As the global population ages, the number of individuals with clinical Alzheimer’s disease and related dementias (ADRD) is rapidly increasing (Prince et al., Reference Prince, Bryce, Albanese, Wimo, Ribeiro and Ferri2013). In 2010, the worldwide prevalence of ADRD was 35.6 million people. This number is expected to increase to 115 million people worldwide by the year 2050. The number of people with preclinical Alzheimer’s disease (e.g. evidence of Alzheimer’s disease neuropathology and/or neurodegeneration without cognitive decline on standardized measures) is even higher (Brookmeyer et al., Reference Brookmeyer, Abdalla, Kawas and Corrada2018).
Unfortunately, there are no disease-altering interventions for ADRD. It is of utmost importance to identify modifiable risk factors that can prevent or delay the onset of ADRD. This is especially true for individuals at high risk of clinical dementia such as individuals who have preclinical Alzheimer’s disease but no cognitive impairment. Delaying the onset of clinical ADRD not only prolongs the individual’s quality of life but can have a significant public health impact. Delaying the onset of clinical ADRD by 5 years may translate to a savings of approximately 500,000 dollars in informal healthcare costs per individual (Zissimopoulos et al., Reference Zissimopoulos, Crimmins and St Clair2014). Therefore, researchers need to work to identify factors that promote resilience against age and disease-related cognitive declines.
Cognitive reserve (CR) is an important aspect of resilience. Promoting CR may be important for delaying the onset of clinical ADRD. Discrepancies between detected neuropathology and clinical manifestation are common (Stern, Reference Stern2009). For example, it is well known that some individuals are able to tolerate significant amounts of accumulated neuropathology yet have relatively spared cognitive functioning. CR is a construct that accounts for these discrepancies (Stern et al., Reference Stern2018). Someone with higher CR is able to withstand higher amounts of neuropathology while being able to function independently. Importantly, CR is thought to be a fluid construct in that it changes across the lifespan and is a result of experiences that occur throughout the lifespan. The fluid nature of CR is important as it highlights that individuals may potentially be able to increase CR over the course of the entire lifespan. Some important experiences or lifestyle factors that contribute to CR include educational attainment, occupational complexity, engagement in cognitively stimulating activities, engagement in active leisure activities, physical exercise, dietary factors, and lower stress (Satz et al., Reference Satz, Cole, Hardy and Rassovsky2011).
Social support is another important factor that is thought to promote CR. Increased social support, such as having more close friends, may contribute to emotional, instrumental, and informational support. This support may then promote CR by reducing stress and promoting healthier lifestyles. Another possibility is that individuals with more social support may spend more time engaging in leisure activities that are thought to promote CR. There have been no studies examining if engagement in leisure activities mediate protective effects of higher social support on declines in cognitive performance. In this important work by Ihle et al. (Reference Ihle2019), they present evidence that engagement in leisure activities may mediate the protective association between higher social support on a slower decline in executive function over a 6-year period.
Ihle et al. (Reference Ihle2019) examined data from the ongoing Vivre–Leben–Vivere (VLV) survey (Ihle et al., Reference Ihle2016). The VLV is a large interdisciplinary study examining the mental and physical health of older adults (aged 65 and older) living in Switzerland. In 2011, participants completed assessments of both social support and leisure activity engagement. Social support consisted of having the individual indicate the number of close friends that they had. Leisure activities captured different domains of activity including cognitive activities, physical activities, and social activities. A total of 18 activities were measured including: going for a walk, gardening, physical exercise, playing sports, going to a restaurant, going to the movies, excursions of 1 or 2 days, vacations 3 days or longer, playing musical instruments, other artistic activities, taking a course, playing card games, doing crossword puzzles, needlework, doing crafts, participation in political activities, volunteering in the community, and going to a sporting event. Executive functioning was then measured at the study baseline in 2011, and again 6 years later in 2017, with the part A and B of the Trailmaking Test.
First, the authors considered the association between baseline engagement in leisure activities and change in Trailmaking Test performance over the 6-year-follow-up. Individuals reporting more engagement in leisure activities tended to have less decline in Trailmaking Test performance over the 6-year-follow-up. The authors then examined the direct association between the number of close friends at baseline and changes in Trailmaking Test performance that is independent of leisure activities. The number of close friends at baseline was not associated with changes in Trailmaking Test over 6 years. The number of close friends at baseline was significantly associated with participation in leisure activities. Individuals with more close friends were more likely to engage in leisure activities with greater frequency. The resulting indirect effect of having more close friends on changes in Trailmaking Test performance mediated by leisure activity engagement was statistically significant. Participation in more leisure activities explained approximately 41% of the protective association of having more close friends at study baseline on changes in Trailmaking Test performance. These findings suggest that observed associations between having more close friends and declines in executive functioning are partially attributable to increased participation in leisure activities.
This study by Ihle et al. is consistent with a broader literature linking increased social support as protective of declines in cognitive performance over time (Kelly et al., Reference Kelly2017). This study is also consistent with literature suggesting that activity engagement is also protective of cognitive decline over time (Fratiglioni et al., Reference Fratiglioni, Marseglia and Dekhtyar2020). The Ihle et al. study provides insight into mechanisms explaining why social support may be associated with reduced cognitive decline over time. Specifically, the authors found that individuals with more close friends were more likely to engage in more leisure activities, which were subsequently associated with less declines in executive functioning over time.
As with any study, these findings also need to be interpreted within the context of limitations. First, the exposure variable (number of close friends) and the mediator (engagement in leisure activities) were measured at the same time point. Thus, causal inferences cannot be made because the temporal precedence of having more friends on engagement in leisure activities cannot be established. Reverse causality cannot be ruled out as individuals engaging in more leisure activities may cause you to have more friends. Another limitation is that the authors examined leisure activities as a composite score which does not provide insight into what sort of leisure activities were most protective. The individual components that make up leisure activities in this study, specifically physical exercise, engagement in cognitively stimulating activities, formal education, and spending time are all thought to contribute to increased CR. Identifying the individual components of leisure activities that are most protective is important and can guide future efforts to increase CR.
This study from Ihle et al. provides some insight into potential mechanisms that explain associations between social support and cognitive decline. In order to eventually develop interventions to slow cognitive decline and delay the onset of clinical ADRD dementia more studies are needed to identify the mechanisms that explain why certain lifestyle factors and social support are associated with slower cognitive decline. Similarly, new approaches are needed to be developed to better quantify complex constructs such as CR. As defined, CR is a latent construct representing the discrepancy between cognitive performance and neuropathology, thus CR cannot be directly measured (Stern et al., Reference Stern2018). This makes quantifying CR challenging (Jones et al., Reference Jones, Manly, Glymour, Rentz, Jefferson and Stern2011). Historically, CR has been measured indirectly using proxy variables (e.g. education or occupational attainment, IQ, or engagement in cognitively stimulating activities). These proxy variables are problematic for a number of reasons including: (1) proxy variables may reduce the risk of cognitive impairment through mechanisms other than CR and (2) it is impossible to examine a change in CR over time with the proxy approach. Recently, alternative approaches have been developed to estimate CR by using the residual variance in cognitive performance after regressing out the effects of neuropathological factors (Petkus et al., Reference Petkus2019; Reed et al., Reference Reed2010). The resulting residual is a quantitative estimate of CR. Someone with a higher residual has cognitive performance that is better than what would be expected given the measured neuropathology. Although limitations are also present with this approach, the residual approach is important as it serves as an attempt to quantify the complex construct of CR. Developing new approaches to quantify CR is important as a reliable and valid estimate of CR would be useful clinically to identify individuals with low CR who are at highest risk for cognitive decline. Furthermore, quantitative approaches to measure CR can be useful tools for research.
Although the prevalence and number of individuals with ADRD is increasing due to the overall aging of the population, the incidence of ADRD has been decreasing since 1990 (Roehr et al., Reference Roehr, Pabst, Luck and Riedel-Heller2018). Increased CR in the current generation of older adults due to higher formal education compared to prior generations of older adults is thought to be one potential reason for decreased incidence rates. The recent events surrounding the social distancing and lockdowns related to COVID-19 only increase the importance of understanding factors that promote CR. Social distancing and stay-at-home orders from COVID-19 likely will have significant negative impacts on CR of older adults. The consequences of these policies likely include reduced social support, increased social isolation, decreased opportunities for leisure activities outside of the home, increased stress, and less physical exercise (if one relies on a gym or fitness center). The Ihle et al. study highlights the importance of leisure activities as a potential protective factor against declines in executive functioning over time. Most individuals are currently unable to engage in the majority of the leisure activities measured in the current study due to stay-at-home orders and social distancing. The immediate ramifications of these policies on CR and the long-term consequences on ADRD risk are unknown but warrant further study. Further consideration of the impact of these policies on CR and identifying recommendations to give to older adults to maintain CR in the midst of social distancing have potential public health significance.
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As the global population ages, the number of individuals with clinical Alzheimer’s disease and related dementias (ADRD) is rapidly increasing (Prince et al., Reference Prince, Bryce, Albanese, Wimo, Ribeiro and Ferri2013). In 2010, the worldwide prevalence of ADRD was 35.6 million people. This number is expected to increase to 115 million people worldwide by the year 2050. The number of people with preclinical Alzheimer’s disease (e.g. evidence of Alzheimer’s disease neuropathology and/or neurodegeneration without cognitive decline on standardized measures) is even higher (Brookmeyer et al., Reference Brookmeyer, Abdalla, Kawas and Corrada2018).
Unfortunately, there are no disease-altering interventions for ADRD. It is of utmost importance to identify modifiable risk factors that can prevent or delay the onset of ADRD. This is especially true for individuals at high risk of clinical dementia such as individuals who have preclinical Alzheimer’s disease but no cognitive impairment. Delaying the onset of clinical ADRD not only prolongs the individual’s quality of life but can have a significant public health impact. Delaying the onset of clinical ADRD by 5 years may translate to a savings of approximately 500,000 dollars in informal healthcare costs per individual (Zissimopoulos et al., Reference Zissimopoulos, Crimmins and St Clair2014). Therefore, researchers need to work to identify factors that promote resilience against age and disease-related cognitive declines.
Cognitive reserve (CR) is an important aspect of resilience. Promoting CR may be important for delaying the onset of clinical ADRD. Discrepancies between detected neuropathology and clinical manifestation are common (Stern, Reference Stern2009). For example, it is well known that some individuals are able to tolerate significant amounts of accumulated neuropathology yet have relatively spared cognitive functioning. CR is a construct that accounts for these discrepancies (Stern et al., Reference Stern2018). Someone with higher CR is able to withstand higher amounts of neuropathology while being able to function independently. Importantly, CR is thought to be a fluid construct in that it changes across the lifespan and is a result of experiences that occur throughout the lifespan. The fluid nature of CR is important as it highlights that individuals may potentially be able to increase CR over the course of the entire lifespan. Some important experiences or lifestyle factors that contribute to CR include educational attainment, occupational complexity, engagement in cognitively stimulating activities, engagement in active leisure activities, physical exercise, dietary factors, and lower stress (Satz et al., Reference Satz, Cole, Hardy and Rassovsky2011).
Social support is another important factor that is thought to promote CR. Increased social support, such as having more close friends, may contribute to emotional, instrumental, and informational support. This support may then promote CR by reducing stress and promoting healthier lifestyles. Another possibility is that individuals with more social support may spend more time engaging in leisure activities that are thought to promote CR. There have been no studies examining if engagement in leisure activities mediate protective effects of higher social support on declines in cognitive performance. In this important work by Ihle et al. (Reference Ihle2019), they present evidence that engagement in leisure activities may mediate the protective association between higher social support on a slower decline in executive function over a 6-year period.
Ihle et al. (Reference Ihle2019) examined data from the ongoing Vivre–Leben–Vivere (VLV) survey (Ihle et al., Reference Ihle2016). The VLV is a large interdisciplinary study examining the mental and physical health of older adults (aged 65 and older) living in Switzerland. In 2011, participants completed assessments of both social support and leisure activity engagement. Social support consisted of having the individual indicate the number of close friends that they had. Leisure activities captured different domains of activity including cognitive activities, physical activities, and social activities. A total of 18 activities were measured including: going for a walk, gardening, physical exercise, playing sports, going to a restaurant, going to the movies, excursions of 1 or 2 days, vacations 3 days or longer, playing musical instruments, other artistic activities, taking a course, playing card games, doing crossword puzzles, needlework, doing crafts, participation in political activities, volunteering in the community, and going to a sporting event. Executive functioning was then measured at the study baseline in 2011, and again 6 years later in 2017, with the part A and B of the Trailmaking Test.
First, the authors considered the association between baseline engagement in leisure activities and change in Trailmaking Test performance over the 6-year-follow-up. Individuals reporting more engagement in leisure activities tended to have less decline in Trailmaking Test performance over the 6-year-follow-up. The authors then examined the direct association between the number of close friends at baseline and changes in Trailmaking Test performance that is independent of leisure activities. The number of close friends at baseline was not associated with changes in Trailmaking Test over 6 years. The number of close friends at baseline was significantly associated with participation in leisure activities. Individuals with more close friends were more likely to engage in leisure activities with greater frequency. The resulting indirect effect of having more close friends on changes in Trailmaking Test performance mediated by leisure activity engagement was statistically significant. Participation in more leisure activities explained approximately 41% of the protective association of having more close friends at study baseline on changes in Trailmaking Test performance. These findings suggest that observed associations between having more close friends and declines in executive functioning are partially attributable to increased participation in leisure activities.
This study by Ihle et al. is consistent with a broader literature linking increased social support as protective of declines in cognitive performance over time (Kelly et al., Reference Kelly2017). This study is also consistent with literature suggesting that activity engagement is also protective of cognitive decline over time (Fratiglioni et al., Reference Fratiglioni, Marseglia and Dekhtyar2020). The Ihle et al. study provides insight into mechanisms explaining why social support may be associated with reduced cognitive decline over time. Specifically, the authors found that individuals with more close friends were more likely to engage in more leisure activities, which were subsequently associated with less declines in executive functioning over time.
As with any study, these findings also need to be interpreted within the context of limitations. First, the exposure variable (number of close friends) and the mediator (engagement in leisure activities) were measured at the same time point. Thus, causal inferences cannot be made because the temporal precedence of having more friends on engagement in leisure activities cannot be established. Reverse causality cannot be ruled out as individuals engaging in more leisure activities may cause you to have more friends. Another limitation is that the authors examined leisure activities as a composite score which does not provide insight into what sort of leisure activities were most protective. The individual components that make up leisure activities in this study, specifically physical exercise, engagement in cognitively stimulating activities, formal education, and spending time are all thought to contribute to increased CR. Identifying the individual components of leisure activities that are most protective is important and can guide future efforts to increase CR.
This study from Ihle et al. provides some insight into potential mechanisms that explain associations between social support and cognitive decline. In order to eventually develop interventions to slow cognitive decline and delay the onset of clinical ADRD dementia more studies are needed to identify the mechanisms that explain why certain lifestyle factors and social support are associated with slower cognitive decline. Similarly, new approaches are needed to be developed to better quantify complex constructs such as CR. As defined, CR is a latent construct representing the discrepancy between cognitive performance and neuropathology, thus CR cannot be directly measured (Stern et al., Reference Stern2018). This makes quantifying CR challenging (Jones et al., Reference Jones, Manly, Glymour, Rentz, Jefferson and Stern2011). Historically, CR has been measured indirectly using proxy variables (e.g. education or occupational attainment, IQ, or engagement in cognitively stimulating activities). These proxy variables are problematic for a number of reasons including: (1) proxy variables may reduce the risk of cognitive impairment through mechanisms other than CR and (2) it is impossible to examine a change in CR over time with the proxy approach. Recently, alternative approaches have been developed to estimate CR by using the residual variance in cognitive performance after regressing out the effects of neuropathological factors (Petkus et al., Reference Petkus2019; Reed et al., Reference Reed2010). The resulting residual is a quantitative estimate of CR. Someone with a higher residual has cognitive performance that is better than what would be expected given the measured neuropathology. Although limitations are also present with this approach, the residual approach is important as it serves as an attempt to quantify the complex construct of CR. Developing new approaches to quantify CR is important as a reliable and valid estimate of CR would be useful clinically to identify individuals with low CR who are at highest risk for cognitive decline. Furthermore, quantitative approaches to measure CR can be useful tools for research.
Although the prevalence and number of individuals with ADRD is increasing due to the overall aging of the population, the incidence of ADRD has been decreasing since 1990 (Roehr et al., Reference Roehr, Pabst, Luck and Riedel-Heller2018). Increased CR in the current generation of older adults due to higher formal education compared to prior generations of older adults is thought to be one potential reason for decreased incidence rates. The recent events surrounding the social distancing and lockdowns related to COVID-19 only increase the importance of understanding factors that promote CR. Social distancing and stay-at-home orders from COVID-19 likely will have significant negative impacts on CR of older adults. The consequences of these policies likely include reduced social support, increased social isolation, decreased opportunities for leisure activities outside of the home, increased stress, and less physical exercise (if one relies on a gym or fitness center). The Ihle et al. study highlights the importance of leisure activities as a potential protective factor against declines in executive functioning over time. Most individuals are currently unable to engage in the majority of the leisure activities measured in the current study due to stay-at-home orders and social distancing. The immediate ramifications of these policies on CR and the long-term consequences on ADRD risk are unknown but warrant further study. Further consideration of the impact of these policies on CR and identifying recommendations to give to older adults to maintain CR in the midst of social distancing have potential public health significance.