The longitudinal path from happiness to cognitive performance: The role of loneliness and cognitive reserve

The longitudinal path from happiness to cognitive performance: The role of loneliness and cognitive reserve | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The longitudinal path from happiness to cognitive performance: The role of loneliness and cognitive reserve Rabia Khalaila, Sharon Shiovitz-Ezra, Dikla Segel-Karpas This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8785156/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 8 You are reading this latest preprint version Abstract Purpose Happiness has been linked to better cognitive outcomes in older adults. Loneliness may serve as a mediator in this relationship, while cognitive reserve (CR) may buffer or enhance these effects. This study examined the direct effect of happiness on cognitive performance over two years, the mediating role of loneliness in this relationship, and whether CR moderates the direct and indirect (via loneliness) effects of happiness on cognitive performance. Methods Data were drawn from a longitudinal survey of adults aged 50 and above (N = 55,340). Cognitive performance was assessed at baseline (T1) and at a two-year follow-up (T2) using a composite score combining immediate recall, delayed recall, numeracy, and verbal fluency. Happiness was measured at T1 using a single-item scale, and loneliness was assessed via the short R-UCLA Loneliness Scale. CR was computed as a standardized composite of educational attainment, occupational complexity, and engagement in cognitive activities. Results Happiness at T1 significantly predicted better cognitive performance at T2 (B = 0.0098, p = .0197), and loneliness partially mediated this effect (indirect B = 0.002, 95% CI [0.001, 0.003]). CR moderated both the direct effect of happiness (interaction B = -0.0084, p = .0104) and the indirect effect via loneliness (interaction B = 0.0059, p = .0009), with stronger associations at lower levels of CR. Conclusion Happiness promotes cognitive health in later life, partly by reducing loneliness, especially among individuals with lower CR, highlighting the importance of emotional well-being and social connectedness in cognitively vulnerable populations. Cognitive performance Happiness Loneliness CR Moderated mediation Figures Figure 1 Figure 2 Figure 3 INTRODUCTION The relationship between happiness and cognitive functioning is a nuanced and extensively researched area within psychological and gerontological sciences. The literature suggests that positive affect and well-being are linked to improved cognitive health, particularly in aging populations. The exact mechanism behind this association is still not fully understood. In this study, we aimed to enhance our understanding of the relationship between happiness and cognitive function in older adults by examining how loneliness serves as a mediator and how cognitive reserve (CR) acts as a moderator. Positive Affect and Cognitive Functioning Happiness and positive affect are linked to improved cognitive performance in older adults. As people age, maintaining positive affect becomes increasingly vital for cognitive resilience, especially in late life (Hughes, Agrigoroaei, Jeon, Bruzzese, & Lachman, 2018 ). Hittner et al. ( 2020 ) demonstrated that positive affect is linked to less memory decline over nine years, suggesting a protective role of happiness in cognitive aging. Similarly, higher positive affect correlated with slower cognitive deterioration over a 12-year follow-up, emphasizing the potential long-term benefits of happiness on cognition (Berk, van Boxtel, Köhler, & van Os, 2017 ). Prospective studies highlighted a dynamic and bidirectional relationship between well-being and cognitive performance (Allerhand, Gale, & Deary, 2014 ; Hill, van Boxtel, Ponds, Houx, & Jolles, 2005 ). High positive affect often correlates with better memory, processing speed, and executive functioning. Low levels are associated with increased risk for cognitive decline. Several theoretical models explain these associations. Fredrickson’s ( 2001 ) ‘broaden-and-build theory’ posits that positive emotions expand cognitive and behavioral repertoires, thereby fostering resilience and cognitive flexibility. This was supported by neuropsychological evidence suggesting that positive affect influences neural processes underlying cognition (Ashby, Isen, & Turken, 1999 ). Moreover, the neuroprotective effects of happiness may involve reduced neurodegeneration or neuroinflammation resulting in enhanced neuroplasticity (Anthony, Turnbull, Tadin, & Lin, 2024 ). Another theory suggested that positive affect could reduce cortisol and inflammatory markers such as C-reactive protein, both of which are associated with harmful effects on cognitive function (Folkman & Moskowitz, 2000 ). This implies that positive emotions contribute to a healthier neuroendocrine profile, thus supporting cognitive resilience. Folkman and Moskowitz ( 2000 ) proposed that positive affect has a crucial role in coping and stress buffering: Experiencing positive emotions enhances adaptive coping strategies, in turn reducing perceived stress and minimizing negative health effects. Buckner ( 2004 ) highlighted that chronic stress and negative emotions can harm hippocampal volume and memory, but positive affect acts as a buffer against these detrimental effects, thereby supporting cognitive function. The literature also explores behavioral pathways. Positive affect influences health-related behaviors such as increased physical activity, better sleep, and social engagement (Argyle, Martin, & Lu, 1995 ). These behaviors are linked to enhanced neurocognitive health, as physical activity stimulates neurogenesis and promotes synaptic plasticity (Folley, Zhou, Llewellyn, & Hyppönen, 2019 ). Similarly, social interaction, fostered by positive moods, provides cognitive stimulation and emotional support, which buffer against decline. Conversely, loneliness, characterized by a sense of social disconnection or lack of meaningful social interactions (de Jong Gierveld, 1998 ), can have a detrimental impact on cognitive health. Evidence suggests that loneliness is strongly linked to cognition in older adults. Lara et al.’s ( 2019 ) review indicated that loneliness and social isolation are significantly linked to the risk of cognitive deterioration, with loneliness contributing to poorer cognitive outcomes over time. Similarly, Cardona and Andrés ( 2023 ) found that social isolation and loneliness are associated with higher rates of cognitive decline. Harrington et al. ( 2023 ) further reinforced this link through a systematic review and meta-analysis, showing that loneliness is consistently related to decreased cognitive function in older adults without dementia. Additionally, Boss et al. ( 2015 ) highlighted that loneliness negatively impacts various domains of cognition including memory, executive function, and processing speed. Although happiness and loneliness are typically studied independently in relation to cognitive outcomes, they are likely interrelated. Positive affect fosters social connection and resilience (Fredrickson, 2001 ), whereas loneliness reflects a breakdown of these processes. Thus, loneliness may represent a key pathway through which happiness influences later-life cognition. Therefore, this study aimed to address this gap and enhance our understanding of the behavioral mechanisms that underlie the connection between happiness and cognitive function via loneliness. The current study also makes a significant contribution by examining the moderating role of CR, highlighting its importance in understanding the dynamics at play. CR and cognition CR is a key concept explaining why some individuals maintain cognitive functioning despite age-related brain changes. Opdebeeck et al. ( 2015 ) defined CR as the brain's resilience to neuropathological damage, enabling efficient use of neural networks to sustain cognitive performance. This adaptive ability helps older adults compensate for structural brain changes, delaying cognitive decline and functional impairments. The relationship between CR and cognitive function is based on the idea that lifelong mental activities, education, and social engagement help develop flexible neural networks. Thus, CR is a structural resource accumulated throughout the life course. Stern ( 2009 ) indicated that higher CR enhances neural processing and cognitive flexibility, which buffer neurodegenerative effects. Studies have shown that CR proxies— education and occupational complexity—are linked to better cognitive outcomes in aging populations (Opdebeeck et al., 2015 ). Further studies such as Zhang et al. ( 2024 ), indicated that CR mediates the relationship between physical activity and cognitive function, while Gonzales et al. ( 2025 ) highlighted the benefits of social engagement in reducing cognitive decline. Schrempft et al. ( 2023 ) stressed that socioeconomic factors throughout life shape CR, reinforcing the need for a multidimensional approach to measuring it. The protective effects of CR are particularly evident in older populations. Martin et al. ( 2023 ) found that higher CR in centenarians correlated with better cognitive functioning and independence. Berezuk et al. ( 2021 ) demonstrated that higher CR benefits real-world functioning in individuals with mild cognitive impairment, emphasizing the broader relevance of CR to everyday life. The extensive body of evidence indicates that CR plays a vital role in healthy aging by providing a buffer against cognitive decline and enhancing the capacity for neural compensation. While CR is often conceptualized as a direct buffer against neuropathology, recent work has suggested it may also shape how psychosocial factors influence cognition. For instance, Opdebeeck et al. ( 2018 ) found that CR moderated the association between mood and cognitive outcomes, and Khalaila ( 2025 ) found that CR moderated the association between depression and cognitive performance. These indicate the need for models that examine psychosocial and structural resources in interaction rather than isolation. Building CR through education, occupation, social engagement, and lifelong learning remains a promising avenue for promoting successful aging and reducing the burden of age-related neurodegenerative diseases. In the present study, we wanted specifically to determine whether the positive effects of happiness on cognitive function are stronger among individuals with low CR, and if CR can mitigate the harmful effects of loneliness on cognitive performance in old age. To explore whether structural resources can compensate when social and psychological resources are low, we used a longitudinal dataset with two measurements and examined a moderated mediation model in which CR moderates the path between happiness and cognitive performance, and between loneliness and cognitive performance (Fig. 1 ). Based on the reviewed literature we hypothesized: Happiness at baseline (T1) will be positively associated with cognitive performance at follow-up (T2). The relationship between happiness at baseline (T1) and cognitive performance at follow-up (T2) will be partially mediated by loneliness, so that greater happiness will be associated with lower loneliness levels, which in turn will be associated with better cognitive performance. The direct effect of happiness at baseline (T1) on cognitive performance at follow-up (T2) will be moderated by CR, so that the positive effect of happiness will be stronger among individuals with lower CR. The indirect effect of happiness at baseline (T1) on cognitive performance at follow-up (T2) via loneliness will be moderated by CR, so that the negative effect of loneliness on cognitive performance will be stronger among individuals with lower CR. DESIGN AND METHODS Data The study utilized data from the Survey of Health, Aging and Retirement in Europe (SHARE) (Börsch-Supan et al., 2013 ). This survey provided comprehensive information across various domains for a representative sample of community-dwelling adults aged 50 and older, as well as their spouses of any age. Questionnaires were administered through Computer Assisted Personalized Interviews (CAPI). The current analysis is based on data collected in 2013 (wave 5: baseline) and in 2015 (wave 6: follow-up) (Börsch-Supan, 2020 ). A total of 55,340 participants aged 50 or older who did not have a diagnosis of Alzheimer's disease or dementia at Time 1, took part in the study. This sample represented 15 countries: Austria, Belgium, Switzerland, the Czech Republic, Germany, Denmark, Estonia, Spain, France, Israel, Italy, Luxembourg, the Netherlands, Sweden, and Slovenia. Ultimately, 32,325 participants provided complete information for cognitive assessments at the two study waves used in the current study (Time 1 and Time 2). To compare the study participants with those excluded due to missing follow-up information, Student's t-test for independent groups was employed for continuous variables, while chi-square tests were used for categorical variables. The excluded participants at Time 2 (N = 23,015) participants were older, had more chronic diseases, greater functional disability, more depressive symptoms, lower CR, and worse cognitive performance at Time 1. Moreover, they were more likely to be male and less physically active (see Supplementary Table 1). Measures Dependent variable Cognitive Performance - We integrated four cognitive metrics into a single measure - immediate recall, delayed recall, numeracy, and verbal fluency. These components create a validated assessment of cognitive function in later life (Khalaila, Dintica, & Yaffe, 2024 ). The immediate and delayed recall tasks evaluate short-term verbal learning, memory, and information retention (Cheke & Clayton, 2013 ). In the immediate recall task, participants repeat ten words that are read aloud to them. After a ten-minute interval, they are asked to recall the words in the delayed recall task. Serial sevens test was used for the numeracy component, where participants sequentially subtract seven from 100, up to five times. Each correct subtraction earns one point (Scholey, Harper, & Kennedy, 2001 ). Scores on the numeracy test range from 0 to 5. Verbal fluency, which assesses executive function and language skills (Henry, Crawford, & Phillips, 2004 ), requires participants to name as many animals as possible within one minute; naming more than 45 animals earns 45 points. We standardized the scores from these four tests using z-scores (M = 0, SD = 1), and calculated the average of the standardized scores to determine overall cognitive performance (Cohn-Schwartz & Khalaila, 2022 ). The combined scores ranged from − 2.8 to 2.8 at baseline (T1) and from − 2.9 to 2.8 at the two years follow-up point (T2). Independent variable Happiness was measured using a single-item "I look back on my life with happiness", rated on 1 ("never") to 4 ("often") scale This variable was assessed at baseline (T1). The use of a single-item scale to measure happiness has been validated and found to be reliable in previous research (Zhu et al., 2024 ). Mediator Loneliness was assessed using the short version of the R-UCLA Loneliness Scale (Hughes, Waite, Hawkley, & Cacioppo, 2004 ) consisting three items rated on a scale ranging from 1 (often) to 3 (hardly ever or never): feeling a lack of companionship, left out and isolated from others. Items were recoded so that the total score ranges from 3 to 9, with a higher score indicating greater loneliness (α = .73). Cognitive reserve (CR) CR was defined as a combined indicator of education attainment, occupational complexity, and cognitive activities. These factors were selected based on prior research (Khalaila et al., 2024 ; Opdebeeck et al., 2018 ). Education attainment was assessed on a 7-point scale (0 to 6) based on the ISCED-97 classification: 0 = none, 1 = primary level, 2 = lower secondary, 3 = upper secondary, 4 = post-secondary no tertiary, 5 = first stage of tertiary, 6 = second stage of tertiary. Occupational complexity was categorized using the ISCO-08 occupational skill levels, with scores ranging from 0 to 4: 0 = unemployed, 1 = simple physical or manual tasks (e.g., elementary occupations), 2 = tasks requiring literacy, numeracy, communication, or manual dexterity (e.g., service and sales workers), 3 = complex tasks requiring specialized knowledge (e.g., technicians and associate professionals), and 4 = tasks requiring complex problem-solving and theoretical knowledge (e.g., professionals, physicians). Cognitive activities were measured by self-report of four activities: attending an educational course, reading books or magazines, doing word or number games (e.g., crosswords), and playing cards or games, with scores ranging from 0 to 4. The composite measures of CR were constructed by averaging the standardized scores of these three metrics. A higher score indicated greater CR. Covariates The study controlled for two baseline variables: loneliness and cognitive performance at T1. Additionally, it considered six covariates: age, gender (1 = women, 0 = men), number of chronic diseases, depression, physical activity, and activities of daily living (ADL). Participants were asked to indicate whether they had ever been diagnosed with any of 14 chronic conditions, including heart failure, hypertension, cerebrovascular disease, diabetes, hyperlipidemia, and chronic lung disease. Depressive symptoms were assessed using the European Depression (EURO-D) scale (Prince et al., 1999 ) consisting of 12 items evaluating various symptoms of depression (1 = present; 0 = absent), leading to a total possible score ranging from 0 to 12. Physical activity was measured using two indicators: moderate activity and vigorous activity. These indicators were combined into a single variable with two levels: "Never participate in vigorous or moderate physical activity" or "Active." Functional disability was assessed by counting the number of areas in which participants reported difficulties in daily activities, based on a list of six areas including dressing, bathing, and eating (Katz, Downs, Cash, & Grotz, 1970 ). Data Analysis Pearson correlation tests were used to examine the bivariate relationships among study variables. To investigate our hypotheses related to mediation and moderated mediation, we followed the analytical approaches outlined by Preacher and Hayes ( 2008 ) using PROCESS models 4 and 15. In our framework, loneliness acted as a mediator between happiness and cognitive performance, and CR served as a moderator, modifying both the direct and indirect pathways. First, we evaluated the direct and indirect effect of happiness on cognitive performance using PROCESS mediation model 4. We then implemented the moderated-mediation model 15 (Hayes, 2012 ) examining the moderating role of CR in the direct and indirect effect of happiness on cognitive performance. Simple slopes analyses determined the conditional effects of the direct and indirect effects at three levels of the moderator (CR): -1 standard deviation (Low CR), Average CR, and + 1 standard deviation (High CR). In all statistical analyses we controlled for the covariates. All statistical analyses were conducted using SPSS version 28.0 and the PROCESS tool (Hayes, 2012 ). RESULTS Table 1 presents the descriptive statistics for the study sample. The study sample included 55.8% women, ages ranged from 50 to 110 years (M = 65.0, SD = 9.8). On average, participants reported 1.74 chronic diseases, low depressive symptoms (M = 2.57), and minimal dependency in daily activities (ADL M = 0.24). Most were physically active (88%), with average happiness rated 3.35/4 and loneliness increasing slightly from baseline (3.80) to follow-up (3.88). Table 1 Descriptive statistics of the study variables (N = 55,340) Covariates and control variables N (%) Mean (S.D) Range Gender – T1 Men 24435 (44.2) Women 30905 (55.8) Age – T1 65.0 (9.8) 50–110 ADL– T1 0.24 (0.8) 0–6 Number of chronic Diseases – T1 1.74 (1.5) 0–14 Physical activity – T1 Never participate in vigorous or moderate physical activity 6606 (12.0) Active 48364 (88.0) Depression– T1 2.57 (2.2) 0–12 Loneliness – T1 3.80 (1.3) 3–9 Cognitive performance – T1 -0.005 (0.8) -2.8–2.8 Moderator Cognitive reserve – T1 -0.000 (1.2) -2.8–3.7 Independent variable Happiness – T1 3.35 (0.7) 1–4 Mediator Loneliness – T2 3.88 (2.2) 3–9 Dependent variable Cognitive performance - T2 0.000 (0.80) -2.9–2.8 Table 2 presents the Pearson correlations among the study variables. Cognitive outcomes are positively associated with happiness (r = 0.11, p< .001) and negatively associated with loneliness (r= -0.22, p< .001). Moreover, CR is positively associated with cognitive performance (r = 0.49, p< .001) and happiness (r = 0.14, p< .001), and negatively correlated with loneliness (r= -0.14, p< .001). Table 2 Pearson correlations between study variables and cognitive performance – T2 1 2 3 4 5 6 7 8 9 10 11 1. Cognitive performance – T2 1.00 2. Happiness – T1 0.11*** 1.00 3. Loneliness – T2 -0.22*** -0.18** 1.00 4. – T1 0.49*** 0.14** -0.14*** 1.00 5. Age– T1 -0.40*** 0.01 0.13** -0.16*** 1.00 6. Gender – T1 -0.01** 0.02* -0.09** 0.09** -0.01** 1.00 7. Chronic diseases – T1 -0.19** -0.11** 0.16*** − .011** 0.27*** -0.05** 1.00 8. Physical activity – T1 0.21*** 0.09** -0.13*** 0.19*** -0.24*** 0.04** -0.19*** 1.00 9. ADL– T1 -0.16** -0.10** 0.14*** -0.13*** 0.20*** -0.02* 0.26*** -0.38*** 1.00 10. Cognitive performance – T1 0.66*** 0.14*** -0.17*** 0.47*** -0.38*** -0.02* -0.18*** 0.28*** -0.26*** 1.00 11. Depression – T1 -0.20** -0.26*** 0.30*** -0.20*** 0.10** -0.19*** 0.31*** -0.23*** 0.28*** -0.26*** 1.00 12. Loneliness – T1 -0.17** -0.18*** 0.50*** -0.12*** 0.12** -0.08** 0.17*** -0.15*** 0.15** -0.16** 0.32*** Mediation analyses PROCESS model 4 was used to examine the longitudinal relationship between happiness and cognitive performance, as well as to determine whether loneliness mediated the effect. The results showed a significant total direct effect of happiness on cognitive performance when the mediator was not included (B = 0.012, SE = 0.004, 95% CI = 0.004 to 0.020, p = 0.004). After including loneliness as a mediator, the direct effect of happiness on cognitive performance decreased but remained significant (B = 0.009, SE = 0.004, 95% CI = 0.001 to 0.018, p = 0.019). Additionally, a significant indirect effect was found through loneliness (B = 0.002, 95% CI = 0.001 to 0.003), indicating that loneliness partially explains the relationship between happiness and cognitive performance. This suggests that lower levels of happiness are associated with increased feelings of loneliness which, in turn, have a negative association with cognitive performance. Moderated – mediation analyses Table 4 presents the conditional indirect effects of happiness on cognitive performance through loneliness, moderated by CR, using PROCESS model 15. The first model in Table 3 examines the effect of happiness on the mediator, loneliness. The results indicate that lower levels of happiness are associated with higher levels of loneliness (b= -0.087, SE = 0.009, t= -9.32, p < 0.001). Table 3 Direct and indirect effect of Happiness (T1) on cognitive performance (T2) through the mediator (Loneliness – T2) conditionally in the level of Cognitive reserve (CR) - T1 (N = 26,648) Effect of happiness – T1 on mediator – Loneliness-T2 B SE t p Adj R2 (p.value) Happiness – T1 ◊ Loneliness – T2 − .0873 .0094 -9.3209 .0000 0.2957 (.0000) Effects on dependent variable – Cognitive performance-T2 B SE t p Adj R2 (p.value) Happiness (T1) ◊ cognitive performance (T2) .0098 .0042 2.3328 .0197 0.5872 (.0000) Loneliness (T2) ◊ cognitive performance (T2) − .0256 .0028 9.3167 .0000 CR (T1) ◊ cognitive performance (T2) .1125 .0145 7.7689 .0000 Happiness*CR ◊ cognitive performance − .0084 .0033 -2.5609 .0104 loneliness*CR ◊ cognitive performance .0059 .0018 3.3169 .0009 Covariates and control variables – T1 Age (T1) − .0143 0004 -38.2109 .0000 Gender (T1) − .0568 .0063 -8.9589 .0000 ADL (T1) − .0117 .0056 -2.0824 .0373 Number of chronic diseases (T1) − .0058 .0023 -2.5857 .0097 Physical activity (T1) .0633 .0122 5.2001 .0000 Depression (T1) − .0078 .0017 -4.6041 .0000 Loneliness (T1) .0012 .0029 .4004 .6888 Cognitive performance (T1) .5837 .0052 112.1153 .0000 Notes: ADL = Activities of daily living The second model in Table 3 evaluates the impact of happiness, loneliness, CR, and their interactions (loneliness * CR and happiness * CR) on cognitive performance. This model was significant [F(13) = 2914.52, P = 0.000] and explained approximately 59% of the variance in cognitive performance two years later. Additionally, there is a significant interaction between happiness and CR affecting cognitive performance (b = -0.0084, SE = 0.0033, t = -2.56, p = 0.0104). This interaction indicates a notable moderating effect, with the strongest positive relationship between happiness and cognitive performance occurring at low levels of CR (-1 SD CR; b = 0.019, SE = 0.005, t = 3.47, p < 0.001). The effect diminishes at moderate levels (average CR; b = 0.008, SE = 0.004, t = 2.06, p = 0.038) and becomes non-significant at high levels of CR (+ 1 SD CR; b= -0.001, SE = 0.006, t= -0.27, p = 0.78), as illustrated in Fig. 2 . Furthermore, there is a significant interaction between the mediator (loneliness) and CR related to cognitive performance (b = 0.0059, SE = 0.0018, t = 3.316, p = 0.0009) (see Fig. 3 ). The strongest negative relationship between loneliness and cognitive performance are found at low levels of CR (-1 SD CR; b= -0.032, SE = 0.003, t= -10.05, p < 0.000). The effect lessens at moderate levels (average CR; b= -0.024, SE = 0.002, t= -8.93, p < 0.000) and at high levels CR (+ 1 SD CR; b= -0.017, SE = 0.003, t= -4.55, p < 0.000). DISCUSSION The aging of the population implies a growing number of individuals who suffer from normal age-related cognitive decline as well as pathological cognitive decline such as Alzheimer's Disease (Cox & Deary, 2022 ). The personal, familial and social costs of memory decline urge researchers to identify risk and protective factors. In addition to biological and neurological processes that are associated with memory decline (Cox & Deary, 2022 ; Jin & Cai, 2023 ), studies have repeatedly demonstrated the role that psychosocial aspects play in this regard (Zahodne, 2021 ). Positive affectivity (Hughes et al., 2018 ) and social relationships (Zahodne, 2021 ) are prominent psychological factors that were found to decrease the risk of cognitive decline, and their protective effect is often ascribed to neurological (Ashby et al., 1999 ), physiological (Steptoe, Wardle, & Marmot, 2005 ), and behavioral processes (health behaviors) (Argyle et al., 1995 ). In this paper, we explored a social pathway, linking happiness to cognitive function via the experience of loneliness. Our findings suggest that loneliness partially mediates the relationship between happiness and cognitive performance. Interpersonal theories that concern affective states and traits emphasize that the experience of positive or negative emotions is not only an intra-individual process, but rather an interpersonal experience (Coyne, 1976; Van Kleef, 2009 ). In his classic work, Coyne (1976) suggested that depression is expressed in social behavior and elicits negative reactions and rejection from others that, in turn, strengthen the depression. More current works have found that negative attributes such as hostility result in increased loneliness, and this relationship is partially attributed to decreased social contact, possibly because the expression of hostility deters others (Segel-Karpas & Ermer, 2021 ; Segel-Karpas & Ayalon, 2020 ). On the other hand, positive affect or positive attributes can attract others by signaling safety and approachability (Van Kleef, 2009 ), in addition to allowing the individual to explore and structure positive social experiences (Fredrickson, 2001 ). In our case, to some extent, happiness protects against the experience of loneliness that, in turn, is associated with deterioration in cognitive performance. According to the Evolutionary Theory of Loneliness (Cacioppo et al., 2006 ), loneliness functions as an adaptive signal to reconnect socially to increase chances of survival. However, when chronic, it biases cognitive processes toward heightened vigilance for social threat and undermines attention, memory, and executive control (Cacioppo & Hawkley, 2009 ). Over time, these cognitive processes and stress-related mechanisms contribute to decline in cognitive functioning (Cacioppo & Hawkley, 2009 ). Our study suggests that the experience of happiness in later life could be one of the factors that both directly affect cognitive function and also distance the loneliness that, in turn, also decreases cognition. However, the significance of happiness and loneliness for cognitive performance is not uniform. These personal and social aspects have a more meaningful role when CR is low. Thus, people with high CR can not only cope with neurological changes better than those with low CR (Khalaila et al., 2024 ), but are also less affected by psychosocial risk and protective factors. In other words, when cognition can be preserved via other mechanisms, the psychosocial aspects have a less significant role. However, those with low CR who also experience low happiness and high loneliness levels, are at increased risk for low cognitive performance. In should be noted that whereas the effect of loneliness on cognitive performance remains significant at all levels of CR, the effect of happiness becomes insignificant when CR is high, possibly suggesting that loneliness is a greater risk factor than unhappiness. Our study supports previous studies that have found variability in the association between psychosocial variables and cognitive performance. For example, the association between depression (Khalaila, 2025 ), negative mood (Opdebeeck et al., 2018 ) and cognitive function is weaker when CR is high. Similarly, social contact is more beneficial to cognitive performance for individuals with lower levels of openness to experience than for those with higher levels of openness to experience, suggesting that those who seek cognitive stimuli elsewhere are less dependent on social relationships for better cognitive performance (Segel-Karpas & Lachman, 2018 ). Overall, our findings contribute to the growing body of research on sociopsychological and structural risk and protective factors for cognitive performance in older adulthood. We suggest that when considering social risk factors such as loneliness (Cacioppo & Hawkley, 2009 ), other factors such as CR should be taken into account. Despite its strengths—large representative dataset, longitudinal design, and a robust composite measure of cognitive reserve—this study has several limitations. Only two waves of data were used, preventing analysis of long-term trajectories. Future work could test how CR shapes the cumulative effects of happiness and loneliness on cognition. Happiness was measured with a single item; broader measures and inclusion of other risk factors such as personality traits (Segel-Karpas & Lachman, 2018 ) or cognitive schemas (Segel-Karpas & Ayalon, 2020 ) are warranted. Finally, individuals with dementia were excluded to focus on normal aging, but examining psychosocial factors and CR in dementia may help identify ways to slow cognitive decline. Theoretically, the current study joins that body of research aiming at identifying risk and protective factors for cognitive performance in older adulthood, suggesting that CR could act as a buffer against the harmful effects of loneliness and unhappiness. Specifically, it intimates that psychosocial and structural resources should not be viewed as parallel but independent predictors of cognitive health, but rather as dynamically interacting: when structural reserves are limited, psychosocial factors such as happiness and loneliness become disproportionately important. This extends both broaden-and-build theory and CR theory by highlighting their conditional interplay, suggesting a dual-resilience framework in which emotional well-being and structural reserve act as compensatory buffers. Practically, our findings highlight the importance of developing CR across the life course through education, cognitively demanding work, and lifelong learning. At the same time, they suggest that reducing loneliness should take priority over enhancing happiness since loneliness exerts a more persistent effect on cognition, even among those with high CR. Together, these results point to a dual strategy: strengthening CR over time while addressing loneliness as an urgent and fundamental risk factor in later life. Declarations Author Contribution All authors contributed to the study conception and design. R.K analyzed the data and wrote the methods and results sections, prepared the tables and figures, S.S.E wrote the introduction and literature review, and D.S.K wrote the discussion and conclusion . All authors review and approved the final manuscript. Acknowledgement This paper uses data from SHARE Wave 5 (DOI: 10.6103/SHARE.w5.710) and Wave 6 (DOI: 10.6103/SHARE.w6.710). The SHARE data collection has been primarily funded by the European Commission through FP5–FP7, Horizon 2020, and Horizon Europe, as well as national funding sources. The SHARE data are available free of charge for scientific use to registered researchers via the SHARE Research Data Center (www.share-project.org). Access requires prior registration and approval. Data Availability This paper uses data from SHARE Wave 5 (DOI: 10.6103/SHARE.w5.710) and Wave 6 (DOI: 10.6103/SHARE.w6.710). The SHARE data collection has been primarily funded by the European Commission through FP5–FP7, Horizon 2020, and Horizon Europe, as well as national funding sources. The SHARE data are available free of charge for scientific use to registered researchers via the SHARE Research Data Center (www.share-project.org). Access requires prior registration and approval. References Allerhand M, Gale CR, Deary IJ (2014) The dynamic relationship between cognitive function and positive well-being in older people: A prospective study using the English longitudinal study of aging. 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Int J Epidemiol 42:992–1001. https://doi.org/10.1093/ije/dyt088 Buckner RL (2004) Memory and executive function in aging and AD: Multiple factors that cause decline and reserve factors that compensate. Neuron 44(1):195–208. https://doi.org/10.1016/j.neuron.2004.09.006 Cacioppo JT, Hawkley LC (2009) Perceived social isolation and cognition. Trends Cogn Sci 13(10):447–454. https://doi.org/10.1016/j.tics.2009.06.005 Cacioppo JT, Hughes ME, Waite LJ, Hawkley LC, Thisted RA (2006) Loneliness as a specific risk factor for depressive symptoms: Cross-sectional and longitudinal analyses. Psychol Aging 21(1):140–151. https://doi.org/10.1037/0882-7974.21.1.140 Cardona M, Andrés P (2023) Are social isolation and loneliness associated with cognitive decline in ageing? Front Aging Neurosci 15:1075563. https://doi.org/10.3389/fnagi.2023.1075563 Cheke LG, Clayton NS (2013) Do different tests of episodic memory produce consistent results in human adults? 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Am Psychol 55:647–654. https://doi.org/10.1037/0003-066X.55.6.647 Fredrickson BL (2001) The role of positive emotions in positive psychology: The broaden-and-build theory of positive emotions. Am Psychol 56(3):218–226. https://doi.org/10.1037/0003-066X.56.3.218 Gonzales E, Whetung C, Lee YJ (2025) Education and formal volunteering delays cognitive decline among Hispanics: Implications for health interventions. J Gerontol Soc Work 68(5):737–757. https://doi.org/10.1080/01634372.2025.2504071 Harrington KD, Vasan S, Kang JE, Sliwinski MJ, Lim MH (2023) Loneliness and cognitive function in older adults without dementia: A systematic review and meta-analysis. J Alzheimer’s Disease 91(4):1243–1259. https://doi.org/10.3233/JAD-220832 Hayes AF (2012) PROCESS [Macro]. Retrieved from http://afhayes.com/ introduction-to-mediation-moderation-and-conditional-process-analysis.html Henry JD, Crawford JR, Phillips LH (2004) Verbal fluency performance in dementia of the Alzheimer’s type: A meta-analysis. Neuropsychologia 42(9):1212–1222. https://doi.org/10.1016/j.neuropsychologia.2004.02.001 Hill RD, van Boxtel MP, Ponds R, Houx PJ, Jolles J (2005) Positive affect and its relationship to free recall memory performance in a sample of older Dutch adults from the Maastricht aging study. Int J Geriatr Psychiatry 20(5):429–435. https://doi.org/10.1002/gps.1300 Hittner EF, Stephens JE, Turiano NA, Gerstorf D, Lachman ME, Haase CM (2020) Positive affect is associated with less memory decline: Evidence from a 9-year longitudinal study. Psychol Sci 31(11):1386–1395. https://doi.org/10.1177/0956797620953883 Hughes ML, Agrigoroaei S, Jeon M, Bruzzese M, Lachman ME (2018) Change in cognitive performance from midlife Into old Age: Findings from the Midlife in the United States (MIDUS) Study. J Int Neuropsychol Soc 24(8). https://doi.org/10.1017/S1355617718000425 Hughes ME, Waite LJ, Hawkley LC, Cacioppo JT (2004) A short scale for measuring loneliness in large surveys: Results from two population-based studies. Res Aging 26(6):655–672. https://doi.org/10.1177/0164027504268574 Jin M, Cai SQ (2023) Mechanisms underlying brain aging under normal and pathological conditions. Neurosci Bull 39:303–314. https://doi.org/10.1007/s12264-022-00969-9 Katz S, Downs TD, Cash HR, Grotz RC (1970) Progress in development of the index of ADL. Gerontologist 1:20–30 Khalaila R (2025) The moderation effect of cognitive reserve on the longitudinal association between depression and cognitive performance among older adults. Aging Ment Health 1–10. https://doi.org/10.1080/13607863.2025.2545360 Khalaila R, Dintica C, Yaffe K (2024) The association between cognitive reserve and cognitive trajectories among older adults. Innov Aging 8(2). https://doi.org/10.1093/geroni/igae014 Lara E, Caballero FF, Rico-Uribe LA, Olaya B, Haro JM, Ayuso‐Mateos JL, Miret M (2019) Are loneliness and social isolation associated with cognitive decline? Int J Geriatr Psychiatry 34(11):1613–1622. https://doi.org/10.1002/gps.5174 Martin P, Gondo Y, Lee G, Woodard JL, Miller LS, Poon LW (2023) Cognitive reserve and cognitive functioning among oldest old adults: findings from the Georgia Centenarian Study. Exp Aging Res 49(4):334–346. https://doi.org/10.1080/0361073X.2022.2106717 Opdebeeck C, Matthews FE, Wu YT, Woods RT, Brayne C, Clare L (2018) Cognitive reserve as a moderator of the negative association between mood and cognition: evidence from a population-representative cohort. Psychol Med 48(1):61–71. https://doi.org/10.1017/S003329171700126X Opdebeeck C, Nelis SM, Quinn C, Clare L (2015) How does cognitive reserve impact the relationships between mood, rumination and cognitive function in later life? Aging Mental Health 19(8):705–712 Preacher KJ, Hayes AF (2008) Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models. Behav Res Methods 40:879–891. https://doi.org/10.3758/brm.40.3.879 Prince MJ, Reischies F, Beekman AT, Fuhrer R, Jonker C, Kivela SL, Lawlor BA, Lobo A, Magnusson H, Fichter M, van Oyen H, Roelands M, Skoog I, Turrina C, Copeland JR (1999) Development of the EURO-D scale–a European, Union initiative to compare symptoms of depression in 14 European centres. Br J Psychiatry 174:330–338. https://doi.org/10.1192/bjp.174.4.330 Scholey AB, Harper S, Kennedy DO (2001) Cognitive demand and blood glucose. Physiol Behav 73(4):585–592. https://doi.org/10.1016/S0031-9384(01)00476-0 Schrempft S, Trofimova O, Künzi M, Draganski B, Kliegel M, Stringhini S (2023) Life-course socioeconomic conditions and cognitive performance in older adults: a cross-cohort comparison. Aging Ment Health 27(4):745–754. https://doi.org/10.1080/13607863.2022.2084511 Segel-Karpas D, Ayalon L (2020) Loneliness and hostility in older adults: A cross-lagged model. Psychol Aging 35(2):169–176. https://doi.org/10.1037/pag0000417 Segel-Karpas D, Ermer A (2021) Cynical hostility and loneliness in older adult married couples: An indirect effect through friendships. Journals Gerontology: Ser B 76(2):306–316. https://doi.org/10.1093/geronb/gbaa170 Segel-Karpas D, Lachman ME (2018) Social contact and cognitive functioning: The role of personality. Journals Gerontology: Ser B Psychol Sci Social Sci 73(6):974–984. https://doi.org/10.1093/geronb/gbw079 Steptoe A, Wardle J, Marmot M (2005) Positive affect and health-related neuroendocrine, cardiovascular, and inflammatory processes. Proceedings of the National Academy of Sciences, USA, 102, 6508–6512 Stern Y (2009) Cognitive reserve. Neuropsychologia 47:2015–2028. https://doi.org/10.1016/j.neuropsychologia.2009.03.004 Van Kleef GA (2009) How emotions regulate social life: The emotions as social information (EASI) model. Curr Dir Psychol Sci 18(3):184–188. https://doi.org/10.1111/j.1467-8721.2009.01633.x Zahodne LB (2021) Psychosocial protective factors in cognitive aging: A targeted review. Arch Clin Neuropsychol 36(7):1266–1273. https://doi.org/10.1093/arclin/acab051 Zhang HR, Wu JW, Wang L, Ye MZ, Zheng GH (2024) Mediating effect of cognitive reserve in the relationship between physical activity and cognitive function in community-dwelling older adults. Exp Aging Res 51(3):364–376. https://doi.org/10.1080/0361073X.2024.2409587 Zhu X, Luchetti M, Aschwanden D, Sesker AA, Stephan Y, Sutin AR, Terracciano A (2024) The association between happiness and cognitive function in the UK Biobank. Curr Psychol 43(2):1816–1825. https://doi.org/10.1007/s12144-023-04446-y Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8785156","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":597126139,"identity":"c0d48730-d2d0-48d6-80ec-bbad7eb17a36","order_by":0,"name":"Rabia Khalaila","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA2UlEQVRIie3PoQrCQBzH8d84mGWwekG8V9gQ1OSznCxYnFbB4GTgig9g81X+cqBl9gXDQDCJKJZFh4JBxJvNcN94/D/8/weYTH+ZA0iiBmDlzwfGokqkWY56oAexKhAQ9aIXgYa0k906z9N9f5XE1u2CrkBNQ+rpMPBkdgxnC8U4IfAj3WEcgxaXFxXGfEQlYVL7F+6e2kVJ+rY4sIIwrUD4oAWZKelwZpdbVBVyDrhMlb90AruTelt/rj8sXF+LjRIiUSwbjyfCdRV9JW95gP3LvMlkMpk+dwdBtkZKMkwXvAAAAABJRU5ErkJggg==","orcid":"","institution":"Zefat Academic College","correspondingAuthor":true,"prefix":"","firstName":"Rabia","middleName":"","lastName":"Khalaila","suffix":""},{"id":597126140,"identity":"d78a3a22-68ea-479e-98bb-11729e56f731","order_by":1,"name":"Sharon Shiovitz-Ezra","email":"","orcid":"","institution":"Hebrew University of Jerusalem","correspondingAuthor":false,"prefix":"","firstName":"Sharon","middleName":"","lastName":"Shiovitz-Ezra","suffix":""},{"id":597126143,"identity":"5d8cd026-0c6a-44fd-b52a-989e8557e381","order_by":2,"name":"Dikla Segel-Karpas","email":"","orcid":"","institution":"University of Haifa","correspondingAuthor":false,"prefix":"","firstName":"Dikla","middleName":"","lastName":"Segel-Karpas","suffix":""}],"badges":[],"createdAt":"2026-02-04 10:40:20","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8785156/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8785156/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":103533861,"identity":"b7b89eeb-b068-454b-af70-06d90001b6cc","added_by":"auto","created_at":"2026-02-26 17:52:13","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":87036,"visible":true,"origin":"","legend":"\u003cp\u003eA moderated mediation model: The association between happiness and cognitive performance is mediated by loneliness; cognitive reserve moderates the association between happiness and cognitive performance and between loneliness and cognitive performance.\u003c/p\u003e","description":"","filename":"Fig.1.png","url":"https://assets-eu.researchsquare.com/files/rs-8785156/v1/60b7286d2e7cb3975f14d9b5.png"},{"id":104397935,"identity":"ea829519-9afa-43a2-bcc4-0b010a04d4cf","added_by":"auto","created_at":"2026-03-11 11:58:56","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":206701,"visible":true,"origin":"","legend":"\u003cp\u003eRelationship between happiness and cognitive performance at different values of the moderator (cognitive reserve), controlling covariates.\u003c/p\u003e","description":"","filename":"Fig.2.png","url":"https://assets-eu.researchsquare.com/files/rs-8785156/v1/74023839a106ab27a7f52ae1.png"},{"id":103533859,"identity":"38984190-a2b6-4b86-8281-82e7317eda70","added_by":"auto","created_at":"2026-02-26 17:52:13","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":230322,"visible":true,"origin":"","legend":"\u003cp\u003eRelationship between loneliness and cognitive performance at different values of the moderator (CR), controlling covariates.\u003c/p\u003e","description":"","filename":"Fig.3.png","url":"https://assets-eu.researchsquare.com/files/rs-8785156/v1/c4ed9043d4281bfccc1c06e9.png"},{"id":104407274,"identity":"dba72f87-027e-4542-b994-db473b91a762","added_by":"auto","created_at":"2026-03-11 12:36:24","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1368413,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8785156/v1/6f1e61bd-ef39-4173-9c67-8a03c626189c.pdf"},{"id":104397762,"identity":"4746a588-3998-4037-969d-97e999258032","added_by":"auto","created_at":"2026-03-11 11:55:50","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":15926,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTable1.docx","url":"https://assets-eu.researchsquare.com/files/rs-8785156/v1/dbae23f469fb063fec52f353.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"The longitudinal path from happiness to cognitive performance: The role of loneliness and cognitive reserve","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eThe relationship between happiness and cognitive functioning is a nuanced and extensively researched area within psychological and gerontological sciences. The literature suggests that positive affect and well-being are linked to improved cognitive health, particularly in aging populations. The exact mechanism behind this association is still not fully understood. In this study, we aimed to enhance our understanding of the relationship between happiness and cognitive function in older adults by examining how loneliness serves as a mediator and how cognitive reserve (CR) acts as a moderator.\u003c/p\u003e\n\u003ch3\u003ePositive Affect and Cognitive Functioning\u003c/h3\u003e\n\u003cp\u003eHappiness and positive affect are linked to improved cognitive performance in older adults. As people age, maintaining positive affect becomes increasingly vital for cognitive resilience, especially in late life (Hughes, Agrigoroaei, Jeon, Bruzzese, \u0026amp; Lachman, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Hittner et al. (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) demonstrated that positive affect is linked to less memory decline over nine years, suggesting a protective role of happiness in cognitive aging. Similarly, higher positive affect correlated with slower cognitive deterioration over a 12-year follow-up, emphasizing the potential long-term benefits of happiness on cognition (Berk, van Boxtel, K\u0026ouml;hler, \u0026amp; van Os, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Prospective studies highlighted a dynamic and bidirectional relationship between well-being and cognitive performance (Allerhand, Gale, \u0026amp; Deary, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Hill, van Boxtel, Ponds, Houx, \u0026amp; Jolles, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). High positive affect often correlates with better memory, processing speed, and executive functioning. Low levels are associated with increased risk for cognitive decline.\u003c/p\u003e \u003cp\u003eSeveral theoretical models explain these associations. Fredrickson\u0026rsquo;s (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2001\u003c/span\u003e) \u0026lsquo;broaden-and-build theory\u0026rsquo; posits that positive emotions expand cognitive and behavioral repertoires, thereby fostering resilience and cognitive flexibility. This was supported by neuropsychological evidence suggesting that positive affect influences neural processes underlying cognition (Ashby, Isen, \u0026amp; Turken, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e1999\u003c/span\u003e). Moreover, the neuroprotective effects of happiness may involve reduced neurodegeneration or neuroinflammation resulting in enhanced neuroplasticity (Anthony, Turnbull, Tadin, \u0026amp; Lin, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAnother theory suggested that positive affect could reduce cortisol and inflammatory markers such as C-reactive protein, both of which are associated with harmful effects on cognitive function (Folkman \u0026amp; Moskowitz, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2000\u003c/span\u003e). This implies that positive emotions contribute to a healthier neuroendocrine profile, thus supporting cognitive resilience. Folkman and Moskowitz (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2000\u003c/span\u003e) proposed that positive affect has a crucial role in coping and stress buffering: Experiencing positive emotions enhances adaptive coping strategies, in turn reducing perceived stress and minimizing negative health effects. Buckner (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2004\u003c/span\u003e) highlighted that chronic stress and negative emotions can harm hippocampal volume and memory, but positive affect acts as a buffer against these detrimental effects, thereby supporting cognitive function.\u003c/p\u003e \u003cp\u003eThe literature also explores behavioral pathways. Positive affect influences health-related behaviors such as increased physical activity, better sleep, and social engagement (Argyle, Martin, \u0026amp; Lu, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e1995\u003c/span\u003e). These behaviors are linked to enhanced neurocognitive health, as physical activity stimulates neurogenesis and promotes synaptic plasticity (Folley, Zhou, Llewellyn, \u0026amp; Hypp\u0026ouml;nen, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Similarly, social interaction, fostered by positive moods, provides cognitive stimulation and emotional support, which buffer against decline.\u003c/p\u003e \u003cp\u003eConversely, loneliness, characterized by a sense of social disconnection or lack of meaningful social interactions (de Jong Gierveld, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e1998\u003c/span\u003e), can have a detrimental impact on cognitive health. Evidence suggests that loneliness is strongly linked to cognition in older adults. Lara et al.\u0026rsquo;s (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) review indicated that loneliness and social isolation are significantly linked to the risk of cognitive deterioration, with loneliness contributing to poorer cognitive outcomes over time. Similarly, Cardona and Andr\u0026eacute;s (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) found that social isolation and loneliness are associated with higher rates of cognitive decline. Harrington et al. (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) further reinforced this link through a systematic review and meta-analysis, showing that loneliness is consistently related to decreased cognitive function in older adults without dementia. Additionally, Boss et al. (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) highlighted that loneliness negatively impacts various domains of cognition including memory, executive function, and processing speed. Although happiness and loneliness are typically studied independently in relation to cognitive outcomes, they are likely interrelated. Positive affect fosters social connection and resilience (Fredrickson, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2001\u003c/span\u003e), whereas loneliness reflects a breakdown of these processes. Thus, loneliness may represent a key pathway through which happiness influences later-life cognition.\u003c/p\u003e \u003cp\u003eTherefore, this study aimed to address this gap and enhance our understanding of the behavioral mechanisms that underlie the connection between happiness and cognitive function via loneliness. The current study also makes a significant contribution by examining the moderating role of CR, highlighting its importance in understanding the dynamics at play.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eCR and cognition\u003c/h2\u003e \u003cp\u003eCR is a key concept explaining why some individuals maintain cognitive functioning despite age-related brain changes. Opdebeeck et al. (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) defined CR as the brain's resilience to neuropathological damage, enabling efficient use of neural networks to sustain cognitive performance. This adaptive ability helps older adults compensate for structural brain changes, delaying cognitive decline and functional impairments.\u003c/p\u003e \u003cp\u003eThe relationship between CR and cognitive function is based on the idea that lifelong mental activities, education, and social engagement help develop flexible neural networks. Thus, CR is a structural resource accumulated throughout the life course. Stern (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2009\u003c/span\u003e) indicated that higher CR enhances neural processing and cognitive flexibility, which buffer neurodegenerative effects. Studies have shown that CR proxies\u0026mdash; education and occupational complexity\u0026mdash;are linked to better cognitive outcomes in aging populations (Opdebeeck et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Further studies such as Zhang et al. (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), indicated that CR mediates the relationship between physical activity and cognitive function, while Gonzales et al. (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2025\u003c/span\u003e) highlighted the benefits of social engagement in reducing cognitive decline. Schrempft et al. (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) stressed that socioeconomic factors throughout life shape CR, reinforcing the need for a multidimensional approach to measuring it. The protective effects of CR are particularly evident in older populations. Martin et al. (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) found that higher CR in centenarians correlated with better cognitive functioning and independence. Berezuk et al. (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) demonstrated that higher CR benefits real-world functioning in individuals with mild cognitive impairment, emphasizing the broader relevance of CR to everyday life.\u003c/p\u003e \u003cp\u003eThe extensive body of evidence indicates that CR plays a vital role in healthy aging by providing a buffer against cognitive decline and enhancing the capacity for neural compensation. While CR is often conceptualized as a direct buffer against neuropathology, recent work has suggested it may also shape how psychosocial factors influence cognition. For instance, Opdebeeck et al. (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) found that CR moderated the association between mood and cognitive outcomes, and Khalaila (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2025\u003c/span\u003e) found that CR moderated the association between depression and cognitive performance. These indicate the need for models that examine psychosocial and structural resources in interaction rather than isolation. Building CR through education, occupation, social engagement, and lifelong learning remains a promising avenue for promoting successful aging and reducing the burden of age-related neurodegenerative diseases. In the present study, we wanted specifically to determine whether the positive effects of happiness on cognitive function are stronger among individuals with low CR, and if CR can mitigate the harmful effects of loneliness on cognitive performance in old age. To explore whether structural resources can compensate when social and psychological resources are low, we used a longitudinal dataset with two measurements and examined a moderated mediation model in which CR moderates the path between happiness and cognitive performance, and between loneliness and cognitive performance (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eBased on the reviewed literature we hypothesized:\u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eHappiness at baseline (T1) will be positively associated with cognitive performance at follow-up (T2).\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eThe relationship between happiness at baseline (T1) and cognitive performance at follow-up (T2) will be partially mediated by loneliness, so that greater happiness will be associated with lower loneliness levels, which in turn will be associated with better cognitive performance.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eThe direct effect of happiness at baseline (T1) on cognitive performance at follow-up (T2) will be moderated by CR, so that the positive effect of happiness will be stronger among individuals with lower CR.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eThe indirect effect of happiness at baseline (T1) on cognitive performance at follow-up (T2) via loneliness will be moderated by CR, so that the negative effect of loneliness on cognitive performance will be stronger among individuals with lower CR.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"DESIGN AND METHODS","content":"\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eData\u003c/h2\u003e \u003cp\u003eThe study utilized data from the Survey of Health, Aging and Retirement in Europe (SHARE) (B\u0026ouml;rsch-Supan et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). This survey provided comprehensive information across various domains for a representative sample of community-dwelling adults aged 50 and older, as well as their spouses of any age. Questionnaires were administered through Computer Assisted Personalized Interviews (CAPI). The current analysis is based on data collected in 2013 (wave 5: baseline) and in 2015 (wave 6: follow-up) (B\u0026ouml;rsch-Supan, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eA total of 55,340 participants aged 50 or older who did not have a diagnosis of Alzheimer's disease or dementia at Time 1, took part in the study. This sample represented 15 countries: Austria, Belgium, Switzerland, the Czech Republic, Germany, Denmark, Estonia, Spain, France, Israel, Italy, Luxembourg, the Netherlands, Sweden, and Slovenia. Ultimately, 32,325 participants provided complete information for cognitive assessments at the two study waves used in the current study (Time 1 and Time 2).\u003c/p\u003e \u003cp\u003eTo compare the study participants with those excluded due to missing follow-up information, Student's t-test for independent groups was employed for continuous variables, while chi-square tests were used for categorical variables. The excluded participants at Time 2 (N\u0026thinsp;=\u0026thinsp;23,015) participants were older, had more chronic diseases, greater functional disability, more depressive symptoms, lower CR, and worse cognitive performance at Time 1. Moreover, they were more likely to be male and less physically active (see Supplementary Table\u0026nbsp;1).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eMeasures\u003c/h3\u003e\n\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eDependent variable\u003c/h2\u003e \u003cp\u003eCognitive Performance - We integrated four cognitive metrics into a single measure - immediate recall, delayed recall, numeracy, and verbal fluency. These components create a validated assessment of cognitive function in later life (Khalaila, Dintica, \u0026amp; Yaffe, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The immediate and delayed recall tasks evaluate short-term verbal learning, memory, and information retention (Cheke \u0026amp; Clayton, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). In the immediate recall task, participants repeat ten words that are read aloud to them. After a ten-minute interval, they are asked to recall the words in the delayed recall task. Serial sevens test was used for the numeracy component, where participants sequentially subtract seven from 100, up to five times. Each correct subtraction earns one point (Scholey, Harper, \u0026amp; Kennedy, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). Scores on the numeracy test range from 0 to 5. Verbal fluency, which assesses executive function and language skills (Henry, Crawford, \u0026amp; Phillips, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2004\u003c/span\u003e), requires participants to name as many animals as possible within one minute; naming more than 45 animals earns 45 points. We standardized the scores from these four tests using z-scores (M\u0026thinsp;=\u0026thinsp;0, SD\u0026thinsp;=\u0026thinsp;1), and calculated the average of the standardized scores to determine overall cognitive performance (Cohn-Schwartz \u0026amp; Khalaila, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The combined scores ranged from \u0026minus;\u0026thinsp;2.8 to 2.8 at baseline (T1) and from \u0026minus;\u0026thinsp;2.9 to 2.8 at the two years follow-up point (T2).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eIndependent variable\u003c/h2\u003e \u003cp\u003eHappiness was measured using a single-item \"I look back on my life with happiness\", rated on 1 (\"never\") to 4 (\"often\") scale This variable was assessed at baseline (T1). The use of a single-item scale to measure happiness has been validated and found to be reliable in previous research (Zhu et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eMediator\u003c/h3\u003e\n\u003cp\u003eLoneliness was assessed using the short version of the R-UCLA Loneliness Scale (Hughes, Waite, Hawkley, \u0026amp; Cacioppo, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2004\u003c/span\u003e) consisting three items rated on a scale ranging from 1 (often) to 3 (hardly ever or never): feeling a lack of companionship, left out and isolated from others. Items were recoded so that the total score ranges from 3 to 9, with a higher score indicating greater loneliness (α\u0026thinsp;=\u0026thinsp;.73).\u003c/p\u003e\n\u003ch3\u003eCognitive reserve (CR)\u003c/h3\u003e\n\u003cp\u003eCR was defined as a combined indicator of education attainment, occupational complexity, and cognitive activities. These factors were selected based on prior research (Khalaila et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Opdebeeck et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Education attainment was assessed on a 7-point scale (0 to 6) based on the ISCED-97 classification: 0\u0026thinsp;=\u0026thinsp;none, 1\u0026thinsp;=\u0026thinsp;primary level, 2\u0026thinsp;=\u0026thinsp;lower secondary, 3\u0026thinsp;=\u0026thinsp;upper secondary, 4\u0026thinsp;=\u0026thinsp;post-secondary no tertiary, 5\u0026thinsp;=\u0026thinsp;first stage of tertiary, 6\u0026thinsp;=\u0026thinsp;second stage of tertiary. Occupational complexity was categorized using the ISCO-08 occupational skill levels, with scores ranging from 0 to 4: 0\u0026thinsp;=\u0026thinsp;unemployed, 1\u0026thinsp;=\u0026thinsp;simple physical or manual tasks (e.g., elementary occupations), 2\u0026thinsp;=\u0026thinsp;tasks requiring literacy, numeracy, communication, or manual dexterity (e.g., service and sales workers), 3\u0026thinsp;=\u0026thinsp;complex tasks requiring specialized knowledge (e.g., technicians and associate professionals), and 4\u0026thinsp;=\u0026thinsp;tasks requiring complex problem-solving and theoretical knowledge (e.g., professionals, physicians). Cognitive activities were measured by self-report of four activities: attending an educational course, reading books or magazines, doing word or number games (e.g., crosswords), and playing cards or games, with scores ranging from 0 to 4. The composite measures of CR were constructed by averaging the standardized scores of these three metrics. A higher score indicated greater CR.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eCovariates\u003c/h2\u003e \u003cp\u003eThe study controlled for two baseline variables: loneliness and cognitive performance at T1. Additionally, it considered six covariates: age, gender (1\u0026thinsp;=\u0026thinsp;women, 0\u0026thinsp;=\u0026thinsp;men), number of chronic diseases, depression, physical activity, and activities of daily living (ADL). Participants were asked to indicate whether they had ever been diagnosed with any of 14 chronic conditions, including heart failure, hypertension, cerebrovascular disease, diabetes, hyperlipidemia, and chronic lung disease. Depressive symptoms were assessed using the European Depression (EURO-D) scale (Prince et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e1999\u003c/span\u003e) consisting of 12 items evaluating various symptoms of depression (1\u0026thinsp;=\u0026thinsp;present; 0\u0026thinsp;=\u0026thinsp;absent), leading to a total possible score ranging from 0 to 12.\u003c/p\u003e \u003cp\u003ePhysical activity was measured using two indicators: moderate activity and vigorous activity. These indicators were combined into a single variable with two levels: \"Never participate in vigorous or moderate physical activity\" or \"Active.\" Functional disability was assessed by counting the number of areas in which participants reported difficulties in daily activities, based on a list of six areas including dressing, bathing, and eating (Katz, Downs, Cash, \u0026amp; Grotz, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e1970\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eData Analysis\u003c/h2\u003e \u003cp\u003ePearson correlation tests were used to examine the bivariate relationships among study variables. To investigate our hypotheses related to mediation and moderated mediation, we followed the analytical approaches outlined by Preacher and Hayes (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2008\u003c/span\u003e) using PROCESS models 4 and 15. In our framework, loneliness acted as a mediator between happiness and cognitive performance, and CR served as a moderator, modifying both the direct and indirect pathways. First, we evaluated the direct and indirect effect of happiness on cognitive performance using PROCESS mediation model 4. We then implemented the moderated-mediation model 15 (Hayes, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) examining the moderating role of CR in the direct and indirect effect of happiness on cognitive performance. Simple slopes analyses determined the conditional effects of the direct and indirect effects at three levels of the moderator (CR): -1 standard deviation (Low CR), Average CR, and +\u0026thinsp;1 standard deviation (High CR). In all statistical analyses we controlled for the covariates. All statistical analyses were conducted using SPSS version 28.0 and the PROCESS tool (Hayes, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2012\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e"},{"header":"RESULTS","content":"\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e presents the descriptive statistics for the study sample. The study sample included 55.8% women, ages ranged from 50 to 110 years (M\u0026thinsp;=\u0026thinsp;65.0, SD\u0026thinsp;=\u0026thinsp;9.8). On average, participants reported 1.74 chronic diseases, low depressive symptoms (M\u0026thinsp;=\u0026thinsp;2.57), and minimal dependency in daily activities (ADL M\u0026thinsp;=\u0026thinsp;0.24). Most were physically active (88%), with average happiness rated 3.35/4 and loneliness increasing slightly from baseline (3.80) to follow-up (3.88).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDescriptive statistics of the study variables (N\u0026thinsp;=\u0026thinsp;55,340)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eCovariates and control variables\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMean (S.D)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRange\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eGender \u0026ndash; T1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e24435 (44.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWomen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e30905 (55.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge \u0026ndash; T1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e65.0 (9.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e50\u0026ndash;110\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eADL\u0026ndash; T1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.24 (0.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u0026ndash;6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of chronic Diseases \u0026ndash; T1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.74 (1.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u0026ndash;14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePhysical activity \u0026ndash; T1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNever participate in vigorous or moderate physical activity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6606 (12.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eActive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e48364 (88.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDepression\u0026ndash; T1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.57 (2.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u0026ndash;12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLoneliness \u0026ndash; T1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.80 (1.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3\u0026ndash;9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCognitive performance \u0026ndash; T1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.005 (0.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-2.8\u0026ndash;2.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eModerator\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCognitive reserve \u0026ndash; T1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.000 (1.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-2.8\u0026ndash;3.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIndependent variable\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHappiness \u0026ndash; T1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.35 (0.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u0026ndash;4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMediator\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLoneliness \u0026ndash; T2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.88 (2.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3\u0026ndash;9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDependent variable\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCognitive performance - T2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.000 (0.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-2.9\u0026ndash;2.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e presents the Pearson correlations among the study variables. Cognitive outcomes are positively associated with happiness (r\u0026thinsp;=\u0026thinsp;0.11, p\u0026lt; .001) and negatively associated with loneliness (r= -0.22, p\u0026lt; .001). Moreover, CR is positively associated with cognitive performance (r\u0026thinsp;=\u0026thinsp;0.49, p\u0026lt; .001) and happiness (r\u0026thinsp;=\u0026thinsp;0.14, p\u0026lt; .001), and negatively correlated with loneliness (r= -0.14, p\u0026lt; .001).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePearson correlations between study variables and cognitive performance \u0026ndash; T2\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"12\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1. Cognitive performance \u0026ndash; T2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2. Happiness \u0026ndash; T1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.11***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3. Loneliness \u0026ndash; T2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.22***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.18**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4. \u0026ndash; T1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.49***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.14**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.14***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5. Age\u0026ndash; T1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.40***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.13**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.16***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6. Gender \u0026ndash; T1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.01**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.02*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.09**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.09**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-0.01**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7. Chronic diseases \u0026ndash; T1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.19**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.11**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.16***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.011**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.27***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e-0.05**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8. Physical activity \u0026ndash; T1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.21***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.09**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.13***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.19***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-0.24***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.04**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-0.19***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9. ADL\u0026ndash; T1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.16**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.10**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.14***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.13***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.20***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e-0.02*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.26***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e-0.38***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10. Cognitive performance \u0026ndash; T1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.66***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.14***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.17***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.47***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-0.38***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e-0.02*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-0.18***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.28***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e-0.26***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11. Depression \u0026ndash; T1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.20**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.26***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.30***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.20***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.10**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e-0.19***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.31***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e-0.23***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.28***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e-0.26***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12. Loneliness \u0026ndash; T1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.17**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.18***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.50***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.12***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.12**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e-0.08**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.17***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e-0.15***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.15**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e-0.16**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.32***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eMediation analyses\u003c/h2\u003e \u003cp\u003ePROCESS model 4 was used to examine the longitudinal relationship between happiness and cognitive performance, as well as to determine whether loneliness mediated the effect. The results showed a significant total direct effect of happiness on cognitive performance when the mediator was not included (B\u0026thinsp;=\u0026thinsp;0.012, SE\u0026thinsp;=\u0026thinsp;0.004, 95% CI\u0026thinsp;=\u0026thinsp;0.004 to 0.020, p\u0026thinsp;=\u0026thinsp;0.004). After including loneliness as a mediator, the direct effect of happiness on cognitive performance decreased but remained significant (B\u0026thinsp;=\u0026thinsp;0.009, SE\u0026thinsp;=\u0026thinsp;0.004, 95% CI\u0026thinsp;=\u0026thinsp;0.001 to 0.018, p\u0026thinsp;=\u0026thinsp;0.019). Additionally, a significant indirect effect was found through loneliness (B\u0026thinsp;=\u0026thinsp;0.002, 95% CI\u0026thinsp;=\u0026thinsp;0.001 to 0.003), indicating that loneliness partially explains the relationship between happiness and cognitive performance. This suggests that lower levels of happiness are associated with increased feelings of loneliness which, in turn, have a negative association with cognitive performance.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eModerated \u0026ndash; mediation analyses\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;4 presents the conditional indirect effects of happiness on cognitive performance through loneliness, moderated by CR, using PROCESS model 15. The first model in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e examines the effect of happiness on the mediator, loneliness. The results indicate that lower levels of happiness are associated with higher levels of loneliness (b= -0.087, SE\u0026thinsp;=\u0026thinsp;0.009, t= -9.32, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDirect and indirect effect of Happiness (T1) on cognitive performance (T2) through the mediator (Loneliness \u0026ndash; T2) conditionally in the level of Cognitive reserve (CR) - T1 (N\u0026thinsp;=\u0026thinsp;26,648)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003eEffect of happiness \u0026ndash; T1 on mediator \u0026ndash; Loneliness-T2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eSE\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003et\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eAdj R2\u003c/em\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003e(p.value)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHappiness \u0026ndash; T1 \u0026loz; Loneliness \u0026ndash; T2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.0873\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.0094\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-9.3209\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.0000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.2957\u003c/p\u003e \u003cp\u003e(.0000)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003e\u003cb\u003eEffects on dependent variable \u0026ndash; Cognitive performance-T2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eSE\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003et\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eAdj R2\u003c/em\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003e(p.value)\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHappiness (T1) \u0026loz; cognitive performance (T2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.0098\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.0042\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.3328\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.0197\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"13\" rowspan=\"14\"\u003e \u003cp\u003e0.5872\u003c/p\u003e \u003cp\u003e(.0000)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLoneliness (T2) \u0026loz; cognitive performance (T2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.0256\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.0028\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.3167\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.0000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCR (T1) \u0026loz; cognitive performance (T2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.1125\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.0145\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.7689\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.0000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHappiness*CR \u0026loz; cognitive performance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.0084\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.0033\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-2.5609\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.0104\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eloneliness*CR \u0026loz; cognitive performance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.0059\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.0018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.3169\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.0009\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCovariates and control variables \u0026ndash; T1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (T1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.0143\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-38.2109\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.0000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender (T1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.0568\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.0063\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-8.9589\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.0000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eADL (T1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.0117\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.0056\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-2.0824\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.0373\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of chronic diseases (T1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.0058\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.0023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-2.5857\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.0097\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePhysical activity (T1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.0633\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.0122\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.2001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.0000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDepression (T1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.0078\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.0017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-4.6041\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.0000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLoneliness (T1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.0012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.0029\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.4004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.6888\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCognitive performance (T1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.5837\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.0052\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e112.1153\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.0000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003cem\u003eNotes: ADL\u0026thinsp;=\u0026thinsp;Activities of daily living\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe second model in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e evaluates the impact of happiness, loneliness, CR, and their interactions (loneliness * CR and happiness * CR) on cognitive performance. This model was significant [F(13)\u0026thinsp;=\u0026thinsp;2914.52, P\u0026thinsp;=\u0026thinsp;0.000] and explained approximately 59% of the variance in cognitive performance two years later.\u003c/p\u003e \u003cp\u003eAdditionally, there is a significant interaction between happiness and CR affecting cognitive performance (b = -0.0084, SE\u0026thinsp;=\u0026thinsp;0.0033, t = -2.56, p\u0026thinsp;=\u0026thinsp;0.0104). This interaction indicates a notable moderating effect, with the strongest positive relationship between happiness and cognitive performance occurring at low levels of CR (-1 SD CR; b\u0026thinsp;=\u0026thinsp;0.019, SE\u0026thinsp;=\u0026thinsp;0.005, t\u0026thinsp;=\u0026thinsp;3.47, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The effect diminishes at moderate levels (average CR; b\u0026thinsp;=\u0026thinsp;0.008, SE\u0026thinsp;=\u0026thinsp;0.004, t\u0026thinsp;=\u0026thinsp;2.06, p\u0026thinsp;=\u0026thinsp;0.038) and becomes non-significant at high levels of CR (+\u0026thinsp;1 SD CR; b= -0.001, SE\u0026thinsp;=\u0026thinsp;0.006, t= -0.27, p\u0026thinsp;=\u0026thinsp;0.78), as illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFurthermore, there is a significant interaction between the mediator (loneliness) and CR related to cognitive performance (b\u0026thinsp;=\u0026thinsp;0.0059, SE\u0026thinsp;=\u0026thinsp;0.0018, t\u0026thinsp;=\u0026thinsp;3.316, p\u0026thinsp;=\u0026thinsp;0.0009) (see Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The strongest negative relationship between loneliness and cognitive performance are found at low levels of CR (-1 SD CR; b= -0.032, SE\u0026thinsp;=\u0026thinsp;0.003, t= -10.05, p\u0026thinsp;\u0026lt;\u0026thinsp;0.000). The effect lessens at moderate levels (average CR; b= -0.024, SE\u0026thinsp;=\u0026thinsp;0.002, t= -8.93, p\u0026thinsp;\u0026lt;\u0026thinsp;0.000) and at high levels CR (+\u0026thinsp;1 SD CR; b= -0.017, SE\u0026thinsp;=\u0026thinsp;0.003, t= -4.55, p\u0026thinsp;\u0026lt;\u0026thinsp;0.000).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThe aging of the population implies a growing number of individuals who suffer from normal age-related cognitive decline as well as pathological cognitive decline such as Alzheimer's Disease (Cox \u0026amp; Deary, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The personal, familial and social costs of memory decline urge researchers to identify risk and protective factors. In addition to biological and neurological processes that are associated with memory decline (Cox \u0026amp; Deary, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Jin \u0026amp; Cai, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), studies have repeatedly demonstrated the role that psychosocial aspects play in this regard (Zahodne, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003ePositive affectivity (Hughes et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) and social relationships (Zahodne, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) are prominent psychological factors that were found to decrease the risk of cognitive decline, and their protective effect is often ascribed to neurological (Ashby et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e1999\u003c/span\u003e), physiological (Steptoe, Wardle, \u0026amp; Marmot, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2005\u003c/span\u003e), and behavioral processes (health behaviors) (Argyle et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e1995\u003c/span\u003e). In this paper, we explored a social pathway, linking happiness to cognitive function via the experience of loneliness.\u003c/p\u003e \u003cp\u003eOur findings suggest that loneliness partially mediates the relationship between happiness and cognitive performance. Interpersonal theories that concern affective states and traits emphasize that the experience of positive or negative emotions is not only an intra-individual process, but rather an interpersonal experience (Coyne, 1976; Van Kleef, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). In his classic work, Coyne (1976) suggested that depression is expressed in social behavior and elicits negative reactions and rejection from others that, in turn, strengthen the depression. More current works have found that negative attributes such as hostility result in increased loneliness, and this relationship is partially attributed to decreased social contact, possibly because the expression of hostility deters others (Segel-Karpas \u0026amp; Ermer, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Segel-Karpas \u0026amp; Ayalon, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). On the other hand, positive affect or positive attributes can attract others by signaling safety and approachability (Van Kleef, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2009\u003c/span\u003e), in addition to allowing the individual to explore and structure positive social experiences (Fredrickson, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). In our case, to some extent, happiness protects against the experience of loneliness that, in turn, is associated with deterioration in cognitive performance.\u003c/p\u003e \u003cp\u003eAccording to the Evolutionary Theory of Loneliness (Cacioppo et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2006\u003c/span\u003e), loneliness functions as an adaptive signal to reconnect socially to increase chances of survival. However, when chronic, it biases cognitive processes toward heightened vigilance for social threat and undermines attention, memory, and executive control (Cacioppo \u0026amp; Hawkley, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). Over time, these cognitive processes and stress-related mechanisms contribute to decline in cognitive functioning (Cacioppo \u0026amp; Hawkley, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). Our study suggests that the experience of happiness in later life could be one of the factors that both directly affect cognitive function and also distance the loneliness that, in turn, also decreases cognition.\u003c/p\u003e \u003cp\u003eHowever, the significance of happiness and loneliness for cognitive performance is not uniform. These personal and social aspects have a more meaningful role when CR is low. Thus, people with high CR can not only cope with neurological changes better than those with low CR (Khalaila et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), but are also less affected by psychosocial risk and protective factors. In other words, when cognition can be preserved via other mechanisms, the psychosocial aspects have a less significant role. However, those with low CR who also experience low happiness and high loneliness levels, are at increased risk for low cognitive performance. In should be noted that whereas the effect of loneliness on cognitive performance remains significant at all levels of CR, the effect of happiness becomes insignificant when CR is high, possibly suggesting that loneliness is a greater risk factor than unhappiness.\u003c/p\u003e \u003cp\u003eOur study supports previous studies that have found variability in the association between psychosocial variables and cognitive performance. For example, the association between depression (Khalaila, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2025\u003c/span\u003e), negative mood (Opdebeeck et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) and cognitive function is weaker when CR is high. Similarly, social contact is more beneficial to cognitive performance for individuals with lower levels of openness to experience than for those with higher levels of openness to experience, suggesting that those who seek cognitive stimuli elsewhere are less dependent on social relationships for better cognitive performance (Segel-Karpas \u0026amp; Lachman, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOverall, our findings contribute to the growing body of research on sociopsychological and structural risk and protective factors for cognitive performance in older adulthood. We suggest that when considering social risk factors such as loneliness (Cacioppo \u0026amp; Hawkley, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2009\u003c/span\u003e), other factors such as CR should be taken into account.\u003c/p\u003e \u003cp\u003eDespite its strengths\u0026mdash;large representative dataset, longitudinal design, and a robust composite measure of cognitive reserve\u0026mdash;this study has several limitations. Only two waves of data were used, preventing analysis of long-term trajectories. Future work could test how CR shapes the cumulative effects of happiness and loneliness on cognition. Happiness was measured with a single item; broader measures and inclusion of other risk factors such as personality traits (Segel-Karpas \u0026amp; Lachman, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) or cognitive schemas (Segel-Karpas \u0026amp; Ayalon, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) are warranted. Finally, individuals with dementia were excluded to focus on normal aging, but examining psychosocial factors and CR in dementia may help identify ways to slow cognitive decline. Theoretically, the current study joins that body of research aiming at identifying risk and protective factors for cognitive performance in older adulthood, suggesting that CR could act as a buffer against the harmful effects of loneliness and unhappiness. Specifically, it intimates that psychosocial and structural resources should not be viewed as parallel but independent predictors of cognitive health, but rather as dynamically interacting: when structural reserves are limited, psychosocial factors such as happiness and loneliness become disproportionately important. This extends both broaden-and-build theory and CR theory by highlighting their conditional interplay, suggesting a dual-resilience framework in which emotional well-being and structural reserve act as compensatory buffers.\u003c/p\u003e \u003cp\u003ePractically, our findings highlight the importance of developing CR across the life course through education, cognitively demanding work, and lifelong learning. At the same time, they suggest that reducing loneliness should take priority over enhancing happiness since loneliness exerts a more persistent effect on cognition, even among those with high CR. Together, these results point to a dual strategy: strengthening CR over time while addressing loneliness as an urgent and fundamental risk factor in later life.\u003c/p\u003e"},{"header":"Declarations","content":" \u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eAll authors contributed to the study conception and design. R.K analyzed the data and wrote the methods and results sections, prepared the tables and figures, S.S.E wrote the introduction and literature review, and D.S.K wrote the discussion and conclusion . All authors review and approved the final manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eThis paper uses data from SHARE Wave 5 (DOI: 10.6103/SHARE.w5.710) and Wave 6 (DOI: 10.6103/SHARE.w6.710). The SHARE data collection has been primarily funded by the European Commission through FP5\u0026ndash;FP7, Horizon 2020, and Horizon Europe, as well as national funding sources. The SHARE data are available free of charge for scientific use to registered researchers via the SHARE Research Data Center (www.share-project.org). Access requires prior registration and approval.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThis paper uses data from SHARE Wave 5 (DOI: 10.6103/SHARE.w5.710) and Wave 6 (DOI: 10.6103/SHARE.w6.710). The SHARE data collection has been primarily funded by the European Commission through FP5\u0026ndash;FP7, Horizon 2020, and Horizon Europe, as well as national funding sources. The SHARE data are available free of charge for scientific use to registered researchers via the SHARE Research Data Center (www.share-project.org). 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Curr Psychol 43(2):1816\u0026ndash;1825. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s12144-023-04446-y\u003c/span\u003e\u003cspan address=\"10.1007/s12144-023-04446-y\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"european-journal-of-ageing","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ejoa","sideBox":"Learn more about [European Journal of Ageing](http://link.springer.com/journal/10433)","snPcode":"10433","submissionUrl":"https://submission.nature.com/new-submission/10433/3","title":"European Journal of Ageing","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Cognitive performance, Happiness, Loneliness, CR, Moderated mediation","lastPublishedDoi":"10.21203/rs.3.rs-8785156/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8785156/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003ePurpose\u003c/h2\u003e \u003cp\u003eHappiness has been linked to better cognitive outcomes in older adults. Loneliness may serve as a mediator in this relationship, while cognitive reserve (CR) may buffer or enhance these effects. This study examined the direct effect of happiness on cognitive performance over two years, the mediating role of loneliness in this relationship, and whether CR moderates the direct and indirect (via loneliness) effects of happiness on cognitive performance.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eData were drawn from a longitudinal survey of adults aged 50 and above (N\u0026thinsp;=\u0026thinsp;55,340). Cognitive performance was assessed at baseline (T1) and at a two-year follow-up (T2) using a composite score combining immediate recall, delayed recall, numeracy, and verbal fluency. Happiness was measured at T1 using a single-item scale, and loneliness was assessed via the short R-UCLA Loneliness Scale. CR was computed as a standardized composite of educational attainment, occupational complexity, and engagement in cognitive activities.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eHappiness at T1 significantly predicted better cognitive performance at T2 (B\u0026thinsp;=\u0026thinsp;0.0098, p = .0197), and loneliness partially mediated this effect (indirect B\u0026thinsp;=\u0026thinsp;0.002, 95% CI [0.001, 0.003]). CR moderated both the direct effect of happiness (interaction B = -0.0084, p = .0104) and the indirect effect via loneliness (interaction B\u0026thinsp;=\u0026thinsp;0.0059, p = .0009), with stronger associations at lower levels of CR.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eHappiness promotes cognitive health in later life, partly by reducing loneliness, especially among individuals with lower CR, highlighting the importance of emotional well-being and social connectedness in cognitively vulnerable populations.\u003c/p\u003e","manuscriptTitle":"The longitudinal path from happiness to cognitive performance: The role of loneliness and cognitive reserve","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-26 17:52:08","doi":"10.21203/rs.3.rs-8785156/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"106777926893842135847418281267149735329","date":"2026-04-29T08:39:20+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-23T21:23:08+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"108876471065841769891572848611975900137","date":"2026-04-23T09:44:05+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"258978824575860778376937096103456847239","date":"2026-03-09T17:33:41+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-02-23T17:26:23+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-02-20T08:24:23+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-02-11T06:58:32+00:00","index":"","fulltext":""},{"type":"submitted","content":"European Journal of Ageing","date":"2026-02-04T09:58:17+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"european-journal-of-ageing","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ejoa","sideBox":"Learn more about [European Journal of Ageing](http://link.springer.com/journal/10433)","snPcode":"10433","submissionUrl":"https://submission.nature.com/new-submission/10433/3","title":"European Journal of Ageing","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"f6e7b47b-fbed-4b68-aacb-87731cf65a15","owner":[],"postedDate":"February 26th, 2026","published":true,"recentEditorialEvents":[{"type":"reviewerAgreed","content":"106777926893842135847418281267149735329","date":"2026-04-29T08:39:20+00:00","index":46,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-02-26T17:52:09+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-26 17:52:08","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8785156","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8785156","identity":"rs-8785156","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}