000, more American workers are willing to work for free rather than take the time that is allowed to them. A lack of support from their boss and even their colleagues to take a vacation is often a driving force in deciding to forgo time off. In fact, 80% of the respondents to the survey above said they would take time away if they felt they had support from their boss. Two-thirds reported that they hear nothing, mixed messages, or discouraging remarks about taking their time off. Almost a third (31%) feel they should contact their workplace, even while on vacation.

Benefits of taking time away from work

Several studies have noted the benefits of taking time away from work. It reduces job stress burnout, [63] improves both mental health [64] and physical health, [65] especially if that leisure time also includes moderate physical activity. [66] Leisure activities can also improve productivity and job satisfaction [67] and help adults deal with balancing family and work obligations. [68]

There are many socioemotional changes that occur in how middle-aged adults perceive themselves. While people in their early 20s may emphasize how old they are to gain respect or to be viewed as experienced, by the time people reach their 40s they tend to emphasize how young they are. For instance, few 40-year-olds cut each other down for being so young stating: “You’re only 43? I’m 48!” A previous focus on the future gives way to an emphasis on the present. Neugarten [69] notes that in midlife, people no longer think of their lives in terms of how long they have lived. Rather, life is thought of in terms of how many years are left.

• This chapter was adapted from select chapters in Lumen Learning's Lifespan Development , authored by Martha Lally and Suzanne Valentine-French available under a Creative Commons Attribution-NonCommercial-ShareAlike license , and Waymaker Lifespan Development , authored by Ronnie Mather for Lumen Learning and available under a Creative Commons Attribution license . Some selections from Lumen Learning were adapted from previously shared content from Laura Overstreet's Lifespan Psychology and Wikipedia. ↵
• This section, Psychosocial Development, is adapted from Lifespan Development by Ronnie Mather for Lumen Learning, and licensed under a Creative Commons ShareAlike License . Selections from the content were originally taken from LifeSpan Psychology by Laura Overstreet and Wikipedia's article on socioemotional selectivity theory . ↵
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• Arai, Y., Sugiura, M., Miura, H., Washio, M., & Kudo, K. (2000). Undue concern for other’s opinions deters caregivers of impaired elderly from using public services in rural Japan. International Journal of Geriatric Psychiatry, 15 (10), 961- 968. ↵
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• Monthly Labor Review. (2021). Percentage of the non-institutionalized civilian workforce employed by gender & age. https://www.bls.gov/cps/tables.htm#otheryears ↵
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• Besen, E., Matz-Costa, C., Brown, M., Smyer, M. A., & Pitt-Catsouphers, M. (2013). Job characteristics, core self-evaluations, and job satisfaction. International Journal of Aging & Human Development, 76 (4), 269-295. ↵
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Psychosocial Development in Middle Adulthood Copyright © 2022 by Diana Lang; Nick Cone; Martha Lally; Suzanne Valentine-French; and Ronnie Mather is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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9.8: Personality and Work Satisfaction

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Learning Outcomes

• Describe personality and work related issues in midlife

Personality in Midlife

Research on adult personality examines normative age-related increases and decreases in the expression of the so-called “Big Five” traits—extroversion, neuroticism, conscientiousness, agreeableness, and openness to experience. These are assumed to be based largely on biological heredity. These five traits are sometimes summarized via the OCEAN acronym. Individuals are assessed by the measurement of these traits along a continuum (e.g. high extroversion to low extroversion). They now dominate the field of empirical personality research. Does personality change throughout adulthood? Previously the answer was thought to be no. It was William James who stated in his foundational text, The Principles of Psychology (1890), that “[i]n most of us, by the age of thirty, the character is set like plaster, and will never soften again”. Not surprisingly, this became known as the plaster hypothesis.

Contemporary research shows that, although some people’s personalities are relatively stable over time, others’ are not (Lucas & Donnellan, 2011; Roberts & Mroczek, 2008). Longitudinal studies reveal average changes during adulthood, and individual differences in these patterns over the lifespan may be due to idiosyncratic life events (e.g., divorce, illness). Roberts, Wood & Caspi (2008) report evidence of increases in agreeableness and conscientiousness as persons age, mixed results in regard to openness, reduction in neuroticism but only in women, and no change with regard to extroversion. Whether this “maturation” is the cause or effect of some of the changes noted in the section devoted to psycho social development is still unresolved. Longitudinal research also suggests that adult personality traits, such as conscientiousness, predict important life outcomes including job success, health, and longevity (Friedman, Tucker, Tomlinson-Keasey, Schwartz, Wingard, & Criqui, 1993; Roberts, Kuncel, Shiner, Caspi, & Goldberg, 2007). How important these changes are remains somewhat unresolved. Thus, we have the hard plaster hypothesis, emphasizing fixity in personality over the age of thirty with some very minor variation, and the soft plaster version which views these changes as possible and important. [1]

Carl Jung believed that our personality actually matures as we get older. A healthy personality is one that is balanced. People suffer tension and anxiety when they fail to express all of their inherent qualities. Jung believed that each of us possess a “shadow side.” For example, those who are typically introverted also have an extroverted side that rarely finds expression unless we are relaxed and uninhibited. Each of us has both a masculine and feminine side, but in younger years, we feel societal pressure to give expression only to one. As we get older, we may become freer to express all of our traits as the situation arises. We find gender convergence in older adults. Men become more interested in intimacy and family ties. Women may become more assertive. This gender convergence is also affected by changes in society’s expectations for males and females. With each new generation we find that the roles of men and women are less stereotypical, and this allows for change as well.

Subjective Aging

One aspect of the self that particularly interests life span and life course psychologists is the individual’s perception and evaluation of their own aging and identification with an age group. Subjective age is a multidimensional construct that indicates how old (or young) a person feels, and into which age group a person categorizes themself. After early adulthood, most people say that they feel younger than their chronological age, and the gap between subjective age and actual age generally increases. On average, after age 40 people report feeling 20% younger than their actual age (e.g., Rubin & Berntsen, 2006). Asking people how satisfied they are with their own aging assesses an evaluative component of age identity. Whereas some aspects of age identity are positively valued (e.g., acquiring seniority in a profession or becoming a grandparent), others may be less valued, depending on societal context. Perceived physical age (i.e., the age one looks in a mirror) is one aspect that requires considerable self-related adaptation in social and cultural contexts that value young bodies. Feeling younger and being satisfied with one’s own aging are expressions of positive self-perceptions of aging. They reflect the operation of self-related processes that enhance well-being. Levy (2009) found that older individuals who are able to adapt to and accept changes in their appearance and physical capacity in a positive way report higher well-being, have better health, and live longer.

There is now an increasing acceptance of the view within developmental psychology that an uncritical reliance on chronological age may be inappropriate. People have certain expectations about getting older, their own idiosyncratic views, and internalized societal beliefs. Taken together they constitute a tacit knowledge of the aging process. A negative perception of how we are aging can have real results in terms of life expectancy and poor health. Levy et al (2002) estimated that those with positive feelings about aging lived 7.5 years longer than those who did not. Subjective aging encompasses a wide range of psychological perspectives and empirical research. However, there is now a growing body of work centered around a construct referred to as Awareness of Age Related Change (AARC) (Diehl et al, 2015), which examines the effects of our subjective perceptions of age and their consequential, and very real, effects. Neuport & Bellingtier (2017) report that this subjective awareness can change on a daily basis, and that negative events or comments can disproportionately affect those with the most positive outlook on aging.

Work Satisfaction

Middle adulthood is characterized by a time of transition, change, and renewal. Accordingly, attitudes about work and satisfaction from work tend to undergo a transformation or reorientation during this time. Age is positively related to job satisfaction—the older we get the more we derive satisfaction from work(Ng & Feldman, 2010). [2] However, that is far from the entire story and repeats, once more, the paradoxical nature of the research findings from this period of the life course. Dobrow, Gazach & Liu (2018) found that job satisfaction in those aged 43-51 was correlated with advancing age, but that there was increased dissatisfaction the longer one stayed in the same job. Again, as socio-emotional selectivity theory would predict, there is a marked reluctance to tolerate a work situation deemed unsuitable or unsatisfying. Years left, as opposed to years spent, necessitates a sense of purpose in all daily activities and interactions, including work. [3]

The workplace today is one in which many people from various walks of life come together. Work schedules are more flexible and varied, and more work independently from home or anywhere there is an internet connection. The midlife worker must be flexible, stay current with technology, and be capable of working within a global community.

Seeking job enjoyment may account for the fact that many people over 50 sometimes seek changes in employment known as “ encore careers .” Some midlife adults anticipate retirement, while others may be postponing it for financial reasons, or others may simple feel a desire to continue working.

You can view the transcript for “Boomers Find Second Act in “Encore” Careers (7/26/13)” here (opens in new window) .

Relationships at Work

Working adults spend a large part of their waking hours in relationships with coworkers and supervisors. Because these relationships are forced upon us by work, researchers focus less on their presence or absence and instead focus on their quality. High quality work relationships can make jobs enjoyable and less stressful. This is because workers experience mutual trust and support in the workplace to overcome work challenges. Liking the people we work with can also translate to more humor and fun on the job. Research has shown that supervisors who are more supportive have employees who are more likely to thrive at work (Paterson, Luthans, & Jeung, 2014; Monnot & Beehr, 2014; Winkler, Busch, Clasen, & Vowinkel, 2015). On the other hand, poor quality work relationships can make a job feel like drudgery. Everyone knows that horrible bosses can make the workday unpleasant. Supervisors that are sources of stress have a negative impact on the subjective well-being of their employees (Monnot & Beehr, 2014). Specifically, research has shown that employees who rate their supervisors high on the so-called “dark triad”—psychopathy, narcissism, and Machiavellianism—reported greater psychological distress at work, as well as less job satisfaction (Mathieu, Neumann, Hare, & Babiak, 2014).

In addition to the direct benefits or costs of work relationships on our well-being, we should also consider how these relationships can impact our job performance. Research has shown that feeling engaged in our work and having a high job performance predicts better health and greater life satisfaction (Shimazu, Schaufeli, Kamiyama, & Kawakami, 2015). Given that so many of our waking hours are spent on the job—about 90,000 hours across a lifetime—it makes sense that we should seek out and invest in positive relationships at work.

One of the most influential researchers in this field, Dorien Kooij (2013) identified four key motivations in older adults continuing to work. First, growth or development motivation- looking for new challenges in the work environment. The second are feelings of recognition and power. Third, feelings of power and security afforded by income and possible health benefits. Interestingly enough, the fourth area of motivation was Erikson’s generativity. The latter has been criticized for a lack of support in terms of empirical research findings, but two studies (Zacher et al, 2012; Ghislieri & Gatti, 2012) found that a primary motivation in continuing to work was the desire to pass on skills and experience, a process they describe as leader generativity . Perhaps a more straightforward term might be mentoring. In any case, the concept of generative leadership is now firmly established in the business and organizational management literature.

Organizations, public and private, are going to have to deal with an older workforce. The proportion of people in Europe over 60 will increase from 24% to 34% by 2050 (United Nations 2015), the US Bureau of Labor Statistics predicts that 1 in 4 of the US workforce will be 55 or over. Workers may have good reason to avoid retirement, although it is often viewed as a time of relaxation and well-earned rest, statistics may indicate that a continued focus on the future may be preferable to stasis, or inactivity. In fact, Fitzpatrick & Moore (2018) report that death rates for American males jump 2% immediately after they turn 62, most likely a result of changes induced by retirement. Interestingly, this small spike in death rates is not seen in women, which may be the result of women having stronger social determinants of health (SDOH), which keep them active and interacting with others out of retirement.

https://assessments.lumenlearning.co...essments/16646

[glossary-page] [glossary-term]leader generativity:[/glossary-term] [glossary-definition]mentoring and passing on off skills and experience that older adults can provide at work to feel motivated[/glossary-definition]

[glossary-term]plaster hypothesis:[/glossary-term] [glossary-definition]the belief that personality is set like plaster by around the age of thirty[/glossary-definition] [/glossary-page]

• Roberts, B. W., Wood, D., & Caspi, A. (2008). The development of personality traits in adulthood. In O. P. John, R. W. Robins, & L.A. Pervin (Eds.),Handbook of personality: Theory and research(Vol.3, pp. 375–398). New York: Guilford. ↵
• (Ng & Feldman (2010) The relationship of age with job attitudes: a meta analysis Personnel Psychology 63 677-715 ↵
• Riza, S., Ganzach, Y & Liu Y (2018) Time and job satisfaction: a longitudinal study of the differential roles of age and tenure Journal of Management 44,7 2258-2579 ↵

Contributors and Attributions

• Modification, adaptation, and original content. Authored by : Ronnie Mather for Lumen Learning. Provided by : Lumen Learning. License : CC BY: Attribution
• Psyc 200 Lifespan Psychology. Authored by : Laura Overstreet. Located at : http://opencourselibrary.org/econ-201/ . License : CC BY: Attribution
• Work relationships. Authored by : Kenneth Tan and Louis Tay . Provided by : Purdue University. Located at : https://nobaproject.com/modules/relationships-and-well-being . License : CC BY-NC-SA: Attribution-NonCommercial-ShareAlike
• Work birthday party. Authored by : Bart Everson. Provided by : Flickr. Located at : https://www.flickr.com/photos/11018968@N00/3330917965/ . License : CC BY: Attribution
• Sections on personality and subjective aging. Authored by : Tara Queen and Jacqui Smith. Provided by : University of Michigan. Located at : https://nobaproject.com/modules/aging . Project : The Noba Project. License : CC BY-NC-SA: Attribution-NonCommercial-ShareAlike
• Boomers Find Second Act in Encore Careers (7/26/13). Provided by : NBRbizrpt. Located at : https://www.youtube.com/watch?time_continue=1&v=UMIFOSrzmNM . License : Other . License Terms : Standard YouTube License
• Authored by : OmarMedinaFilms. Provided by : Needpix. Located at : https://www.needpix.com/photo/download/1230837/adult-music-microphone-sound-i-am-a-student-musician-instruments-band-concert . License : CC0: No Rights Reserved

Chapter 9: Middle Adulthood

Learning Objectives

At the end of this chapter, you will be able to:

• Identify the characteristics of middle adulthood physical and cognitive development.
• Describe the characteristics associated with middle adulthood psychosocial development.
• Recognize how culture plays a role in middle adulthood development.
• Interpret the theoretical development stages that take place during middle adulthood.
• Discuss the common factors associated with academic or career achievement for middle adulthood and the potential barriers they face to success.

Defining Middle Adulthood

Middle adulthood , or midlife, is the period between early and late adulthood. The general age range for this stage is from 40-45 to 60-65, but this can vary based on cultural definitions and expectations. Although research on this developmental period is relatively new, it is an essential stage of life that reflects both developmental gains and losses, and it is currently being studied in more detail. As the large Baby Boom cohort (those born between 1946 and 1964) is now in this stage of life, there has been an increased interest in understanding this critical developmental stage.

While getting out of shape is often associated with aging, it is not inevitable. Physical inactivity, stress, smoking, drinking, poor diet, and chronic diseases such as diabetes and arthritis can all contribute to a decline in overall health. However, adopting healthier lifestyles can help combat many of these changes.

Specific physiological changes are likely to occur in middle adulthood, but regular physical activity can help combat them. Exercise doesn’t have to be intense; even brisk walking thirty minutes daily can make a significant difference. “Use it or lose it” is a good mantra for this stage of development, as the body begins to lose muscle mass and function as we age (known as sarcopenia). From the age of 30, the body loses between 3-8% of muscle mass each decade, and this rate accelerates after the age of 60. However, diet and exercise can help reduce the extent of these changes and their consequences. This section will explore some changes during middle adulthood and discuss how they can impact our daily lives.

Louisiana Snapshot

It Must Be the Humidity

It is stated that high humidity levels can provide many benefits, one in particular, the appearance of anti-aging (Asarch & Asarch, 2022). With consistent exposure to humidity, one’s skin receives enough hydration to remain supple and youthful. Well, one can assume Louisiana’s humidity level must be significant in midlifers looking young as if aging has been paused. Although it may seem like their facial appearance has gone in reverse, their lives continue to move forward in various directions, which can result in sudden and drastic changes.

What Types of Physical Development Are Experienced during Middle Adulthood?

The importance of avoiding a sedentary lifestyle was apparent to Hippocrates in 400 BCE and remains relevant today. Piasecki et al. (2018) suggest that sarcopenia , the loss of muscle tissue and function as we age, may be caused by leg muscles becoming disconnected from the nervous system. However, exercise can encourage new nerve growth, slowing the progression of sarcopenia. By age 75, individuals may have up to 30-60% fewer nerve endings in their leg muscles than in their early 20s.

Although it has only been recognized as an independent disease entity since 2016 (ICD-10), sarcopenia was already assigned its medical code by the Centers for Disease Control and Prevention in 2018. Mobility-related diseases will become increasingly costly and affect the quality of life for many people as the population ages. While some doctors and researchers have hesitated to pathologize natural aging changes, mobility is becoming a central concern. Researchers have even identified new conditions such as osteosarcopenia, which describes the decline of muscle tissue (sarcopenia) and bone tissue (osteoporosis). As the costs of caring for those with mobility issues become apparent, diagnoses and pharmaceuticals that deal with the central question of mobility will become ever more critical.

Human beings reach peak bone mass around ages 35-40, and osteoporosis , a “silent disease” that progresses until a fracture occurs, can become a significant problem. It is often associated with women because bone mass can deteriorate in women much more quickly during middle age due to menopause. After menopause, women can lose 5-10% of bone mass per year, making it advisable to monitor calcium and Vitamin D intakes and evaluate individual risk factors. Beginning in their 60s, men and women lose bone mass at roughly the same rate. Currently, approximately 2 million American men have been diagnosed with osteoporosis, and a further 12 million are considered to be at risk, according to the National Osteoporosis Foundation.

Rheumatoid arthritis (RA) , the third most common form of arthritis, can be developed between the ages of 30 and 60. Its specific cause is unknown, but it occurs when antibodies attack normal synovial fluid in the joints, mistaking them for an alien threat. Women are affected by RA more than men, with a ratio of about 3 to 1. Women are also more likely to experience symptoms at an earlier age. The peak onset of RA for women is estimated to be in their early 40s. Hormonal changes are believed to be the cause of RA because women who are pregnant and have RA often experience temporary remission. While this condition is often associated with those in their 60s, only about a third of people with RA first experience symptoms at this age. However, the symptoms become more acute over time.

Symptoms of Rheumatoid Arthritis

• Tender, warm, swollen joints
• Symmetrical pattern of affected joints
• Joint inflammation often affects the wrist and finger joints closest to the hand
• Joint inflammation sometimes affects other joints, including the neck, shoulders, elbows, hips, knees, ankles, and feet
• Fatigue, occasional fevers, a loss of energy
• Pain and stiffness lasting for more than 30 minutes in the morning or after a long rest
• Symptoms that last for many years
• Variability of symptoms among people with the disease.

As people age, they often experience chronic inflammation that does not have a clear cause. This type of inflammation differs from the acute inflammation that occurs with infections. Inflammation is the body’s natural response to injury or harmful pathogens. However, suppose it persists for more extended periods. In that case, it can have serious health effects such as fatigue, fever, chest or abdominal pain, rashes, and increased susceptibility to diseases such as cancer, rheumatoid arthritis, and heart disease. Contributing factors to chronic inflammation include untreated acute inflammation, autoimmune disorders, long-term irritant exposure, and social isolation. Chronic inflammation has also been linked to muscle loss and chronic diseases like dementia. With the aging population, issues related to autoimmune disease, chronic inflammation, and bone mass density will become significant health and social policy concerns in the coming years.

Vision, Hearing, and Other Physical Changes

As people age, they experience some changes in their physical condition that are primarily biological. These changes include problems with vision and hearing, joint pain, and weight gain (Lachman, 2004). Aging affects sight, as the eye’s lens gets larger but loses some flexibility to adjust to visual stimuli. This is called presbyopia, often making it difficult for middle-aged adults to see things up close. Night vision is also affected, as the pupil loses its ability to open and close to accommodate changes in light.

Presbycusis is the primary cause of hearing loss, with one in four people between ages 65 and 74 and one in two by age 75 being affected. This condition occurs after years of exposure to intense noise levels, leading to the loss or damage of nerve hair cells within the cochlea. Men are more likely to develop hearing loss due to their higher likelihood of working in noisy environments (NIDCD, n.d.). Smoking, high blood pressure, and stroke can exacerbate hearing loss, with high-frequency sounds being the first to be affected. To prevent hearing loss, avoiding exposure to boisterous environments is essential.

Weight gain is one of the most common complaints of middle-aged adults, with many experiencing what is known as the “middle-aged spread” or the accumulation of fat in the abdomen. Men accumulate fat on their upper abdomen and back, while women get more fat on their waist and upper arms. The metabolism slows by about one-third during midlife, so many middle-aged adults are surprised by the weight gain despite eating the same diet (Berger, 2005). To maintain their earlier physique, midlife adults need to increase their level of exercise, eat less, and watch their nutrition.

Most changes during midlife can be easily compensated for, such as buying glasses, exercising, and watching what one eats. However, the percentage of adults who have a disability increases through midlife. While 7 percent of people in their early 40s have a disability, the rate jumps to 30 percent by the early 60s. Those of lower socioeconomic status are likelier to experience such an increase (Bumpass & Aquilino, 1995).

What Can We Conclude from This Information?

How we live our lives can significantly impact our health, especially during midlife. Habits such as smoking, drinking, unhealthy eating, stress, lack of physical exercise, and chronic illnesses like diabetes or arthritis can all reduce our overall health. Therefore, midlife adults must take preventative measures to improve their physical well-being. Those with a strong sense of control over their lives, engaging in challenging physical and mental activities, participating in weight-bearing exercises, monitoring their nutrition, and using social resources are most likely to enjoy good health throughout these years. According to Saint-Maurice et al. (2019), even those who begin exercising in their 40s can enjoy the same benefits as those who started in their 20s. Additionally, it’s never too late to begin, and maintaining healthy habits is just as crucial as starting them in the first place.

What Are Some Normal Physiological Changes in Middle Adulthood?

The climacteric.

One of the biological changes that occurs during midlife is known as the climacteric . It is a period where men may experience a reduction in their reproductive ability, while women lose their capacity to reproduce completely after reaching menopause. The climacteric is a natural process that marks the end of the reproductive phase of human life.

Menopause refers to a period of transition in which a woman’s ovaries stop releasing eggs, and the level of estrogen and progesterone production decreases (Figure 9.1). After menopause, a woman’s menstruation ceases (National Institution of Health, 2007).

Changes typically occur between the mid-40s and mid-50s. The median age range for a woman to have her last menstrual period is 50-52, but ages vary. A woman may first notice that her periods are more or less frequent than before. These changes in menstruation may last from 1 to 3 years. After a year without menstruation, a woman is considered menopausal and no longer capable of reproduction. (Keep in mind that some women, however, may experience another period even after going for a year without one.) The loss of estrogen also affects vaginal lubrication, which diminishes and becomes waterier. The vaginal wall also becomes thinner and less elastic.

Menopause is not seen as universally distressing (Lachman, 2004). Changes in hormone levels are associated with hot flashes and sweats in some women, but women vary in the extent to which these are experienced. Depression, irritability, and weight gain are not necessarily due to menopause (Rossi, 2019). Depression and mood swings are more common during menopause in women who have prior histories of these conditions rather than those who have not. The incidence of depression and mood swings is not greater among menopausal women than non-menopausal women.

Cultural influences impact how menopause is experienced. For example, a classroom study found that after listing the symptoms of menopause in a psychology course, a woman from Kenya responded that those symptoms are not prevalent in her country, which represents cultural variations in menopausal symptoms. Another example shows that hot flashes are experienced by 75 percent of women in Western cultures but by less than 20 percent of women in Japan (Berk, 2007).

Women in the United States respond differently to menopause depending on their expectations for themselves and their lives. African-American and Mexican-American women, in association with White women who are career-focused overall, tend to think of menopause as a liberating experience. Nevertheless, there has been a widespread tendency to erroneously attribute frustrations and irritations expressed by women of menopausal age to menopause and thereby not take her concerns seriously. Fortunately, many practitioners in the United States today are normalizing rather than pathologizing menopause.

Do Males Experience a Climacteric?

Yes. While they do not lose their ability to reproduce as they age, they tend to produce lower testosterone levels and fewer sperm. However, men are capable of reproduction throughout life after puberty. It is natural for sex drive to diminish slightly as men age, but a lack of sex drive may be a result of low levels of testosterone.

Low levels of testosterone result in symptoms such as a loss of interest in sex, loss of body hair, difficulty achieving or maintaining an erection, loss of muscle mass, and breast enlargement. This decrease in libido and lower testosterone (androgen) levels is known as andropause , although this term is somewhat controversial as this experience is not delineated, as menopause is for women. Low testosterone levels may be due to glandular diseases such as testicular cancer. Testosterone levels can be tested; if they are low, men can be treated with testosterone replacement therapy. This can increase sex drive, muscle mass, and beard growth. However, long-term HRT (Hormone Replacement Therapy) for men can increase the risk of prostate cancer (Patient Education Institution, n.d.).

The debate around declining testosterone levels in men may hide a fundamental fact. The issue is not about individual males experiencing individual hormonal changes at all. We have all seen adverts on the media promoting substances to boost testosterone: “Is it low-T?” The answer is probably in the affirmative, if somewhat relative. That is, in all likelihood, they will have lower testosterone levels than their fathers. However, it is equally likely that the issue does not lie solely in their physiological makeup but is rather a generational transformation (Travison et al., 2007). Why this has occurred in such a dramatic fashion is still unknown. There is evidence that low testosterone may have adverse health effects on men. In addition, some studies show evidence of rapidly decreasing sperm count and grip strength. Exactly why these changes are happening is unknown and will likely involve more than one cause.

Exercise, Nutrition, and Health

The impact of exercise.

Exercise is a powerful way to combat the changes we associate with aging. Exercise builds muscle, increases metabolism, helps control blood sugar, increases bone density, and relieves stress. Unfortunately, fewer than half of midlife adults exercise, and only about 20 percent exercise frequently and strenuously enough to achieve health benefits. Many stop exercising soon after they begin an exercise program—particularly those who are very overweight. The best exercise programs are engaged regularly—regardless of the activity, but a well-rounded program that is easy to follow includes walking and weight training. Having a safe, enjoyable place to walk can make a difference in whether or not someone walks regularly. Weight lifting and stretching exercises at home can also be part of an effective program. Exercise is beneficial in reducing stress in midlife. Walking, jogging, cycling, or swimming can release the tension caused by stressors, and learning relaxation techniques can have healthful benefits. Exercise can be considered preventative health care; promoting exercise for the 78 million “baby boomers” may be one of the best ways to reduce health care costs and improve quality of life (Shure & Cahan, 1998).

Aging brings about a reduction in the number of calories a person requires. Many Americans respond to weight gain by dieting. However, eating less does not necessarily mean eating right; people often suffer from vitamin and mineral deficiencies. Very often, physicians will recommend vitamin supplements to their middle-aged patients. As stated above, chronic inflammation is now identified as one of the so-called “pillars of aging.” The link between diet and inflammation is yet unclear, but there is now some information available on the Diet Inflammation Index (Shivappa et al., 2014), which, in popular parlance, supports a diet rich in plant-based foods, healthy fats, nuts, fish in moderation, and sparing use of red meat. The ideal diet is one low in fat, low in sugar, high in fiber, low in sodium, and low in cholesterol.

Health Concerns

Heart Disease : According to the most recent National Vital Statistics Reports (Xu et al., 2016), heart disease continues to be the number one cause of death for Americans, with 23.5% of those who died in 2013. It is also the number one cause of death globally, according to the World Health Organization. (WHO, 2013). Heart disease develops slowly over time and typically appears in midlife (Hooker and Pressman, 2016).

Heart disease can include heart defects and heart rhythm problems, as well as narrowed, blocked, or stiffened blood vessels, referred to as cardiovascular disease. The blocked blood vessels prevent the body and heart from receiving adequate blood. Atherosclerosis, or a buildup of fatty plaque in the arteries, is the most common cause of cardiovascular disease. The plaque buildup thickens the artery walls and restricts the blood flow to organs and tissues. Cardiovascular disease can lead to a heart attack, chest pain (angina), or stroke (Mayo Clinic, 2014).

Symptoms of cardiovascular disease differ for men and women. Males are more likely to suffer chest pain, while women are more likely to demonstrate shortness of breath, nausea, and extreme fatigue. Symptoms can also include pain in the arms, legs, neck, jaw, throat, abdomen, or back (Mayo Clinic, 2014). According to the Mayo Clinic (2014), there are many risk factors for developing heart disease, including medical conditions such as high blood pressure, high cholesterol, diabetes, and obesity.

Other risk factors include:

• Advanced Age—increases the risk of narrowed arteries and weakened or thickened heart muscle.
• Males are at greater risk, but a female’s risk increases after menopause.
• Family History—increased risk, especially if a male parent or brother developed heart disease before age 55 or a female parent or sister developed heart disease before age 65.
• Smoking—nicotine constricts blood vessels, and carbon monoxide damages the inner lining.
• Poor Diet—a diet high in fat, salt, sugar, and cholesterol.
• Stress—unrelieved stress can damage arteries and worsen other risk factors.
• Poor Hygiene—establishing good hygiene habits can prevent viral or bacterial infections that can affect the heart. Poor dental care can also contribute to heart disease.

Hypertension, or high blood pressure, is a serious health problem when the blood flows with a greater force than usual. One in three American adults (70 million people) has hypertension, and only half have it under control (Nwankwo et al., 2013). It can strain the heart, increase the risk of heart attack and stroke, or damage the kidneys (Centers for Disease Control and Prevention, 2014). In early and middle adulthood, uncontrolled high blood pressure can also damage the brain’s white matter (axons) and may be linked to cognitive problems later in life (Maillard, 2012). Normal blood pressure is under 120/80 (see Table 1). The first number is the systolic pressure, which is the pressure in the blood vessels when the heart beats. The second number is the  diastolic pressure, which is the pressure in the blood vessels when the heart is at rest. High blood pressure is sometimes referred to as the silent killer, as most people with hypertension experience no symptoms.

Table 1.  Blood Pressure Levels

                                                        systolic pressure    diastolic pressure.

Table Source: adapted from CDC (2014c)

Risk factors for high blood pressure include:

• Family history of hypertension
• A diet that is too high in sodium, often found in processed foods, and too low in potassium.
• Sedentary lifestyle
• Too much alcohol consumption
• Tobacco use, as nicotine raises blood pressure (CDC, 2014)

Making lifestyle changes can often reduce blood pressure in many people.

Cholesterol is a waxy, fatty substance carried by lipoprotein molecules in the blood. It is created by the body to create hormones and digest fatty foods and is also found in many foods. Your body needs cholesterol, but too much can cause heart disease and stroke. Two important kinds of cholesterol are low-density lipoprotein (LDL) and high-density lipoprotein (HDL). A third type of fat is called triglycerides. Your total cholesterol score is based on all three types of lipids (see Table 3). Total cholesterol is calculated by adding HDL plus LDL plus 20% of the Triglycerides.

Table 2.            Normal Levels of Cholesterol

Cholesterol Type                                                     Normal

*Cholesterol levels are measured in milligrams (mg) of cholesterol per deciliter (dL) of blood. Source: Centers for Disease Control, (2015).

Risk factors for high cholesterol include a family history of high cholesterol, diabetes, a diet high in saturated fats, trans fats, and cholesterol, physical inactivity, and obesity. Almost 32% of American adults have high LDL cholesterol levels, and the majority do not have it under control or have made lifestyle changes.

Diabetes (Diabetes Mellitus)  is a disease in which the body does not control the amount of glucose in the blood.  This disease occurs when the body does not make enough insulin or use it as it should (National Institutions of Health, 2016). Insulin is a hormone that helps glucose in the blood enter cells to give them energy. In adults, 90% to 95% of all diagnosed cases of diabetes are type 2 (American Diabetes Association, 2014). Type 2 diabetes usually begins with insulin resistance, a disorder in which the muscles, liver, and fat tissue cells do not use insulin properly (CDC, 2014). As the need for insulin increases, cells in the pancreas gradually lose the ability to produce enough insulin. In some type 2 diabetics, pancreatic beta cells will cease functioning, and insulin injections will become necessary. Some people with diabetes experience insulin resistance with only minor dysfunction of the beta cell secretion of insulin. Other diabetics experience only slight insulin resistance, with the primary cause being a lack of insulin secretion (CDC, 2014).

Diabetes also affects ethnic and racial groups differently. Non-Hispanic Whites (7.6%) are less likely to be diagnosed with diabetes than Asian Americans (9%), Hispanics (12.8%), non-Hispanic Blacks (13.2%), and American Indians/Alaskan Natives (15.9%). However, these general figures hide the variations within these groups. For instance, the rate of diabetes was less for Central, South, and Cuban Americans than for Mexican Americans and Puerto Ricans and four times less for Alaskan Natives than the American Indians of southern Arizona (CDC, 2014).

The risk factors for diabetes include:

• Those over age 45
• Family history of diabetes
• History of gestational diabetes (see Chapter 2)
• Race and ethnicity
• Physical inactivity

Sleep problems: According to the Sleep in America (2015) poll, 9% of Americans report being diagnosed with a sleep disorder, and of those, 71% have sleep apnea, and 24% suffer from insomnia. Pain also contributes to the difference between the amount of sleep Americans need and the amount they get. An average of 42 minutes of sleep debt occurs for those with chronic pain and 14 minutes for those who have suffered from acute pain in the past week. Stress and poor health are vital to shorter sleep durations and worse sleep quality. Those in midlife with lower life satisfaction experienced more significant sleep onset delay than those with higher life satisfaction. Delayed onset of sleep could result from worry and anxiety during midlife, and improvements in those areas should improve sleep. Lastly, menopause can affect a woman’s sleep duration and quality (National Sleep Foundation, 2016).

After heart disease, cancer was the second leading cause of death for Americans in 2013, accounting for 22.5% of all deaths (Xu et al., 2016). According to the National Institutes of Health (2015),  cancer is the name given to a collection of related diseases in which the body’s cells begin to divide without stopping and spread into surrounding tissues. These extra cells can divide and form growths called tumors, which are typically masses of tissue. Cancerous tumors are malignant, which means they can invade nearby tissues. When removed, malignant tumors may grow back. Unlike malignant tumors, benign tumors do not invade nearby tissues. Benign tumors can sometimes be quite large and, when removed, usually do not grow back. Although benign tumors in the body are not cancerous, benign brain tumors can be life-threatening.

Cancer cells can prompt nearby normal cells to form blood vessels that supply the tumors with oxygen and nutrients allowing them to grow. These blood vessels also remove waste products from the tumors. Cancer cells can also hide from the immune system, a network of organs, tissues, and specialized cells that protect the body from infections and other conditions. Lastly, cancer cells can metastasize, which means they can break from where they first formed, called primary cancer, and travel through the lymph system or blood to form new tumors in other body parts. This new metastatic tumor is the same type as the primary tumor (National Institutes of Health, 2015).

What Types of Cognitive Development Are Experienced during Middle Adulthood?

While we sometimes associate aging with cognitive decline (often due to how it is portrayed in the media), aging does not necessarily mean decreased cognitive function. Tacit knowledge, verbal memory, vocabulary, inductive reasoning, and other practical thought skills increase with age. We’ll learn about these advances and some neurological changes in middle adulthood in the following section (Lumen Learning, n.d.). The cognitive mechanics of processing speed, often called fluid intelligence, physiological lung capacity, and muscle mass, are in relative decline. However, knowledge, experience, and the increased ability to regulate emotions can compensate for these losses. Continuing cognitive focus and exercise can also reduce the extent and effects of cognitive decline. There is some evidence that adults should be as aggressive in maintaining their mental health as they are in their physical health during this time, as the two are intimately related.

Control Beliefs

Central to this are personal control beliefs, which have a long history in psychology. Empirical research has shown that those with an internal locus of control enjoy better results in behavioral, motivational, and cognitive psychological tests across the board. It is reported that this belief in control declines with age, but again, there is a great deal of individual variation. This raises another issue: directional causality. Does my belief in my ability to retain my intellectual skills and abilities at this time of life ensure better performance on a cognitive test than those who believe in their inexorable decline? Or does the fact that I enjoy that intellectual competence or facility instill or reinforce that belief in control and controllable outcomes? It is not clear which factor is influencing the other. The exact nature of the connection between control beliefs and cognitive performance remains unclear (Lachman et al., 2014).

Brain science is developing exponentially and will unquestionably deliver new insights on various cognition-related issues in midlife. One of them will surely be on the brain’s capacity to renew, or at least replenish itself, at this time of life. The ability to restore is called neurogenesis; the capacity to fill what is there is called neuroplasticity. At this stage, it is impossible to ascertain what effect future pharmacological interventions may have on the possible cognitive decline at this and later stages of life.

Cognitive Aging

Researchers have identified areas of loss and gain in cognition in older age. Cognitive ability and intelligence are often measured using standardized tests and validated measures. The psychometric approach has identified two categories of intelligence that show different rates of change across the life span (Schaie & Willis, 1996). Fluid and crystallized intelligence were first identified by Cattell in 1971.  Fluid intelligence refers to information processing abilities, such as logical reasoning, remembering lists, spatial ability, and reaction time. Crystallized intelligence encompasses abilities that draw upon experience and knowledge.

Heredity, culture, social contexts, personal choices, and age influence intelligence. One distinction in specific intelligence noted in adulthood is between fluid intelligence, which refers to the capacity to learn new ways of solving problems and performing activities quickly and abstractly, and crystallized intelligence, which refers to the accumulated knowledge of the world we have acquired throughout our lives (Salthouse, 2004). These intelligences are distinct; crystallized intelligence increases with age, while fluid intelligence decreases.

Measures of crystallized intelligence include vocabulary tests, solving number problems, and understanding texts. There is a general acceptance that fluid intelligence has decreased continually since the 20s but that crystallized intelligence continues to accumulate. One might expect to complete an extensive crossword more quickly at 48 than 22, but the capacity to deal with novel information declines.

With age, systematic declines are observed in cognitive tasks requiring self-initiated, effortful processing without supportive memory cues (Park, 2000). Older adults tend to perform poorer than young adults on memory tasks that involve recall of information, where individuals must retrieve information they learned previously without the help of a list of possible choices. For example, older adults may have more difficulty recalling facts such as names or contextual details about where or when something happened (Craik, 2000). What might explain these deficits as we age?

As we age, working memory, or our ability to simultaneously store and use information, becomes less efficient (Craik & Bialystok, 2006). The ability to process information quickly also decreases with age. This slowing of processing speed may explain age differences in many cognitive tasks (Salthouse, 2004). Some researchers have argued that inhibitory functioning, or the ability to focus on specific information while suppressing attention to less pertinent information, declines with age and may explain age differences in performance on cognitive tasks (Hasher & Zacks, 1988).

Fewer age differences are observed when memory cues are available, such as for recognizing memory tasks or when individuals can draw upon acquired knowledge or experience. For example, older adults often perform as well, if not better, than young adults on tests of word knowledge or vocabulary. Age usually comes with expertise, and research has pointed to areas where aging experts perform as well or better than younger individuals. For example, older typists were found to compensate for age-related declines in speed by looking farther ahead at printed text (Salthouse, 1984). Compared to younger players, more senior chess experts can focus on a smaller set of possible moves, leading to greater cognitive efficiency (Charness, 1981). Accrued knowledge of everyday tasks, such as grocery prices, can help older adults make better decisions than young adults (Tentori et al., 2001).

This video highlights cognitive changes during adulthood and the characteristics that either decline, improve, or remain stable.

Transcript for “Aging and cognitive abilities ”

Performance in Middle Adulthood

Research on interpersonal problem-solving suggests that older adults use more effective strategies than younger adults to navigate social and emotional problems (Blanchard-Fields, 2007). In the context of work, researchers rarely find that older individuals perform less well on the job (Park & Gutchess, 2000). Older workers may develop more efficient strategies and rely on expertise like everyday problem-solving to compensate for cognitive decline.

Given their nature, empirical studies of cognitive aging are often tricky and technical. Similarly, experiments focused on one task may tell you little about general capacities. Memory and attention as psychological constructs are now divided into specific subsets, which can be confusing and difficult to compare.

However, one study does show with relative clarity the issues involved. In the USA, the Federal Aviation Authority insists that all air traffic controllers retire at 56 and cannot begin until age 31 unless they have previous military experience. However, in Canada, controllers are allowed to work until age 65 and are allowed to train at a much earlier age. Nunes and Kramer (2009) studied four groups: a younger group of controllers (20-27), an older group of controllers aged 53 to 64,  and two other groups of the same age who were not air traffic controllers. Older controllers were slower than their younger peers on simple cognitive tasks unrelated to their occupational lives as controllers. However, when it came to job-related tasks, their results were essentially identical. This was not true of the older group of non-controllers, who had significant deficits in comparison. Specific knowledge or expertise in a domain acquired over time (crystallized intelligence) can offset a decline in fluid intelligence.

Tacit Knowledge

The idea of tacit knowledge was first introduced by Michael Polanyi in 1967. Tacit knowledge is pragmatic or practical knowledge learned through experience rather than explicitly taught , and it also increases with age (Hedlund et al., 2002). Tacit knowledge might be considered “know-how” or “professional instinct.” It is called tacit because it cannot be codified or written down. It does not involve academic knowledge, but rather, it consists of using skills and problem-solving in practical ways. Tacit knowledge can be understood in the workplace and used by blue-collar workers, such as carpenters, chefs, and hairdressers.

Think of someone you have encountered who is extremely good at what they do. They may have no more (or less) education, formal training, and experience than others who are supposedly at an equivalent level. What is the “something” that they have? Tacit knowledge is highly prized, and older workers often have the most significant amount, even if they are not conscious of that fact.

Middle Adults Returning to Education

Midlife adults in the United States often find themselves in college classrooms. The enrollment rate for older Americans entering college, often part-time or in the evenings, is rising faster than traditionally aged students. Students over age 35 accounted for 17% of all college and graduate students in 2009 and are expected to comprise 19% by 2020 (Holland, 2014). According to the American Association of Community Colleges (2022), students aged 22-39 make up 36% of enrollments, whereas those aged 40+ make up 8%. In some cases, older students are developing skills and expertise to launch a second career or to take their career in a new direction. Whether they enroll in school to sharpen particular skills, to retool and reenter the workplace, or to pursue interests that have previously been neglected, older students tend to approach the learning process differently than younger college students (Knowles et al., 1998).

The mechanics of cognition, such as working memory and processing speed, gradually decline with age. However, they can be easily compensated for through higher-order cognitive skills, such as forming strategies to enhance memory or summarizing and comparing ideas rather than relying on rote memorization (Lachman, 2004). Although older students may take longer to learn the material, they are less likely to forget it quickly. Adult learners tend to look for relevance and meaning when learning information. Older adults have the most challenging time learning meaningless or unfamiliar material. They are more likely to ask themselves, “Why is this important?” when being introduced to information or trying to memorize concepts or facts. Older adults are more task-oriented learners and want to organize their activities around problem-solving. However, these differences may decline as new generations of higher education enter midlife.

What Are Some Psychosocial Experiences That Occur during Middle Adulthood?

In the popular imagination (and academic press), middle adulthood has been referenced as a “midlife crisis,” which is an emotional crisis of identity and self-confidence that can occur in early middle age. There is an emerging view that this may have been an overstatement—indeed, the evidence on which it is based has been seriously questioned. However, there is some support for the view that people do undertake a sort of emotional audit, reevaluate their priorities, and emerge with a slightly different orientation to emotional regulation and personal interaction at this time. Why and the mechanisms through which this change is affected are a matter of debate. We will examine the ideas of Erikson, Baltes, and Carstensen and how they might inform a more nuanced understanding of this vital part of the lifespan (Lumen Learning, n.d.).

What do you think is the happiest stage of life (Lumen Learning, n.d.)? What about the saddest stages? Perhaps surprisingly, Blanchflower & Oswald (2008) found that reported levels of unhappiness and depressive symptoms peak in the early 50s for men in the U.S. and, interestingly, in the late 30s for women. In Western Europe, minimum happiness is reported around the mid-40s for both men and women, albeit with some significant national differences. There is now a view that “older people” (50+) may be “happier” than younger people despite some cognitive and functional losses. This is often referred to as “the paradox of aging.” Positive attitudes to the continuance of mental and behavioral activities, interpersonal engagement, and their vitalizing effect on human neural plasticity may lead to more life and an extended period of self-satisfaction and continued communal engagement.

Erikson’s Theory

As you know by now, Erikson’s theory is based on epigenesis, meaning that development is progressive and that each individual must pass through the eight different stages of life—all while being influenced by context and environment. Each stage forms the basis for the following stage, and each transition to the next is marked by a crisis that must be resolved. The sense of self, each “season,” was wrested from by that conflict. The ages 40-65 are no different. The individual is still driven to engage productively, but nurturing children and income generation assume lesser functional importance. From where will the individual derive their sense of self and self-worth?

Generativity versus stagnation is Erikson’s characterization of the fundamental conflict of adulthood. It is the seventh conflict of his famous “8 Seasons of Man” (1950), and negotiating this conflict results in the virtue of care. Generativity is “primarily concerned with establishing and guiding the next generation.” Generativity concerns a generalized other (as well as those close to an individual) and occurs when a person can shift their energy to care for and mentor the next generation. One apparent motive for this generative thinking might be parenthood, but others have suggested intimations of mortality by the self. John Kotre (1950) theorized that generativity is selfish, stating that its fundamental task was to outlive the self. He viewed generativity as a form of investment. This form of investment can often be seen through volunteering. However, a commitment to a “belief in the species” can be taken in numerous directions, and it is probably correct to say that most modern treatments of generativity treat it as a collection of facets or aspects—encompassing creativity, productivity, commitment, interpersonal care, and so on.

On the other side of generativity is  stagnation , which refers to lethargy and a lack of enthusiasm and involvement in individual and communal affairs. It may also denote an underdeveloped sense of self or some form of overblown narcissism. Erikson sometimes used the word “rejectivity” when referring to severe stagnation.

This video explains the midlife crisis.

Transcript for “Does Everyone Have a ‘Midlife Crisis’?”

Socioemotional Selectivity Theory (SST)

It is the inescapable fate of human beings to know that their lives are limited. As people move through life, goals and values tend to shift. What we consider priorities, goals, and aspirations are subject to renegotiation. Attachments to others, current and future, are no different. Time is not the unlimited good perceived by a child under normal social circumstances; it is very much a valuable commodity, requiring careful consideration in terms of the investment of resources. This has become known in academic literature as mortality salience.

Mortality salience posits that reminders about death or finitude (at either a conscious or subconscious level) fill us with dread. We seek to deny its reality, but awareness of the increasing nearness of death can potentially affect human judgment and behavior. This has become a critical concept in contemporary social science. With this understanding, Laura Carstensen developed the socioemotional selectivity theory, or SST . The SST maintains that as time horizons shrink, as they typically do with age, people become increasingly selective, investing more significant resources in emotionally meaningful goals and activities . According to the theory, motivational shifts also influence cognitive processing. Aging is associated with a relative preference for positive over negative information. This selective narrowing of social interaction maximizes positive emotional experiences and minimizes emotional risks as individuals age. They systematically hone their social networks so that available social partners satisfy their emotional needs. An adaptive way of maintaining a positive effect might be to reduce contact with those we know may negatively affect us and avoid those who might.

Watch Laura Carstensen explain how happiness increases with age.

Transcript for “Older people are happier – Laura Carstensen.”

Selection, Optimization, Compensation (SOC)

Another perspective on aging was identified by German developmental psychologists Paul and Margret Baltes. Their text Successful Aging (1990) marked a seismic shift in moving social science research on aging from a broadly deficits-based perspective to a newer understanding based on a holistic life course. The former focused exclusively on what was lost during the aging process rather than seeing it as a balance between those losses and gains in areas like regulating emotion, experience, and wisdom.

The Baltes’ model for successful aging argues that people face various opportunities or challenges across the lifespan, such as jobs, educational opportunities, and illnesses. According to the SOC model, a person may select particular goals or experiences, or circumstances might impose themselves on them. Either way, the selection process includes shifting or modifying goals based on choice or circumstance in response to those circumstances.

The change in direction may occur at the subconscious level. This model emphasizes that setting goals and directing efforts towards a specific purpose benefit healthy aging. Optimization is about making the best use of our resources to pursue goals. Compensation, as its name suggests, is about using alternative strategies to attain those goals (Baltes & Baltes, 1990).

The selection, optimization, and compensation processes can be found throughout the lifespan. As we progress in years, we select areas where we place resources, hoping that this selection will optimize our resources and compensate for any defects accruing from physiological or cognitive changes. The work of Paul and Margaret Baltes was very influential in forming a comprehensive developmental perspective that would merge around the central idea of resiliency (Weiss, Westerhof & Bohmeijer, 2016).

The SOC model covers several functional domains—motivation, emotion, and cognition. We might become more adept at playing the SOC game as time passes, as we work to compensate and adjust for changing abilities across the lifespan.

Social Relationships and Stress

Research has shown that the impact of social isolation on our risk for disease and death is similar in magnitude to the risk associated with smoking regularly (Holt-Lunstad, Smith, & Layton, 2010). The importance of social relationships for our health is so significant that some scientists believe our body has developed a physiological system that encourages us to seek out our relationships, especially in times of stress (Taylor et al., 2000).  Social integration is the concept used to describe the number of social roles you have (Cohen & Willis, 1985).

Maintaining these different roles can improve your health by encouraging those around you to maintain a healthy lifestyle. Those in your social network might also provide you with social support (e.g. when you are under stress). This support might include emotional help (e.g., a hug when needed), tangible help (e.g., lending money), or advice. By helping to improve health behaviors and reduce stress, social relationships can have a powerful, protective impact on health and, in some cases, might even help people with serious illnesses stay alive longer (Spiegel et al., 1989).

Caregiving and Stress

A disabled child, spouse, parent, or other family member is part of the lives of some midlife adults. According to the National Alliance for Caregiving (2015), 40 million Americans provide unpaid caregiving. The typical caregiver is a 49-year-old female currently caring for a 69-year-old female who needs care because of a long-term physical condition. Looking more closely at the age of the recipient of caregiving, the typical caregiver for those 18-49 years of age is a female (61%), mainly caring for her child (32%), followed by a spouse or partner (17%). When looking at older recipients (50+) who receive care, the typical caregiver is female (60%) caring for a parent (47%) or spouse (10%).

Caregiving places enormous stress on the caregiver. Caregiving for a young or adult child with special needs was associated with poorer global health and more physical symptoms among both fathers and mothers (Seltzer et al., 2011). Marital relationships are also a factor in how caring affects stress and chronic conditions. Fathers who were caregivers identified more chronic health conditions than non-caregiving fathers, regardless of marital quality. In contrast, caregiving mothers reported higher levels of chronic conditions when they reported a high level of marital strain (Kang & Marks, 2014). Age can also affect how one is affected by the stress of caring for a child with special needs. Using data from the Study of Midlife in the United States, Ha, Hong, Seltzer, and Greenberg (2008) found that older parents were significantly less likely to experience the adverse effects of having a disabled child than younger parents. They concluded that an age-related weakening of the stress occurred over time. This is followed by the greater emotional stability noted at midlife.

Currently, 25% of adult children, mainly baby boomers, provide personal or financial care to a parent (Metlife, 2011). Daughters are more likely to provide primary care, and sons are more likely to provide financial assistance. Adult children 50+ who work and provide care to a parent are more likely to have fair or poor health when compared to those who do not provide care. Some adult children choose to leave the workforce. However, the cost of leaving the workforce early to care for a parent is high. For females, lost wages and social security benefits equals $324,044, while for men, it equals $283,716 (Metlife, 2011). This loss can jeopardize the adult child’s financial future. Consequently, there is a need for greater workplace flexibility for working caregivers.

Spousal Care

Indeed, caring for a disabled spouse would be a demanding experience that could negatively affect one’s health. However, research indicates that there can be positive health effects for caring for a disabled spouse. Beach, Schulz, Yee, and Jackson (2000) evaluated health-related outcomes in four groups: Spouses with no caregiving needed (Group 1), living with a disabled spouse but not providing care (Group 2), living with a disabled spouse and providing care (Group 3), and helping a disabled spouse while reporting caregiver strain, including elevated levels of emotional and physical stress (Group 4). Not surprisingly, the participants in Group 4 were the least healthy and identified poorer perceived health, an increase in health-risk behaviors, and an increase in anxiety and depression symptoms. However, those in Group 3 who provided care for a spouse but did not identify caregiver strain identified decreased levels of anxiety and depression compared to Group 2 and were similar to those in Group 1. It appears that greater caregiving involvement was related to better mental health as long as the caregiving spouse did not feel the strain. The beneficial effects of helping identified by the participants were consistent with previous research (Schulz et al., 1997).

When caring for a disabled spouse, gender differences have also been identified. Female caregivers of a spouse with dementia experienced more burden, had poorer mental and physical health, exhibited increased depressive symptomatology, took part in fewer health-promoting activities, and received fewer hours of help than male caregivers (Gibbons et al., 2014). This recent study was consistent with previous research findings that women experience more caregiving burden than men despite similar caregiving situations (Yeager et al., 2010). Explanations for why women do not use more external support, which may alleviate some of the burden, include women’s expectations that they should assume caregiving roles (Torti et al., 2004) and their concerns with the opinions of others (Arai, 2000). Also contributing to women’s poorer caregiving outcomes is that disabled males are more aggressive than females, especially males with dementia, who display more physical and sexual aggression toward their caregivers (Zuidema, 2009). Female caregivers are certainly at risk for adverse consequences of caregiving, and greater support needs to be available to them.

Working in Midlife

The U.S. workforce comprises civilian, non-institutionalized people aged 16 and above who are employed. Since the late 1990s, the percentage of the population has been steadily declining. In 1999, the percentage of employed people peaked at 67%. However, by 2012, it had dropped to 64%, and as of 2021, it had further decreased to 58% (Monthly Labor Review, 2021). It is important to note that the COVID-19 pandemic in 2020 has also impacted these figures.

Additionally, there has been a rise in the percentage of the population aged 55 and above. In 1992, this percentage was 26%, which grew to 29.3% in 2019. This figure is projected to rise to 32.6% by 2040 (U.S. Census Bureau, Population Division, 2017). The table below shows the employment rates by age, and as of 2021, approximately 64% of the workforce is male. The participation rate in the labor force has improved for both genders and age groups from 2011 to 2021.

Table—Percentage of the non-institutionalized civilian workforce employed by gender & age.

2011 (Men) 2021 (Men) 2011 (Women) 2021 (Women)

*Adapted from Monthly Labor Review.

What Is the Climate in the Workplace for Middle-Aged Adults?

Several studies have found job satisfaction peaks in middle adulthood (Besen et al., 2013). This satisfaction stems from higher wages and often greater involvement in decisions that affect the workplace as they move from worker to supervisor or manager. Job satisfaction is also influenced by being able to do the job well, and after years of experience at a job, many people are more effective and productive. Another reason for this peak in job satisfaction is that at midlife, many adults lower their expectations and goals (Tangri, Thomas, & Mednick, 2003). Middle-aged employees may realize they have reached the highest they are likely to in their careers. This satisfaction at work translates into lower absenteeism, greater productivity, and less job hopping compared to younger adults (Easterlin, 2006).

However, not all middle-aged adults are happy in the workplace. Women may find themselves up against the glass ceiling of organizational discrimination in the workplace that limits their career advancement. This may explain why females employed at large corporations are twice as likely to quit their jobs as men (Barreto, Ryan, & Schmitt, 2009). Another problem older workers may encounter is job burnout, becoming disillusioned and frustrated at work. American workers may experience more burnout than workers in many other developed nations because most developed nations guarantee a set number of paid vacation days by law (International Labor Organization, 2011). In contrast, the United States does not (U.S. Dept. of Labor, 2016).

What Are the Challenges in the Workplace for Middle-Aged Adults?

In recent years, middle-aged adults have been challenged by economic downturns, starting in 2001 and again in 2008. Fifty-five percent of adults reported some problems in the workplace, such as fewer hours, pay cuts, having to switch to part-time, etc., during the most recent economic recession (see Figure) (Pew Research Center, 2010a). While young adults took the biggest hit in terms of levels of unemployment, middle-aged adults also saw their overall financial resources suffer as their retirement nest eggs disappeared. House values shrank while foreclosures increased (Pew Research Center, 2010).

Not surprisingly, this age group reported that the recession hit them worse than other age groups, especially those aged 50-64. Middle-aged adults who find themselves unemployed are likely to remain unemployed longer than those in early adulthood (U.S. Government Accountability Office, 2012). In the eyes of employers, it may be more cost-effective to hire a young adult, despite their limited experience, as they would be starting at lower levels of the pay scale. In addition, hiring someone who is 25 and has many years of work ahead of them versus someone who is 55 and will likely retire in 10 years may also be part of the decision to hire a younger worker (Lachman, 2004). American workers are also competing with global markets and changes in technology. Those who can keep up with all these changes or are willing to uproot and move around the country or even the world have a better chance of finding work. The decision to move may be more accessible for younger people who have fewer obligations to others.

Do Midlifers Enjoy Leisure Time?

As most developed nations restrict the number of hours an employer can demand that an employee work per week and require employers to offer paid vacation time, what do middle-aged adults do with their time off from work and duties, referred to as leisure? Around the world, watching television is the most common leisure activity in early and middle adulthood (Marketing Charts Staff, 2014). On average, middle-aged adults spend 2-3 hours per day watching TV (Gripsrud, 2007), and watching TV accounts for more than half of all leisure time.

In the United States, men spend about 5 hours more per week in leisure activities, especially on weekends, than women (Drake, 2013). The leisure gap between mothers and fathers is slightly smaller, about 3 hours a week, than among those without children under age 18 (Drake, 2013). Those aged 35-44 spend less time on leisure activities than any other age group, 15 or older (Drake, 2013). This is unsurprising as this age group is more likely to be parents and still working up their career ladder, so they may feel they have less time for leisure.

Americans have less leisure time than people in many other developed nations. As you read earlier, there are no laws in many job sectors guaranteeing paid vacation time in the United States. Ray, Sanes, and Schmitt (2013) report that several other nations also provide additional time off for young and older workers and shift workers. In the United States, those in higher-paying jobs and those covered by a union contract are likelier to have paid vacation time and holidays (Ray, Sanes, Schmitt, 2013).

What Are the Benefits of Taking Time Away from Work?

Several studies have noted the benefits of taking time away from work. It reduces job stress burnout and improves mental and physical health, mainly if that leisure time includes moderate physical activity. Leisure activities can also improve productivity and job satisfaction and help adults balance family and work obligations. (Project Time-Off, 2016).

What Do Relationships Look Like During Middle Adulthood?

The importance of establishing and maintaining relationships in middle adulthood is well-established in the academic literature. There are now thousands of published articles purporting to demonstrate that social relationships are integral to any aspect of subjective well-being and physiological functioning, and these help to inform actual healthcare practices. Studies show an increased risk of dementia, cognitive decline, susceptibility to vascular disease, and increased mortality in those who feel isolated and alone. However, loneliness is not confined to people living a solitary existence. It can also refer to those who endure a perceived discrepancy in the socio-emotional benefits of interactions with others, either in number or nature. One may have an expansive social network and still feel a dearth of emotional satisfaction in one’s own life (Lumen Learning, n.d.).

Relationship Types

Intimate relationships.

It makes sense to consider the various relationships in our lives to determine how relationships impact our well-being. For example, would you expect someone to derive the same happiness from an ex-spouse as a child or coworker? Among the most critical relationships for most people is their long-time romantic partner. Most researchers begin their investigation of this topic by focusing on intimate relationships because they are the closest form of social bonds. Intimacy is more than physical; it also entails psychological closeness. Research findings suggest that having a single confidante—someone with whom you can be authentic and trust not to exploit your secrets and vulnerabilities—is more important to happiness than having an extensive social network (Taylor, 2010).

Another important aspect is the distinction between formal and informal relationships. Formal relationships are those that are bound by the rules of politeness. In most cultures, for instance, young people treat older people with formal respect by avoiding profanity and slang when interacting with them. Similarly, workplace relationships tend to be more formal, as do relationships with new acquaintances. Formal connections are generally less relaxed because they require more work, demanding that we exert more self-control. Contrast these connections with informal relationships—friends, lovers, siblings, or others with whom you can relax. We can express our true feelings and opinions in these informal relationships, using the language that comes most naturally to us, and generally be more authentic. Because of this, it makes sense that more intimate relationships—those that are more comfortable and in which you can be more vulnerable—might be the most likely to translate to happiness.

Parenting in Later Life

Just because children grow up does not mean their family stops being a family. Instead, the specific roles and expectations of its members change over time. One significant change comes when a child reaches adulthood and moves away. When exactly children leave home varies greatly depending on societal norms and expectations, as well as on economic conditions such as employment opportunities and affordable housing options. Some parents may experience sadness when their adult children leave the home—a situation called an empty nest.

Many parents also find that their grown children are struggling to become independent. It’s an increasingly common story: a child goes off to college and, upon graduation, cannot find steady employment. In such instances, a frequent outcome is for the child to return home, becoming a “boomerang kid.” As the phenomenon has come to be known, the boomerang generation refers to young adults, mainly between the ages of 25 and 34, who return home to live with their parents. At the same time, they strive for stability in their lives —often in terms of finances, living arrangements, and sometimes romantic relationships. These boomerang kids can be both good and bad for families. Within American families, 48% of boomerang kids report paying their parents rent, and 89% say they help with household expenses—a win for everyone (Parker, 2012).

On the other hand, 24% of boomerang kids report that returning home hurts their relationship with their parents (Parker, 2012). For better or worse, the number of children returning home has been increasing worldwide. The Pew Research Center (2016) reported that the most common living arrangement for people aged 18-34 was living with their parents (32.1%) (Fry, 2016).

Family Issues and Considerations

In addition to middle-aged parents spending more time, money, and energy taking care of their adult children, they are also increasingly taking care of their aging and ailing parents. Middle-aged people in this set of circumstances are commonly called the sandwich generation. They are still looking out for their children while simultaneously caring for elderly parents (Dukhovnov & Zagheni, 2015). Of course, cultural norms and practices again come into play. In some Asian and Hispanic cultures, the expectation is that adult children are supposed to take care of aging parents and parents-in-law. In other Western cultures—cultures that emphasize individuality and self-sustainability—the expectation has historically been that elders either age in place, modify their homes, and receive services to allow them to continue to live independently or enter long-term care facilities. However, given financial constraints, many families take in and care for their aging parents, increasing the number of multigenerational homes worldwide.

As a midlife child, you may take on various responsibilities such as organizing family events, managing communication, and maintaining family ties. This role was first defined by Carolyn Rosenthal in 1985. Typically, kinkeepers are midlife daughters coordinating family gatherings, such as telling everyone what food to bring or arranging a family reunion.

Kinkeeping can be seen as a managerial role that helps to sustain family connections and lines of communication. This applies to many families, including large nuclear, reconstituted, and multi-generational families. Rosenthal discovered that over half of the families she surveyed could identify the person who takes on this role.

Usually, adults at this stage are required to shoulder caregiving responsibilities. With increasing costs of professional care for the elderly and shifts in longevity, this role is likely to grow, which could place even greater pressure on careers.

According to a recent study by Pew Research, 16 out of 1,000 adults aged 45 to 54 in the U.S. have never been married, while 7 out of 1,000 adults aged 55 and older have never been married. However, some individuals may live with a partner, while others may be single due to divorce or widowhood. Bella DePaulo has challenged the notion that singles, particularly those who have always been single, are worse off emotionally and in terms of health compared to their married counterparts.

DePaulo suggests that studies examining the benefits of marriage may be biased, as most only compare married and unmarried individuals without distinguishing between those who have always been single and those who are currently single due to divorce or widowhood. Her research, as well as that of others, has found that while married individuals may be more satisfied with life than those who are divorced or widowed, there is little difference between the always single and the married, particularly when comparing those who recently got married to those who have been married for four or more years. It seems that once the initial honeymoon phase fades, married individuals are no happier or healthier than those who remain single.

Online Dating

Montenegro (2003) surveyed more than 3,000 singles aged between 40 and 69. The survey revealed that nearly half of the participants cited having someone to talk to or do things with as the most important reason for dating. Additionally, sexual fulfillment was also identified as an important goal for many. Alterovitz and Mendelsohn (2013) analyzed online personal ads for men and women over 40. They found that romantic activities and sexual interests were mentioned at similar rates among the middle-aged and young-old age groups but less frequently for the old-old age group.

As society evolves, more people choose different paths regarding relationships. Cohabitation, singlehood, and delayed marriage have become more common. According to the data presented in the figure, 48% of adults aged 45-54 are married, either in their first marriage (22%) or have remarried (26%). This means that marriage is still the most prevalent relationship status among middle-aged adults in the United States. Interestingly, many couples report increased marital satisfaction in midlife as their children leave home (Landsford et al., 2005). However, not all experts agree. Some suggest that those unhappy with their marriage may have already divorced by this point, which could skew reported satisfaction levels (Umberson, 2005).

Livingston (2014) discovered that 27% of people aged 45 to 54 were divorced, with women making up 57% of divorced adults. This indicates that men are more likely to remarry than women. Women initiate two-thirds of divorces (AARP, 2009). Most divorces occur within the first 5 to 10 years of marriage, as people attempt to save their relationship but ultimately end it after limited success. Previously, divorce after 20 or more years of marriage was rare, but it has been on the rise in recent years. Brown and Lin (2012) suggest that this increase in the divorce rate among long-term marriages is due to the decreasing stigma attached to divorce and the fact that some older women are financially capable of supporting themselves after their children have grown. Additionally, with people living longer, older adults may not want to spend more years with an incompatible spouse.

Gottman and Levenson (2000) found that divorces in early adulthood were more conflictual, with each partner blaming the other for the failure of the marriage. In contrast, midlife divorces tended to be more about growing apart or cooling off of the relationship. The effects of divorce vary. Generally, young adults have a harder time adjusting to the consequences of divorce than midlife adults, with a higher risk of depression and other psychological problems (Birditt & Antonucci, 2013).

Midlife divorce is more challenging for women. According to an AARP (2009) survey, 44% of middle-aged women reported facing financial problems after their divorce, compared to only 11% of men. However, many women who divorce in midlife report that they feel a sense of release from their day-to-day unhappiness. Hetherington and Kelly (2002) found that among the enhancers and competent loners who used their divorce experience to grow emotionally and seek more productive intimate relationships or choose to stay single, the majority were women.

Dating Post-Divorce

Most divorced adults have dated by one year after filing for divorce (Anderson & Greene, 2011). One in four recent filers report having been in or were currently in a serious relationship, and over half were in a serious relationship by one year after filing for divorce. Not surprisingly, younger adults were more likely to be dating than middle-aged or older adults due to the larger pool of potential partners from which they could draw. Of course, these relationships will not all end in marriage. Teachman (2008) found that more than two-thirds of women under the age of 45 had cohabited with a partner between their first and second marriages.

Dating for adults with children can be more of a challenge. Courtships are shorter in remarriage than in first marriages. When couples are “dating,” there is less going out and more time spent in activities at home or with the children. So, the couple gets less time together to focus on their relationship. Anxiety or memories of past relationships can also get in the way. As one Talmudic scholar suggests, “When a divorced man marries a divorced woman, four go to bed” (Seccombe & Warner, 2004).

Post-divorce parents  gatekeep —that is, they regulate the flow of information about their new romantic partner to their children in an attempt to balance their own needs for romance with consideration regarding the needs and reactions of their children. Anderson et al. (2004) found that almost half (47%) of dating parents gradually introduce their children to their dating partner, giving both their romantic partner and children time to adjust and get to know each other. Many parents use this approach to avoid their children having to keep meeting someone new until it becomes more apparent that this relationship might be more than casual. It might also help if the adult relationship is on firmer ground to weather any initial pushback from children when it is revealed.

Grandparents

In addition to maintaining relationships with their children and aging parents, many people in middle adulthood take on another role: becoming a grandparent. The role of grandparents varies around the world. In multigenerational households, grandparents may play a more significant role in their grandchildren’s day-to-day activities. While this family dynamic is more common in Latin America, Asia, and Africa, it has increased in the U.S. (Pew Research Center, 2010).

Friendships

Adults of all ages who reported having a confidante or close friend with whom they could share personal feelings and concerns believed these friends contributed to a sense of belonging, security, and overall well-being (Duner & Nordstrom, 2007). Having a close friend is a factor in significantly lower odds of psychiatric morbidity including depression and anxiety (Newton et al., 2008). The availability of a close friend has also been shown to lessen the adverse effects of stress on health (Hawkley, 2008). Additionally, poor social connectedness in adulthood is associated with a more considerable risk of premature mortality than cigarette smoking, obesity, and excessive alcohol use (Holt-Lunstad, Smith, & Layton, 2010).

Female friendships and social support networks at midlife contribute significantly to a woman’s life satisfaction and well-being (Borzumato, 2009). Degges-White and Myers (2006) found that women with supportive people experience greater life satisfaction than those with a more solitary life. A friendship network or a confidant’s presence has been identified for their importance to women’s mental health (Baruch & Brooks-Gunn, 1984). Unfortunately, with numerous caretaking responsibilities at home, it may be difficult for women to find time and energy to enhance friendships that provide an increased sense of life satisfaction (Borzumato-Gainey et al., 2009).  Emslie, Hunt, and Lyons (2013) found that for men in midlife, the shared consumption of alcohol was essential to creating and maintaining male friends. Drinking with friends was justified as a way for men to talk to each other, provide social support, relax, and improve mood. Although the social support provided when men drink together can be helpful, the role of alcohol in male friendships can lead to health-damaging behavior from excessive drinking.

Internet Friendships

What influence does the Internet have on friendships? It is not surprising that people use the Internet with the goal of meeting and making new friends (Fehr, 2008). Researchers have wondered if the issue of not being face-to-face reduces the authenticity of relationships or if the Internet allows people to develop deep, meaningful connections. Interestingly, research has demonstrated that virtual relationships are often as intimate as in-person relationships; in fact, Bargh and colleagues found that online relationships are sometimes more intimate (Bargh, McKenna, & Fitzsimons, 2002). This can be especially true for those individuals who are more socially anxious and lonely, as such individuals are more likely to turn to the Internet to find new and meaningful relationships. McKenna and colleagues (2002) suggest that for people who have difficulty meeting and maintaining relationships due to shyness, anxiety, or lack of face-to-face social skills, the Internet provides a safe, non-threatening place to develop and maintain relationships. Similarly, Benford and Standen (2009) found that for high-functioning autistic individuals, the Internet facilitated communication and relationship development with others, which would have been more complex in face-to-face contexts, leading to the conclusion that Internet communication could be empowering for those who feel frustrated when communicating face to face.

So, What Have You Learned?

Many physical, cognitive, and socioemotional changes occur in middle-aged adults. In addition to how they perceive themselves. While people in their early 20s may emphasize how old they are to gain respect or to be viewed as experienced, by the time people reach their 40s, they tend to emphasize how young they are. For instance, a few 40-year-olds cut each other down for being so young, stating: “You’re only 43? I’m 48!” A previous focus on the future gives way to an emphasis on the present. Neugarten (1968) notes that in midlife, people no longer think of their lives in terms of how long they have lived. Rather, life is thought of regarding how many years are left. Nonetheless, the consistency with maintaining one’s physical, cognitive, and psychosocial health during middle age allows a midlifer to embrace this current phase, resulting in successful aging.

The section “Family Issues and Considerations” briefly discussed how the adult child(ren) is expected to care for their aging parent. In this written assignment, you will interview someone you know or seek out someone who primarily or shares responsibilities in caring for an aging parent. Inquire from them:

• What are the upsides and downsides of taking care of them?
• Any setbacks that were caused in their lives, such as careers, outside relationships, leisure time, etc.?
• How do they take care of themselves? Who is their support system?
• What advice would they like to share with others to ensure a balance between having a personal life and caring for their aging parent(s)?

Written Discussions are a more formal style of writing.

• 1 cover page
• 3 body pages
• 1 Reference list page
• Make sure to cite your source using the APA format.
• The word count has to be 300 minimum.

AARP. (2009). The divorce experience: A study of divorce at midlife and beyond. Washington, DC: AARP

American Association of Community Colleges. (2022). Fast Facts 2022. https://www.aacc.nche.edu/wp-content/uploads/2022/02/AACC_2022_Fact_Sheet.pdf

American Diabetes Association (2016). Standards of medical care in diabetes. Diabetes Care, 39(1), 1-112.

Asarch, & Asarch. (2022, July 18). Is Humidity Good For Skin? – Asarch Dermatology. Asarch Dermatology.  https://www.asarchcenter.com/blog/is-humidity-good-for-skin

Centers for Disease Control and Prevention (2014a). About high blood pressure. http://www.cdc.gov/bloodpressure/about.htm

International Labour Organization. (2011). Global Employment Trends: 2011. http://www.ilo.org/wcmsp5/groups/public/@dgreports/@dcomm/@publ/documents/publication/wcms_150440.pdf

Marketing Charts Staff. (2014). Are young people watching less TV? http://www.marketingcharts.com/television/are-young-people-watching-less-tv-24817/

Mayo Clinic. (2014a). Heart disease. http://www.mayoclinic.org/diseases-conditions/heart-disease/basics/definition/con-2003405

Metlife (2011). Metlife study of caregiving costs to working caregivers: Double jeopardy for baby boomers caring for their parents. http://www.caregiving.org/wp-content/uploads/2011/06/mmi-caregiving-costs-working-caregivers.pdf

Monthly Labor Review. (2021). Percentage of the non-institutionalized civilian workforce employed by gender & age. https://www.bls.gov/cps/tables.htm#otheryears

National Alliance for Caregiving. (2015). Caregiving in the U.S. 2015. http://www.caregiving.org/caregiving2015.

National Institute on Deafness and Other Communication Disorders. Quick Statistics on Hearing. https://www.nidcd.nih.gov/health/statistics/quick-statistics-hearing.

National Institutes of Health. (2015). Cancer. Retrieved from https://www.cancer.gov/about-cancer/understanding/what-is-cancer

National Institutes of Health. (2016a) Facts about diabetes. http://www.niddk.nih.gov/health-information/health-topics/Diabetes/diabetes-facts/Pages/default.aspx

National Institutes of Health. (2007). Menopause: MedlinePlus Medical Encyclopedia. http://www.nlm.nih.gov/medlineplus/ency/article/000894.htm

National Sleep Foundation. (2015). 2015 Sleep in America™ poll finds pain a significant challenge when it comes to Americans’ sleep. National Sleep Foundation. https://sleepfoundation.org/ media-center/press-release/2015-sleep-america-poll

National Sleep Foundation. (2016). Menopause and Insomnia. National Sleep Foundation. https://www.sleepfoundation.org/women-sleep/menopause-and-sleep

Patient Education Institute. (n.d.). Low Testosterone: MedlinePlus Interactive Health Tutorial. http://www.nlm.nih.gov/medlineplus/tutorials/lowtestosterone/htm/index.htm

Pew Research Center. (2010). The return of the multi-generational family household. http://www.pewsocialtrends.org/2010/03/18/the-return-of-the-multi-generational-family-household/

Pew Research Center. (2010a). How the great recession has changed life in America. http://www.pewsocialtrends.org/2010/06/30/how-the-great-recession-has-changed-life-in-america/

Pew Research Center. (2010b). Section 5: Generations and the Great Recession. http://www.people-press.org/2011/11/03/section-5-generations-and-the-great-recession/

Project Time-Off (2016). The state of American vacation: How vacation became a casualty of our work culture. http://www.projecttimeoff.com/research/state-american-vacation-2016

U.S. Government Accountability Office. (2012). Unemployed older workers: Many experience challenges regaining employment and face reduced retirement security. http://www.gao.gov/products/GAO-12-445

U.S. Census Bureau, Population Division. (2017). Projected 5-Year Age Groups and Sex Composition: Main Projections Series for the United States, 2017–2060. https://www.census.gov/data/tables/2017/demo/popproj/2017-summary-tables.html

U.S. Department of Labor (2016). Vacation Leave. https://www.dol.gov/general/topic/workhours/vacation_leave

World Health Organization (WHO). (2013). A global brief on hypertension: Silent killer, global public health crisis. http://apps.who.int/iris/bitstream/10665/79059/1/WHO_DCO_WHD_2013.2_eng.pdf?ua=1

Attribution:

This chapter was adapted by Tremika Cleary from select chapters in Iowa State University Digital Press Individual and Family Development, Health, and Well-being , authored by Diana Lang, Nick Cone; Martha Lally, Suzanne Valentine-French; and Ronnie Mather, available under a   Creative Commons Attribution-ShareAlike 4.0 International License .

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Depression and Life Satisfaction Among Middle-Aged and Older Adults: Mediation Effect of Functional Disability

1 State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, China

2 School of Public Affairs, Xiamen University, Xiamen, China

Shengnan Lin

Shiling huang, chun-yang lee.

3 School of International Business, Xiamen University Tan Kah Kee College, Zhangzhou, China

Yi-Chen Chiang

Associated data.

The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding authors.

With increasing age, middle-aged and older persons face a series of physical and mental health problems. This study aimed to explore the latent relationships among age, functional disability, depression, and life satisfaction. The data were obtained from the Wave 2 (in 2013–2014) and Wave 3 (in 2015–2016) surveys of the China Health and Retirement Longitudinal Study. The analytic sample in the present study included 15,950 individuals aged 45 years and over. The participants answered the same questions concerning depression and life satisfaction in both study waves, and functional disability was measured based on the activities of daily living and instrumental activities of daily living. Age was directly associated with functional disability, life satisfaction, and depression. Functional disability was positively correlated with depression and negatively correlated with life satisfaction. Functional disability strongly mediated the relationships among age, depression, and life satisfaction. Depression and life satisfaction were found to have enduring effects and effects on each other. Additionally, the model revealed a gender difference. Depression in middle-aged people should receive closer attention. Avoiding or improving functional disability may be an effective way to improve life satisfaction and reduce the level of depression in middle-aged and older persons. If prevention work successfully decreases depression, the life dissatisfaction of middle-aged and older people could be improved. Additionally, for the prevention of functional disability and depression and improvement in life satisfaction, gender differences need to be considered.

Introduction

The growth rate of the aging population is unprecedented worldwide and will accelerate in the coming decades, especially in developing countries ( WHO, 2021a ). There are 1 billion people aged 60 and over worldwide. This number is estimated to reach 1.4 billion by 2030 and 2.1 billion by 2050 ( WHO, 2021a ). As a developing country with the largest population worldwide, China was home to 176 million older persons aged 65 years old and over (12.57% of the country’s population) in 2019. By 2050, China’s older population (65+) is likely to rise to 330 million, representing approximately a quarter of the population ( Wang et al., 2016 ). As human life expectancy increases, older people are likely to experience reduced physical capacity ( Auais et al., 2019 ), adding to the associated burden ( Song et al., 2017 ). The early prevention of age-related diseases can reduce the negative effects of aging and the disease burden on the older population ( Partridge et al., 2018 ). Therefore, while addressing the health problems of older people, prevention at a young age should also be emphasized to promote healthy aging.

Maintaining the ability to move and function independently in old age are critical for continued community participation, health, and well-being and is a major challenge posed by population aging ( Auais et al., 2019 ). With increasing age, an increasing number of middle-aged and older people can suffer from functional disabilities that affect their mobility, social participation, and quality of life ( Webber et al., 2010 ; Sole-Auro and Alcaniz, 2015 ). Research has shown that age is one of the main reasons for the impairment of physical ability among older persons ( Falk et al., 2014 ). As people get older, skeletal muscle degenerates, muscle mass and muscle strength gradually decrease, and functional performance decreases ( Barberi et al., 2015 ).

Functional disability is defined as the need for help or the inability to perform one or more activities of daily living (ADL) or instrumental activities of daily living (IADL) ( Griffith et al., 2010 ). ADL refer to the most basic and common body movements that people must perform repeatedly daily to live independently, such as bathing, eating, dressing, getting up and down from bed, going to the toilet, and controlling urine and feces, reflecting the most basic self-care ability. ADL are important indices for predicting the life span and determining the quality of life ( Covinsky, 2006 ). IADL refer to the adaptive work that individuals perform to cope with the needs of their environment. IADL are often complex and require good abilities to perform, such as shopping, cooking, completing household chores, doing the laundry, using the telephone, and managing money. These activities, while not necessary every day, are important for maintaining an individual’s independence. Since ADL measures do not measure the ability of older people to adapt to the environment, they underestimate the number of older people who need assistance in various living activities. Therefore, the inclusion of both ADL and IADL items could better determine the extent of community dysfunction and identify broader service needs ( Spector et al., 1987 ).

Based on the World Health Organization (WHO) definition, health is a state of complete physical, mental, and social well-being and not merely the absence of disease or infirmity ( Kühn and Rieger, 2017 ). In recent years, mental health has played an important role in achieving global development goals, as illustrated by the inclusion of mental health in the 2030 agenda for sustainable development ( UN, 2015 ). When one’s physical health worsens, control over activities is restricted, which endangers mental health ( Rodin, 1986 ). Therefore, attention should be given to both mental health and physical health.

As two important dimensions of mental health, depression and life satisfaction need to be considered ( Headey et al., 1993 ; Guney et al., 2010 ). Depression is a non-communicable disease with a significant global disease burden ( Hay et al., 2017 ). As a common mental illness ( Liu Q. et al., 2020 ), depression affects approximately 264 million people worldwide ( WHO, 2021b ). In China, depression is also a common disease and is a major public health challenge requiring urgent prevention. A systematic analysis showed that 2.2% of men and 3.3% of women suffer from major depression in China ( Baxter et al., 2016 ). A nationally representative China Longitudinal Aging Social Survey also confirmed that depression was higher in women than men ( Li and Chen, 2021 ). Depression not only affects work ( Jantaratnotai et al., 2017 ) and increases the economic burden on society and families ( Kordy et al., 2013 ), but also increases the risk of suicidal ideation and behavior ( Teng et al., 2013 ). Therefore, it is very important to identify the risk factors for depression and implement effective intervention strategies to prevent or delay the development of depression. Depression has a U-shaped overall distribution in the population, but as far as the middle-aged and elderly people are concerned, the incidence of depression in older people is higher than that in middle-aged people ( Mirowsky and Ross, 1992 ). The closer the older adults are to the end of life, the more they experience stressful events, such as illness, declining income, and the death of relatives and friends. The life cycle hypothesis holds that the average level of depression declines during early adulthood to middle age and then rises ( Mirowsky and Ross, 1992 ). Therefore, it is generally believed that with an increase in age, depression among middle-aged and older adults will continue to increase ( Bergdahl et al., 2005 ; Solhaug et al., 2012 ). However, a few studies have found that depression among older people decreases with age ( Sung, 2013 ). Therefore, the effect of age on depression needs to be further verified.

In contrast to depression, life satisfaction is a positive evaluation index; it is a subjective well-being measure reflecting a person’s cognitive judgment of life ( Diener, 1984 ; Hong et al., 2019 ). Life satisfaction is an important goal for improving the quality of life of older adults ( Chachamovich et al., 2007 ), and it is an indispensable cognitive or evaluative element of life quality and successful aging ( Lawton et al., 2002 ). However, life satisfaction among middle-aged and older adults is related to many factors, including age. What is the relationship between age and life satisfaction? Some studies have shown a U-shaped relationship between age and life satisfaction ( Blanchflower and Oswald, 2004 ; Graham and Pozuelo, 2017 ), meaning that life satisfaction declines in middle age and then increases with age. In other words, starting in middle age, people’s life satisfaction increases with age. According to socioemotional selectivity theory (SST), future time perspective (FTP) is a key factor in explaining the persistent or even improved subjective well-being of elderly individuals compared with that of their younger counterparts ( Carstensen et al., 1999 ; Carstensen, 2006 ). With limited FTP, older people tend to focus on the present rather than the future, which benefits their subjective well-being. However, contrary to the assertion of SST, many studies have found that persons with a limited FTP tend to report lower subjective well-being ( Allemand et al., 2012 ; Kozik et al., 2015 ; Gruhn et al., 2016 ). According to life span theories of motivation ( Heckhausen, 2000 ; Hong et al., 2019 ), young and middle-aged people focus on growth and self-development, while older people are increasingly aware of the decline in biological function and the limited resources and opportunities in the future ( Cheng et al., 2009 ). Their motivation focuses on maintaining the current level of function and planning for future decline. Thus, the youngest adults show positive trajectories in terms of perceived past, present, and future life satisfaction, while the trajectory is flat in late middle age and negative in older adults. This result has also been verified ( Hong et al., 2019 ).

The research shows that in addition to age, functional disability is an important factor influencing depression and life satisfaction among middle-aged and older people ( Liang et al., 2017 ; Barry et al., 2020 ). According to the stress process theory ( Pearlin et al., 1981 ), dysfunction may hinder people’s ability to achieve their expected social role of living independently, ultimately leading to depression ( Russell et al., 2009 ). Studies have shown that dysfunction in IADL/ADL leads to a significant increase in depression among older persons in general ( Bozo et al., 2009 ; Park et al., 2014 ). The research ( Peltzer and Phaswana-Mafuya, 2013 ) examining the factors associated with depression among South Africa adults revealed that functional disability was significantly associated with increased depression. Additionally, according to a follow-up study in China, ADL disability could increase the risk of depressive symptoms in middle-aged and older adults and their spouses ( He et al., 2019 ). Compared with non-disabled people, older people with disabilities have higher levels of depression ( Pagan-Rodriguez and Perez, 2012 ).

The relationship between depression and life satisfaction in middle-aged and older adults has also been discussed. One study found that depression has the greatest influence on older adults’ life satisfaction ( Sok, 2010 ), while another study reported that life satisfaction is the strongest negative predictor of depression in older adults ( Yoo et al., 2016 ). The possible pathways have yet to be determined through structural equation modeling (SEM). In summary, the relationship among age, functional disability, depression, and life satisfaction needs to be further verified among middle-aged and older adults using national survey data.

What is the relationship among age, depression, and life satisfaction among middle-aged and older adults? Is functional disability a mediator between age and depression/life satisfaction? Based on the existing literature and theories, our hypotheses (as shown in Figure 1 ) are as follows: among middle-aged and older adults (H1-1), age is positively correlated with functional disability (ADL disability and IADL disability); (H1-2) age is positively correlated with depression; (H1-3) age is negatively correlated with life satisfaction; (H2-1) functional disability is positively correlated with depression; (H2-2) functional disability is negatively correlated with life satisfaction; (H3) functional disability mediates the relationships between age and depression or life satisfaction; and (H4) a cross effect exists between depression and life satisfaction.

Hypothesized model of the research framework. ADL, activities of daily living; IADL, instrumental activities of daily living; DP13, depression in 2013–2014; DP15, depression in 2015–2016; LF13, life satisfaction in 2013–2014; LF15, life satisfaction in 2015–2016. Hypotheses were that (H1-1) age would be positively correlated with functional disability; (H1-2) age would be positively correlated with depression; (H1-3) age would be negatively correlated with life satisfaction; (H2-1) functional disability would be positively correlated with depression; (H2-2) functional disability would be negatively correlated with life satisfaction; (H3) functional disability would mediate the relationships of age with depression and life satisfaction; and (H4) there would be a cross effect between depression and life satisfaction.

Materials and Methods

Participants.

The data were obtained from the Wave 2 (in 2013–2014) and Wave 3 (in 2015–2016) surveys of the China Health and Retirement Longitudinal Study (CHARLS), which is an ongoing nationwide population-based prospective cohort study ( Zhao et al., 2014 ). The sample is representative of the household population aged 45 years and older in China (baseline survey in 2011–2012, with participants recruited from 450 villages and residences in 150 counties and districts in 28 provinces). The follow-up time interval of the CHARLS is 2 years. Therefore, the CHARLS participants received the Wave 2 survey in 2013–2014 and the Wave 3 survey in 2015–2016. For more details on the recruitment strategy, design, and sampling method of the CHARLS, refer Zhao et al. (2014) .

A flowchart of the sample selection in this study is shown in Figure 2 . First, in total, 18,605 respondents participated in the Wave 2 survey. Then, 2343 participants were excluded because they did not continue to participate in the Wave 3 survey. Since the survey involved people aged over 45 years, 312 participants younger than 45 were further excluded. Finally, in total, 15,950 participants were included in our analysis. The follow-up rate was over 85%. Consequently, in the final sample, 7627 men (47.83%) and 8319 women (52.17%) responded to the two interviews. To prove that the data are representative, we conducted attrition analysis of ADL disability, IADL disability, depression, life satisfaction, gender, and age. Since ADL disability, IADL disability, and depression were continuous variables, and life satisfaction was an ordinal variable, we used the values of percentile 25 and percentile 75 of each variable (ADL disability, IADL disability, and depression) in the first wave to divide the whole sample into three groups, and life satisfaction was divided into five groups according to its options. Then Chi-square goodness-of-fit test was used to conduct the attrition analysis (compared the distribution of variables among the second-wave follow-up data and the first wave data). The results showed that there was no statistically significant difference in attrition of IADL disability (χ 2 = 2.48, p = 0.29), depression (χ 2 = 0.09, p = 0.95), life satisfaction (χ 2 = 1.89, p = 0.76), and gender (χ 2 = 0.12, p = 0.72), except for ADL disability and age. But this may be due to excessive sensitivity resulting from the large sample size. In addition, descriptive analysis found that the ADL disability and age distribution difference caused by attrition was only 0.39–1.09 and 1.11–2.37%, respectively. The CHARLS program was approved by the Ethical Review Committee of Peking University, and all participants signed an informed consent form.

Flowchart of the inclusion and exclusion of participants.

Activities of Daily Living and Instrumental Activities of Daily Living

Difficulty with ADL in the past 3 months was measured using the Barthel Index for ADL ( Wade and Collin, 1988 ; Liu N. et al., 2020 ). ADL information was collected with six questions about difficulty in dressing, bathing, eating, getting into or out of bed, using the toilet, and controlling urination and defecation. Respondents were also asked whether they had any difficulty performing IADL ( Lawton and Brody, 1969 ; Liu N. et al., 2020 ), including doing household chores, preparing hot meals, shopping for groceries, making phone calls, taking medications, or managing money, in the past 3 months. Each item was scored from 1 (“don’t have any difficulty”) to 4 (“can’t do it”) points, with the highest score indicating the greatest symptom burden. The same questions were used in both Wave 2 and Wave 3 of the data collection but not in Wave 1 (the question regarding phone calls was not asked in this survey). In this study, to verify the effects of ADL disability and IADL disability on depression and life satisfaction, we used the functional disability data from Wave 2. The Cronbach’s alphas for the ADL and IADL disability measures were 0.85 and 0.83, respectively.

Depressive Symptoms

The participants self-reported their depressive symptoms using The Center for Epidemiological Studies Depression Scale (CES-D) short form ( Kohout et al., 1993 ; Wang et al., 2019 ; Qiao et al., 2021 ) at baseline and each follow-up of the CHARLS. The CES-D short form is composed of 10 items, which is used to evaluate the frequency of symptoms or behaviors experienced during the past week, such as “I was bothered by things that don’t usually bother me,” “I felt depressed,” and “I felt fearful.” Question 5 (“I felt hopeful about the future”) and Question 8 (“I was happy”) are reverse questions, and the responses were reverse-scored before analysis. Each item is scored on a scale from 1 to 4, where 1 = “rarely or none of the time,” 2 = “some or a little of the time,” 3 = “occasionally or a moderate amount of the time,” and 4 = “most or all of the time.” Higher scores indicate more severe depressive symptoms. Previous research has shown that the CES-D short form is reliable and valid ( Lei et al., 2014 ). In our data, the Cronbach’s alphas for this measure were 0.78 (Wave 2) and 0.81 (Wave 3).

Life Satisfaction

In both Wave 2 and Wave 3, life satisfaction was measured by asking participants “Please think about your life as a whole. How satisfied are you with it?” The five possible responses ranged from “completely satisfied” to “not at all satisfied.” The responses were reverse-scored before analysis.

Data Analyses

Statistical analyses were performed using SAS version 9.4 (Copyright © SAS Institute Inc., SAS Campus Drive, Cary, North Carolina 27513, United States. All rights reserved), LISREL version 8.80 (Copyright 2006, Scientific Software International Inc., All rights reserved), IBM SPSS STATISTICS 22.0 (SPSS Inc., Chicago, IL, United States), and R version 4.0.2 (R Foundation, Vienna, Austria). SAS was used to merge the Wave 2 and Wave 3 data based on individual IDs, SPSS was used to analyze the correlations between the variables. Cronbach’s alpha coefficient was used to evaluate the internal consistency of the scales. Confirmatory factor analysis (CFA) was used to test the construct validity of the scales ( Table 1 ). The goodness-of-fit indices for the CES-D short-form were as follows: (1) root mean squared error of approximation (RMSEA) = 0.057; (2) comparative fit index (CFI) = 0.98; and (3) tucker-lewis index (TLI) = 0.98. The goodness-of-fit indices of the ADL and IADL disability measures were as follows: (1) RMSEA = 0.041; (2) CFI = 1; and (3) TLI = 1. If CFI > 0.92, or RMSEA < 0.07, the model is considered to fit the data ( Hair et al., 2014 ; Mora-Pelegrin et al., 2021 ). The results indicate that these instruments had good reliability and validity.

Confirmatory factor analysis and structural equation modeling.

Items of ADL and IADL disability scores 1 (don’t have any difficulty) to 4 (can’t do it) points; items of depression scores 1 (rarely or none of the time) to 4 (most or all of the time) points.

To investigate the correlations among age, ADL disability, IADL disability, depression, and life satisfaction in middle-aged and older individuals, SEM was performed using LISREL version 8.80 (Copyright 2006, Scientific Software International Inc., All rights reserved.). The maximum likelihood estimation method was used. In addition, the estimated indirect effects (IEs) in the output file from LISREL and Monte Carlo resampling with R were used to confirm the significance of the IEs.

Descriptive Statistics and Correlation Analysis

After the inclusion and exclusion criteria were applied, 15,950 older adults were included in the analytical sample. Table 2 shows the means, SDs, and correlation coefficients of all variables.

Descriptive statistics and correlation analysis.

M, mean; ADL, activities of daily living; IADL, instrumental activities of daily living; DP13, depression in 2013–2014; DP15, depression in 2015–2016; LF13, life satisfaction in 2013–2014; LF15, life satisfaction in 2015–2016. ***p < 0.001.

The results showed that IADL disability and ADL disability were positively correlated with depression in 2013–2014 (DP13) and depression in 2015–2016 (DP15) and negatively correlated with life satisfaction in 2013–2014 (LF13) and life satisfaction in 2015–2016 (LF15). There was also a negative correlation between depression and life satisfaction in both surveys. A t -test revealed that there were significant gender differences in IADL disability ( t = −10.28, p < 0.01), DP13 ( t = −18.32, p < 0.001), and DP15 ( t = −21.07, p < 0.001). The Chi-square test also showed significant gender differences in LF13 ( p < 0.05) and LF15 ( p < 0.05). Compared to men, women had higher levels of IADL disability and depression and lower life satisfaction. There was no significant gender difference in ADL disability.

Direct/Indirect Effect Analyses

Based on the preset model, ADL disability and IADL disability were added to the structural equation model as mediating variables in the direct path from age to depression and life satisfaction, and LF15 was set to be correlated with DP15 after controlling for sex ( Figure 3 ). The results suggested a good fit of the data to the model (RMSEA = 0.033; CFI = 0.99; TLI = 0.99).

Structural equation modeling. The model presented the direct and indirect effects between variables. Gender, as a control variable, is not shown in the figure. ADL, activities of daily living; IADL, instrumental activities of daily living; DP13, depression in 2013–2014; DP15, depression in 2015–2016; LF13, life satisfaction in 2013–2014; LF15, life satisfaction in 2015–2016. *** p < 0.001.

The SEM showed that after ADL disability and IADL disability were added as mediation variables, there was a significant negative correlation between age and DP13 (β = −0.10, p < 0.001), and LF13 increased with age (β = 0.18, p < 0.001); this result differed from the hypothesis, so H1-2 and H1-3 were not supported. There was a significant positive correlation between age and ADL disability (β = 0.15, p < 0.001)/IADL disability (β = 0.21, p < 0.001); thus, H1-1 was supported.

Regarding functional disability, ADL disability (β = 0.29, p < 0.001) and IADL disability (β = 0.16, p < 0.001) were positively correlated with DP13; in contrast, ADL disability (β = −0.15, p < 0.001) and IADL disability (β = −0.09, p < 0.001) were negatively correlated with LF13, supporting H2-1 and H2-2. Therefore, ADL disability and IADL disability partially mediated the effects of age on depression and life satisfaction, and H3 was preliminarily supported.

The DP13 was negatively correlated with LF15 (β = −0.23, p < 0.001), and LF13 was negatively correlated with DP15 (β = −0.05, p < 0.001), indicating that depression and life satisfaction may affect each other; thus, H4 was supported. DP13 was positively correlated with DP15 (β = 0.63, p < 0.001), and LF13 was positively correlated with LF15 (β = 0.30, p < 0.001), which indicates that depression and life satisfaction have enduring effects. In addition, we found that DP13 played a mediating role in the relationships of age, ADL disability, and IADL disability with LF15 and that LF13 played a mediating role in the relationships of age, ADL disability, and IADL disability with DP15.

To further verify the mediation hypotheses (H3), Monte Carlo resampling was used to construct the CIs ( Preacher and Selig, 2012 ). Specifically, a program was written in R to construct 95% CIs for the IEs based on 20,000 resamples ( Preacher and Selig, 2012 ). According to the results ( Table 3 ), the 95% CI for all IEs did not include zero. Therefore, H3 was further supported.

Tests of indirect effects of the hypothesized model by Monte Carlo approach of resampling (total sample, n = 15,950).

ADL, activities of daily living; IADL, instrumental activities of daily living; DP13, depression in 2013–2014; DP15, depression in 2015–2016; LF13, life satisfaction in 2013–2014; LF15, life satisfaction in 2015–2016.

Structural Equation Modeling Among Different Gender

In order to realize the possible gender differences, the structural equation model among the men and women samples was tested, respectively ( Figure 4 ). The goodness-of-fit indices ( Table 4 ) show that the models of both men and women were both acceptable. The structural equation model results were quite the same with the results in the whole sample. Notably, the parameter of ADL disability→LF13 was only significant among women (β = −0.24, p < 0.001), whereas the parameter of IADL disability→LF13 was only significant among men (β = −0.15, p < 0.001). That is to say, difficulties in ADL (e.g., dressing, bathing, eating, getting into or out of bed, using the toilet, and controlling urination and defecation) were more likely to lower women’s life satisfaction. Nevertheless, difficulties in IADL (e.g., performing household chores, preparing hot meals, grocery shopping, making phone calls, taking medications, or managing money) were more likely to lower men’s life satisfaction. In addition, Monte Carlo resampling was used to construct the CIs of the mediation models of the men and women samples. The results are shown in Table 5 . In the “Age→ADL disability→LF13” path and “ADL disability→LF13→DP15” path, the 95% CI contained 0 in the men sample and did not contain 0 in the women sample. However, in the “Age→IADL disability→LF13” and “IADL disability→LF13→DP15” paths, the 95% CI did not contain 0 in the men sample and contained 0 in the women sample.

Structural equation modeling for different genders. The coefficients inside the brackets are for women. Significant paths with gender difference according to the multi-group comparison analysis by LISREL: Age→ADL disability (Δχ 2 = 4.63, p < 0.05), Age→IADL disability (Δχ 2 = 4.31, p < 0.05), Age→DP13 (χ 2 = 4.25, p < 0.05), Age→LF13 (Δχ 2 = 3.99, p < 0.05), IADL disability→LF13 (Δχ 2 = 4.43, p < 0.05), DP13→DP15 (Δχ 2 = 4.09, p < 0.05), and DP13→LF15 (Δχ 2 = 4.43, p < 0.05), LF13→LF15 (Δχ 2 = 3.85, p < 0.05). ADL, activities of daily living; IADL, instrumental activities of daily living; DP13, depression in 2013–2014; DP15, depression in 2015–2016; LF13, life satisfaction in 2013–2014; LF15, life satisfaction in 2015–2016. *** p < 0.001.

The goodness-of-fit indices for men and women mediating model.

Mediating effects in different gender mediating models.

Furthermore, we used multigroup comparison analysis to clarify the gender difference among relationships between each two latent variables (refer to the note in Figure 4 ). It was found that the paths of Age→ADL disability (Δχ 2 = 4.63, p < 0.05), Age→IADL disability (Δχ 2 = 4.31, p < 0.05), Age→DP13 (Δχ 2 = 4.25, p < 0.05), Age→LF13 (Δχ 2 = 3.99, p < 0.05), IADL disability→LF13 (Δχ 2 = 4.43, p < 0.05), DP13→DP15 (Δχ 2 = 4.09, p < 0.05), DP13→LF15 (Δχ 2 = 4.43, p < 0.05), and LF13→LF15 (Δχ 2 = 3.85, p < 0.05) had significant gender differences. The path coefficients of Age→ADL disability in men and women samples were 0.12 ( p < 0.001) and 0.16 ( p < 0.001), respectively, and the path coefficients of Age→IADL disability in men and women samples were 0.19 ( p < 0.001) and 0.23 ( p < 0.001), respectively. The results suggest that increasing age may lead to more ADL disability and IADL disability in women than in men. However, women experience more relief from depression and higher life satisfaction than men as they get older. The path coefficients of IADL disability→LF13 in men and women samples were −0.15 ( p < 0.001) and −0.03 ( p > 0.05), respectively, which showed that IADL disability reduced life satisfaction only in men. The path coefficients of DP13→DP15 in men and women samples were 0.61 ( p < 0.001) and 0.62 ( p < 0.001), respectively, indicating that the lasting effect of depression has an extremely significant effect on both genders. Although the coefficients of this pathway were similar in the two samples, significant gender difference still exists according to the multigroup comparison analysis. That is, the lasting effect of depression was greater in women than in men. Besides, the coefficients of DP13→LF15 were −0.25 ( p < 0.001) and −0.21 ( p < 0.001) in men and women samples, respectively. It declared that the early prevention of depression in men had a more significant effect on the improvement of subsequent life satisfaction than that in women. Furthermore, the lasting effect of life satisfaction was greater in women (β = 0.32, p < 0.001) than in men (β = 0.28, p < 0.001). Moreover, the path coefficient of ADL→LF13 in men and women were −0.07 ( p > 0.05) and −0.24 ( p < 0.001), respectively. The non-significant result in men may be due to the SE of the beta was moderately large, the impacts of ADL disability on life satisfaction (95% CI [−0.16, 0.02]) among males were diverse. However, the gender difference of the path coefficient was not statistically significant by using the multigroup comparison.

Symptoms of Functional Disability and Depression

According to lambda values (λ > 0.85) in the structural equation model, we found that regarding ADL, middle-aged and older people with functional disability had great difficulties with dressing (λ = 1.00), bathing/showering (λ = 0.99), eating (λ = 0.90), and getting into/out of bed (λ = 0.90), while regarding IADL, they had great difficulties in performing household chores (λ = 0.98), preparing hot meals (λ = 1.00), and shopping for groceries (λ = 0.94). In addition, depression among this population was mainly characterized by feeling depressed (λ = 1.00), felt everything did was an effort (λ = 0.86), feeling lonely (λ = 0.89), and feeling unable to move on (λ = 0.93). The findings could be applied to geriatric care, quality improvement, program dissemination, and service design.

In this study, a mediating model was used to test the effects of age on depression and life satisfaction and the mechanisms of ADL disability and IADL disability. The results showed that depression among middle-aged people was higher than that among older people and that life satisfaction was lower than that among older people. ADL disability and IADL disability played a partial mediating role in this process, and the predictive effect of IADL disability on life satisfaction in men was significantly greater than that in women. To prove the stability of this result, age was taken as an ordinal variable, which was divided into three groups and four groups, respectively, by constructing an alternative SEM. There were only a few path coefficients that differed ±0.01 from the original SEM.

Depression and Life Satisfaction in Middle-Aged and Older Adults

Some studies have suggested that older people have higher depression ( Bergdahl et al., 2005 ; Solhaug et al., 2012 ) and lower satisfaction ( Kim et al., 2018 ) than middle-aged people. However, another study found that the frequency of depression was higher ( Trollor et al., 2007 ), and life satisfaction was lower among middle-aged people ( An et al., 2020 ). In addition, a study found that the 1-year prevalence rate of depression was 7.7–9.4% among middle-aged people, and 2.6% among older adults ( Kessler et al., 2010 ). These results show that the conclusions are still inconsistent. Our study demonstrated that depression was higher and life satisfaction was lower among middle-aged people than that among older people. Among middle-aged people, although midlife introduces psychosocial resources for physical and mental health, it also carries the risk of depression ( Ellermann and Reed, 2001 ). Middle age is a time when people balance multiple roles and responsibilities in various areas of life, such as work and family ( Lachman, 2004 ). Social responsibility may lead to a greater burden and pressure for middle-aged people. As a result, middle-aged people may be more severely affected by the demands and increased responsibilities of midlife, leading to more negative emotions. Therefore, middle-aged people have a higher risk of mental health and should receive more attention.

Mediating Effects of Activities of Daily Living Disability and Instrumental Activities of Daily Living Disability

The functional disability plays an important mediating role in the relationship between age and depression/life satisfaction. With increasing age, ADL disability and IADL disability may exist, which can affect depression ( Ahn and Kim, 2015 ; Ahmad et al., 2020 ) and life satisfaction ( Enkvist et al., 2012 ) simultaneously. Additionally, ADL disability has a greater effect on this process than IADL disability. The results confirm the previous studies showing that functional disability may be a crucial risk factor for depression in middle-aged and older persons ( Qiu et al., 2020 ). Furthermore, the risk of functional disability in the older age group was higher than that in the younger age groups. The main reason for this finding may be that with increasing age, the functions of the body tissues and organs are weakened, immunity is reduced, and the ability to resist adverse external factors is weakened. Therefore, it is especially important to improve the daily living ability of older persons, delay the decline of their functional disability, reduce their depression, and maintain their life satisfaction. To prevent functional disability, it is recommended that effective health literacy education and assistance focusing on the top four difficulties with ADL (i.e., dressing, bathing or showering, eating, and getting into/out of bed) be offered. Regarding IADL, the difficulties of older people in performing household chores, preparing hot meals, and shopping for groceries could be solved with intelligent equipment, door-to-door delivery, shopping assistance, and other measures.

Depression and Life Satisfaction May Affect Each Other and Have Enduring Effects

Previous studies ( Sok, 2010 ; Yoo et al., 2016 ) have found that life satisfaction is associated with depression, but the causal relationship is unclear. Our structural equation model further showed that depression and life satisfaction may be cross affected by each other and have enduring effects. That is, the influence of previous depression (in 2013–2014) on subsequent life satisfaction (in 2015–2016) was higher than that of previous life satisfaction (in 2013–2014) on subsequent depression (in 2015–2016). The standardized coefficients were −0.18 and −0.07, respectively. Furthermore, depression among middle-aged and older adults may have a lasting effect, which is consistent with a previous study ( Lee et al., 2020 ). Our findings clarify that reducing or preventing depression as early as possible may be a more effective approach to preventing depression among middle-aged and elderly people than improving life satisfaction. The standardized coefficients were 0.60 and −0.07, respectively.

As mentation to maintain long-term life satisfaction among middle-aged and elderly people, enhancing their current life satisfaction and preventing depression are also effective ways. Furthermore, functional disability may increase depression and lead to a decrease in life satisfaction. Prevention is better than cure, and we recommend that avoiding functional disability could result in reduced depression and improved life satisfaction.

Gender Differences

Regarding ADL disability, IADL disability, depression, and life satisfaction in middle-aged and older adults, the results showed that women had higher levels of IADL disability and perceived higher depression and lower life satisfaction than men. However, there was no gender difference in ADL disability, which is consistent with the conclusion of a previous study ( Sato et al., 2001 ). The gender is an important factor in studies of functional disability, depression, and life satisfaction. Fertility, hormonal, and other physiological differences lead to different health risks between men and women. In addition, work, family, and lifestyle roles differ between women and men. The traditional role of caregivers and family workers in the family has a significant detrimental impact on the health status of older women ( Zhang et al., 2005 ). But men’s mental health also needs to be taken seriously. Our findings further demonstrate that gender differences exist on some pathways. Life satisfaction in men was influenced by IADL disability, whereas, in women, it was influenced by ADL disability.

Limitations

Some limitations to this study warrant consideration. First, the associations among age, functional ability, and depressive symptoms/life satisfaction are cross-sectional in the study and can be further validated using longitudinal data in the future. Second, the correlation between age and depression was significant but small. Whether age is weakly correlated with depression or affected by sample size requires more specific studies to clarify. Third, since the information was gathered from the participants in the study, self-report/recall bias may have existed. However, it is not easy to achieve continued participation among cohorts of middle-aged and older people in a cohort study, and the sample size should not be ignored. As a result, our findings with acceptable goodness-of-fit indices deserve paying more attention.

Depression in middle-aged people should be given closer attention. Depression and life satisfaction could affect each other and have enduring effects. Functional disability was an important mediator of depression and life satisfaction. Avoiding or improving functional disability may be an effective way to improve life satisfaction and reduce the level of depression in middle-aged and older persons. For the prevention of functional disability and depression and improvement in life satisfaction, gender differences need to be considered.

Data Availability Statement

Ethics statement.

The studies involving human participants were reviewed and approved by the Ethical Review Committee of Peking University. The patients/participants provided their written informed consent to participate in this study.

Author Contributions

AL and Y-CC designed the study, analyzed the results, and drafted and revised the manuscript. SL designed the study and drafted and revised the manuscript. MC and SH drafted and revised the manuscript. C-YL and DW analyzed the results and revised the manuscript. All authors read and approved the final article.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s Note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Acknowledgments

We thank all the participants, assistants, and researchers for their contribution to this study. We are very grateful to the highly qualified native English-speaking editors of American Journal (AJE, http://www.journalexperts.com/en/ ) for editing the manuscript with the proper English language, grammar, punctuation, spelling, and overall style. In particular, we thank the National School of Development at Peking University and the China Center for Economic Research for the provided data [the China Health and Retirement Longitudinal Study (CHARLS) team for providing the data].

Abbreviations

This work was supported by the National Natural Science Foundation of China (Grant Number 72074187), Scientific Research Grant of Fujian Province of China (Grant Number Z0230104), Social Science Foundation of Fujian Province of China (Grant Number FJ2021T009), and Natural Science Foundation of Fujian Province of China (Grant Number 2018J01129). The sponsors of the project had no role in the study design, data collection, data analysis, data interpretation, and writing the manuscript.

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