Social-Emotional Health and Cognitive Functioning Among Individuals from Families Enriched for Alcohol Use Disorder

Social-Emotional Health and Cognitive Functioning Among Individuals from Families Enriched for Alcohol Use Disorder | 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 Article Social-Emotional Health and Cognitive Functioning Among Individuals from Families Enriched for Alcohol Use Disorder Gayathri Pandey, Ashwini Pandey, Chella Kamarajan, Stacey Saenz de Viteri, and 15 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8970690/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 7 You are reading this latest preprint version Abstract Background Social-Emotional Health (SEH)—the quality of social relationships and emotional well-being—is crucial for maintaining health and cognitive functioning. Given elevated cognitive impairment risk in aging and Alcohol Use Disorder (AUD) populations, we investigated associations between specific SEH factors and cognitive and physical functioning in individuals from families enriched for AUD. Methods Data from the Collaborative Study on the Genetics of Alcoholism (COGA, analytic N = 1,476, 61% lifetime AUD) were analyzed, grouping participants into younger (22–49 years) and later-life (50 + years) adults. Six SEH factors, fluid cognition (e.g., logical reasoning), and crystallized cognition (e.g., vocabulary) were measured via the NIH Toolbox Cognition and Emotion batteries. Physical functioning (SF-36), a self-reported measure of general health, was included as a non-cognitive comparison, with age and gender tested as moderators. Results SEH associations with fluid cognition and physical functioning were robust and conditional on age and gender. In later-life adults, all three positive SEH factors (Emotional Support, Instrumental Support, Friendship) were associated with higher fluid cognition, while all three negative factors (Loneliness, Negative Affect, Perceived Stress) were associated with lower fluid cognition. These associations were predominantly observed in later-life women and were independent of lifetime AUD history. While physical functioning showed widespread SEH associations across groups, SEH was not associated with fluid cognition in younger adults. Conclusion SEH shows robust, age- and gender-specific associations with fluid cognition and physical health. The SEH-fluid cognition link appears to be a late-life phenomenon particularly salient for women and independent of an individual’s lifetime AUD history. Health sciences/Diseases/Psychiatric disorders/Addiction Biological sciences/Psychology/Human behaviour Figures Figure 1 Figure 2 Introduction Social-emotional health (SEH), which represents the quality of one’s social relationships, effective navigation of social situations, and the management of one’s emotions, is essential for one’s overall mental and physical health (Ramirez-Luzuriaga et al., 2021 ; Rutter et al., 2020 ;). For example, people with strong SEH exhibit greater life-satisfaction, decreased risk for mental health problems (depression, anxiety, and substance use disorders), physical health conditions, and decreased mortality (Choi et al., 2020 ; Holt-Lunstad et al., 2010 ; Lennartsson et al., 2022 ; Steptoe et al., 2013 ). SEH has also been shown to play a crucial role in maintaining cognitive function throughout the lifespan (Cohn-Schwartz, 2020 ), with those with strong SEH performing better on cognitive tests and presenting a decreased risk for dementia (Kuiper et al., 2016 ; Piolatto et al., 2022 ). Conversely, a lack of social connections and experiences of high perceived stress or negative emotions are associated with increased risk for cognitive decline (Aggarwal et al., 2014 ; Jurgens et al., 2025 ; Mahalingam et al., 2023 ). The association between SEH and cognition is often understood by examining two distinct components of intelligence: 1) Fluid cognitive abilities—dynamic thinking skills (e.g., executive functions, episodic memory) that reflect biologically based brain processes, which decline across the lifespan and are sensitive to acquired brain injury or disease (Horn, 1968 ; Lovden et al., 2020; Murman, 2015 ). 2) Crystallized cognitive abilities—accumulated knowledge, tend to stabilize or slightly improve with experience, and are less susceptible to injury (Tucker-Drob et al., 2022 ). Because of the distinct theoretical separation between these cognitive domains, there is a lack of empirical work examining the association of SEH separately with fluid and crystallized cognition, particularly when accounting for age and clinical risk factors. Chronic Alcohol Use Disorder (AUD) and related disorders can affect both SEH and cognitive abilities. There is evidence that AUD and SEH deficits are intertwined, reflecting a recognized bidirectional relationship: poor emotion regulation often precedes substance use (Khantzian, 1990 ; Koob, 2015 ), and chronic alcohol consumption can impair social function and emotional competence (Maurage et al., 2011 ; The Ridge Ohio, 2023 ). Further, AUD is also associated with accelerated damage to brain structure and cognitive decline, particularly in fluid abilities (Wang et al., 2023 ; Yen et al., 2022 ). Our own work corroborates this, using a sample of individuals enriched for AUD from the COGA study (Collaborative study on the Genetics of Alcoholism), we showed that a lifetime history of AUD is linked to decreases in fluid cognition (Pandey et al., 2024 ). Given that maintaining good SEH strengthens neural circuits that buffer against cognitive decline (Zhaoyang et al., 2021 ; Wilson et al., 2003 ), understanding the SEH–cognition link in later life is critical, particularly within a population enriched for AUD. While prior studies have demonstrated that social-emotional factors should be considered when examining brain functioning and AUD across the lifespan, the extent to which stressors and social supports have lasting, differential effects on cognitive functioning in younger and later-life adults remains largely unknown. Leveraging data collected from the Collaborative Study on the Genetics of Alcoholism (COGA), this work examines how six specific measures of SEH (three positive factors: emotional support, instrumental support, friendship, and three negative factors: loneliness, negative affect, and perceived stress) are associated with fluid cognition and crystallized cognition. We also examine influences of SEH on physical functioning for comparison, given its established link to physical morbidity and mortality. To identify whether the observed associations are specific to a specific life-stage, we also perform analyses stratified by younger and later-life adults. This comparison is vital for establishing whether social and emotional well-being consistently shape cognitive outcomes throughout life, or if their effect is magnified by the unique convergence of cumulative neurophysiological vulnerability and significant psychosocial shifts (e.g., changes in vocational roles, caregiving status, and peer or partner loss) in later-life. Finally, given research that social networks/support systems differ significantly by gender (Antonucci & Akiyama, 1987 ; Zhaoyang et al., 2024 , (Rogowska et al., 2020 ; Zhaoyang et al., 2024 )), we also examined associations separately in women and men. Methods Sample. Data ( N = 1,476; 51% female; 61% with a lifetime history of AUD) are drawn from the Collaborative Study on the Genetics of Alcoholism (COGA). COGA is a longitudinal, family-based cohort that has characterized individuals from large pedigrees densely affected by AUD, alongside community comparison families, across clinical, behavioral, and neurobiological domains (Agrawal et al., 2023 ; Dick et a., 2023; Meyers et al., 2023 ). Since its inception in 1989, COGA has assessed 17,878 individuals across 2,246 families. Data collection has focused on distinct participant subsets across four principal waves: (a) Wave 1 (1991–1999) initial ascertainment; (b) Wave 2 (1996–2005) follow-up and new family assessment; (c) the Prospective Wave (2004–2019) focused on youth; and (d) the current Lifespan wave (2019-ongoing). The analytic sample for this study is derived exclusively from the Lifespan wave, in which previously assessed younger adult participants from the Prospective wave and later life adults (ages 50+) are re-assessed using updated protocols, including the NIH Toolbox (NIHTB) Emotion and Cognition batteries. The current study included all 1,476 individuals who completed both NIHTB batteries, comprising 558 younger adults (ages 22–49; 56% with a lifetime AUD dx) and 918 later-life adults (ages 50+; 64% with a lifetime AUD dx). Table 1 presents descriptive statistics for the key variables across these age groups. Table 1 Descriptive statistics for the key variables in the overall sample and across younger and later-life adults with group differences. Variables All Subjects ( N = 1476) Younger Adults ( N = 558) Later-life Adults ( N = 918) t -Test N % M(SD) N % M(SD) N % M(SD) df t p # Age 1476 100.0% 52.30 (14.73) 558 100.0% 35.91 (5.86) 918 100.0% 62.26 (8.08) — — — Women 1476 60.0% a — 558 59.0% — 918 60.0% — — — — Non-Hispanic Whites 1476 73.0% b — 558 67.0% — 918 76.4% — — — — DSM-5 AUD dx 1475 61.0% c — 557 55.7% — 918 64.4% — 1140.01 -3.24 < .001 Emotional Support 1462 99.1% 47.31 (10.30) 554 99.3% 47.34 (11.21) 908 98.9% 47.28 (9.71) 1042.62 .104 .459 Instrumental Support 1462 99.1 % 48.12 (10.53) 554 99.3% 46.71 (10.91) 908 98.9% 48.98 (10.20) 1460.00 -4.02 < .001 Friendship 1462 99.1% 47.08 (10.51) 554 99.3% 46.65 (10.76) 908 98.9% 47.34 (10.36) 1460.00 -1.22 .111 Loneliness 1462 99.1% 54.07 (10.62) 554 99.3% 55.60 (10.95) 908 98.9% 53.14 (10.31) 1460.00 4.32 < .001 Negative Affect 1460 98.9% 51.41 (10.62) 554 99.3% 53.50 (11.36) 906 98.7% 50.13 (9.93) 1049.85 5.76 < .001 Perceived Stress 1461 99.0% 51.30 (9.50) 554 99.3% 53.60 (9.94) 907 98.8% 49.89 (8.94) 1074.90 7.16 < .001 Fluid Cognition 1422 96.3% 50.09 (11.82) 542 97.1% 50.88 (12.93) 880 95.9% 49.60 (11.06) 1011.94 1.92 .027 Crystallized Cognition 1430 96.8% 52.18 (9.91) 546 97.8% 52.60 (10.58) 884 96.3% 51.92 (9.48) 1058.46 1.22 .220 Physical Functioning 1282 86.9% 78.70 (25.89) 468 83.9% 87.03 (21.52) 814 88.7% 73.91 (26.97) 1151.66 9.55 < .001 a Gender was coded 1 = men, 2 = women; proportion of women in the sample is presented. All participants gender identity matched their sex assigned at birth. b Race/ethnicity was coded 1 = Whites, 2 = Blacks, 3 = Other; proportion of Whites in the sample is presented c DSM-5 AUD dx 1 = No AUD, 5 = AUD; proportion of individuals with AUD lifetime diagnosis is presented. # Two-sided p. Measures Fluid Cognition. The fluid cognition data were obtained from the NIHTB Cognition battery (iPad version 2). The NIHTB Cognition Battery assesses neurocognitive domains grouped into fluid and crystallized cognitive abilities (Weintraub et al., 2013). The fluid cognition composite (α = .83) is an average of five tests assessing various domains: the dimensional change card sort test (cognitive flexibility), the flanker inhibitory control and attention test (inhibitory control), the list sorting working memory test, the picture sequence memory test (episodic memory), and the pattern comparison processing speed test. These tests cover domains related to logical reasoning and novel problem-solving (Cattell, 1967 ; Dikmen et al., 2014 ; Gershon et al., 2013 ; Heaton et al., 2014; Karr et al., 2023 ; Tulsky et al., 2014; Zelazo et al., 2013 ). Crystallized Cognition. The crystallized cognition composite (α = .84) is an average of the picture vocabulary test (identifying pictures corresponding to spoken words) and the oral reading recognition test (pronouncing printed words) (Akshoomoff et al., 2013 ; Carlozzi et al., 2014 ; Gershon et al., 2014 , 2020 ). Prior work from our research group has indicated diminished performance in both fluid (e.g., response inhibition) and crystallized (e.g., episodic memory) domains in individuals with AUD (Pandey, et al., 2024 ). For both fluid and crystallized cognition, we used the demographic-adjusted T-scores (M = 50, SD = 10) for both composites, which control for the effects of age, self-reported gender, education, and race/ethnicity (Casaletto et al., 2015 ). Social-Emotional Health (SEH) Factors. The SEH factors were assessed using the iPad version 2 of the NIHTB Emotion Battery. This battery assesses emotions via 17 individual scales grouped into four theoretically derived subdomains: psychological well-being, social relationships, negative affect, stress and self-efficacy (Salsman et al., 2013). The individual scales demonstrate high internal consistency (α typically ≥ 0.85; Salsman et al., 2013). We selected three positive scales (i.e., emotional support, instrumental support, friendship) and three negative scales (loneliness, negative affect, and perceived stress) to capture a comprehensive and balanced assessment of both protective and risk facets of social-emotional well-being. We utilized these six specific SEH factors in this study, rather than the broader subdomains, to achieve greater precision in examining the differential associations of discrete social components (support, loneliness) and emotional components (affect, stress) with our outcomes. The instrument employs Computer Adaptive Testing (CAT) and utilizes Item Response Theory scoring, yielding demographic-adjusted T-scores (M = 50, SD = 10) (Yang & Kao, 2014 ). This CAT approach generates individualized item sets for highly accurate and efficient assessment of each latent construct. Physical functioning. Physical functioning was assessed using the Physical Functioning (PF) subscale from the 36-Item Short Form Health Survey (SF-36), a widely used, self-reported measure of general health status (Ware, 2000 ; Ware & Sherbourne, 1992 ). The inclusion of physical functioning provides a non-cognitive outcome measure known to be associated with both SEH and age, allowing for a comparative examination of the observed associations. The PF subscale consists of ten items that specifically assess the degree of limitation in common physical and mobility activities (e.g., walking specified distances, climbing stairs, carrying groceries) (Syddall et al., 2009 ). For analysis, the PF subscale is scored such that higher scores reflect superior physical functioning and fewer self-reported limitations. Individual items are scored from 1 = limited a lot to 3 = not limited at all). DSM-5 AUD Lifetime Diagnosis . Information from participants’ Semi-Structured Assessment for the Genetics of Alcoholism (SSAGA; Bucholz et al., 1994 ) interview was used to classify AUD status. Specifically, interviewed subjects were coded as affected (1) or unaffected (0) based on whether they met lifetime criteria for DSM-5 AUD. That is, subjects who endorsed 2 or more criteria that clustered within a single 12-month period were diagnosed with AUD. Statistical Analyses The data were analyzed using IBM SPSS AMOS, Version 29.0. First, bivariate correlation analysis (Pearson's coefficient) was computed to examine associations among the three outcome variables (Fluid Cognition, Crystallized Cognition, Physical Functioning) and the six social-emotional health (SEH) variables. Next, the primary analysis utilized Hierarchical Multiple Regression (HMR) to examine the unique and interactive effects of each of the six SEH factors on the three outcomes. Each model included one continuous SEH factor as the primary predictor, moderated by Gender, Age Group, and AUD Dx. Each model included only one SEH factor as the independent variable because we wanted: 1. To more accurately capture each factor’s unique contribution to cognition and physical functioning, 2. To avoid multicollinearity among SEH constructs, and 3. To facilitate interpretation of higher-order interaction effects. We specifically included interaction terms involving AUD Dx to assess its role as a moderator. The continuous SEH factor was grand-mean centered, and all categorical moderators were entered using effect coding. The HMR primary analysis was performed to determine the significance of the two-way and three-way interaction terms. Given that the HMR revealed significant interactions only for Age Group and Gender (and not for AUD Dx; See Tables S1 and S2), simple slopes analyses were performed as planned comparisons exclusively to probe the moderating effects of these two variables. The main effect of AUD Dx was not statistically significant across any of the HMR models for fluid and crystallized cognition outcomes (all p s ≥ 0.321). Similarly, the interactions involving AUD Dx were consistently non-significant for all six SEH factors (all p s ≥ 0.212), including the 2-way and 3-way AUD interactions, and therefore, no further testing was conducted to probe AUD moderation. However, all estimates of simple slopes reported here reflect models that were fully adjusted for lifetime AUD diagnosis. The Benjamini-Hochberg (BH) False Discovery Rate (FDR) procedure was applied separately for each outcome variable (Fluid Cognition, Crystallized Cognition, and Physical Functioning) to control the rate of Type I errors (FDR controlled at Q = 0.05). For each outcome, the simple slopes tests were grouped into two distinct families of tests: 1. Age Group: The 12 p -values resulting from testing the effect of all six SEH factors within the later-life adult group and the younger adult group (6 SEH factors x 2 groups = 12 tests) were pooled. 2. Gender Group: The 12 p -values resulting from testing the effect of all six SEH factors within the men and women groups (6 SEH factors x 2 groups = 12 tests) were pooled. Only simple slopes tests meeting the adjusted BH threshold for their respective family were declared statistically significant. Descriptive statistics for key variables in the study for the overall sample and separately for younger and later-life adults are reported in Table 1 (See Table S3 for bivariate correlations among key variables). Results Overall, as shown in Table 2 , conditional effects of SEH on fluid cognition were highly specific to age (see Fig. 1 ). Among younger adults, no significant associations emerged between any of the six SEH factors and fluid cognition. This contrasted sharply with the findings in later-life adults, where all three positive SEH factors (i.e., emotional support, instrumental support, and friendship) were significantly associated with higher fluid cognition (all p s ≤ 0.003, BH corrected), and conversely, all three negative SEH factors (i.e., loneliness, negative affect, and perceived stress) were significantly associated with lower fluid cognition (all p s ≤ 0.009, BH corrected). Associations with crystallized cognition were notably weaker: only two negative SEH factors (i.e., negative affect and perceived stress) were significantly associated with lower crystallized cognition in later life (all p s ≤ 0.001, BH corrected), while, interestingly, loneliness was positively associated with higher crystallized cognition in younger men ( p = 0.004, BH corrected). Table 2 Associations of social-emotional factors with Fluid cognition, Crystallized cognition, and physical functioning in younger and later-life adults (adjusted for DSM-5 AUD lifetime dx) Younger Adults Fluid Cognition Crystallized Cognition Physical Functioning B SE p B SE p B SE p Emotional Support .06 .04 .185 .04 .04 .412 .18 .04 < .001 a Instrumental Support .04 .04 .326 − .02 .04 .670 .06 .04 .157 Friendship .05 .04 .226 .00 .04 .994 .19 .04 < .001 a Loneliness .01 .04 .820 .14 .04 .001 a − .17 .04 < .001 a Negative Affect − .03 .04 .473 .06 .04 .175 − .24 .04 < .001 a Perceived Stress − .05 .04 .250 .01 .04 .912 − .25 .04 < .001 a Later-life Adults Fluid Cognition Crystallized Cognition Physical Functioning B SE p B SE p B SE p Emotional Support .15 .03 < .001 a .03 .03 .425 .14 .03 < .001 a Instrumental Support .14 .03 < .001 a .00 .03 .975 .04 .03 .200 Friendship .10 .03 < .003 a − .01 .03 .806 .20 .03 < .001 a Loneliness − .10 .03 .009 a .02 .03 .625 − .19 .03 < .001 a Negative Affect − .13 .03 < .001 a − .14 .03 < .001 a − .22 .03 < .001 a Perceived Stress − .13 .03 < .001 a − .16 .03 < .001 a − .18 .03 < .001 a Statistically significant associations are bolded. a Associations that withstood Benjamini Hochberg multiple test correction with a False Discovery Rate of 0.05. Further, as shown in Table 3 , stratification by gender revealed that these robust later-life associations were predominantly driven by women (see Fig. 2 ). In later-life women, emotional support and instrumental support were significantly associated with higher fluid cognition, and although friendship was also associated with higher fluid cognition ( p = 0.030), it did not withstand the BH correction. On the other hand, all three negative SEH factors were significantly associated with lower fluid cognition (all p s ≤ 0.014, BH corrected). In contrast, later-life men showed a more limited pattern, with only instrumental support positively associated with fluid cognition, and only negative affect and perceived stress negatively associated. For physical functioning, associations were robust across all groups: emotional support and friendship were consistently associated with significantly better functioning, while loneliness, negative affect, and perceived stress were consistently associated with significantly poorer functioning in all groups (all p s < 0.001, BH corrected), except for later-life men, where only negative affect was significant. These findings suggest that the protective benefits of positive social connections and social support are most prominently limited to fluid cognition (vs. crystallized cognition), particularly among later-life adults, and that the detrimental effects of negative SEH factors were robustly associated with impairment across all three outcomes. Notably, later-life women presented both the strongest positive SEH effects on fluid cognition and the most widespread detrimental effects of negative SEH on fluid cognition, crystallized cognition, and physical functioning. Table 3 Associations of social-emotional factors with Fluid cognition, Crystallized cognition, and physical functioning in men and women across younger and later-life age groups (adjusted for DSM-5 AUD lifetime dx) Younger Adults Men Women Fluid Cognition (n = 222) Crystallized Cognition (n = 223) Physical Functioning (n = 183) Fluid Cognition (n = 316) Crystallized Cognition (n = 318) Physical Functioning (n = 283) B SE p B SE p B SE P B SE P B SE p B SE P Emotional Support .01 .06 .861 − .04 .07 .555 .20 .08 .006 a .10 .06 .074 .13 .05 .029 .17 .06 .003 a Instrumental Support .06 .06 .402 .01 .07 .946 .05 .08 .570 .04 .06 .475 − .02 .05 .680 .08 .06 .174 Friendship .00 .06 .996 .01 .07 .211 .25 .08 < .001 a .09 .06 .103 − .01 .05 .885 .15 .06 .012 a Loneliness .10 .06 .110 .18 .06 .004 a − .20 .08 .120 − .07 .06 .209 .10 .05 .084 − .21 .06 < .001 a Negative Affect .03 .07 .657 .12 .07 .073 − .18 .08 .014 a − .07 .06 .217 .04 .05 .526 − .28 .06 < .001 a Perceived Stress − .02 .07 .819 .03 .07 .693 − .22 .08 .010 a − .07 .05 .203 .01 .05 .873 − .29 .05 < .001 a Men Women Later-life Adults Fluid Cognition (n = 344) Crystallized Cognition (n = 345) Physical Functioning (n = 309) Fluid Cognition (n = 530) Crystallized Cognition (n = 533) Physical Functioning (n = 498) B SE p B SE P B SE P B SE p B SE p B SE P Emotional Support .07 .05 .168 .07 .05 .229 .01 .05 .839 .18 .05 < .001 a − .00 .04 .965 .24 .05 < .001 a Instrumental Support .17 .05 < .001 a .06 .05 .283 .05 .05 .410 .13 .05 .003 a − .04 .04 .399 .04 .05 .416 Friendship .09 .05 .080 .00 .05 .971 .09 .05 .117 .10 .05 .030 − .02 .04 .672 .28 .05 < .001 a Loneliness − .06 .05 .217 .01 .05 .846 − .09 .05 .096 − .11 .05 .014 a .02 .04 .670 − .24 .05 < .001 a Negative Affect − .16 .05 .003 a − .15 .05 .003 a − .13 .05 .024 a − .12 .05 .009 a − .13 .04 .006 a − .29 .05 < .001 a Perceived Stress − .18 .05 < .001 a − .19 .05 < .001 a − .06 .05 .244 − .11 .05 .014 a − .15 .04 .001 a − .24 .05 < .001 a Statistically significant associations are bolded. a Associations that withstood Benjamini Hochberg multiple test correction with a False Discovery Rate of 0.05. Discussion This study provides novel insights into how specific facets of SEH are differentially associated with fluid cognition, crystallized cognition, and physical functioning across the adult lifespan, and differences as a function of age and gender. The findings revealed a pronounced pattern of associations where the influence of SEH was primarily restricted to later-life adults and was most robust in later-life women. Specifically, positive SEH factors (emotional support, instrumental support, and friendship) were consistently and significantly correlated with higher fluid cognition and better physical functioning among later-life adults. Conversely, negative SEH factors (perceived stress, negative affect, and loneliness) were robustly correlated with lower fluid cognition and poor physical functioning in this age group. Interestingly, the most comprehensive pattern of associations emerged among later-life women. They demonstrated the greatest number of significant correlations—both positive and negative—across all three outcomes (fluid cognition, crystallized cognition, and physical functioning). Our data show that strong social connections and positive psychosocial factors are associated with higher fluid cognition and better physical capabilities, while negative psychosocial aspects correlate with detrimental outcomes. These results corroborate previous research linking social engagement, support, and positive emotionality to a healthy brain and body (Cyranowski et al., 2013 ; Holt-Lunstad et al., 2010 ; Kelly et al., 2017 ; Kuiper et al., 2016 ). Furthermore, the negative associations align with studies highlighting the deleterious effects of negative psychosocial factors on mental and physical well-being (Steptoe & Kivimäki, 2012 ; Sundstrom et al., 2020; Wilson et al., 2007; Yu et al., 2021 ). Social-Emotional Health and Fluid Cognition Fluid Cognition, a core cognitive ability involving logical reasoning and problem-solving in novel situations (Cattell, 1967 ), is closely linked to executive functions essential for optimal social adaptation (Opitz et al., 2014 ; Stawski et al., 2011 ) and is vital for overall healthy aging. The role of SEH in overall health is well-documented: positive SEH factors are linked to lower incidence of major physical health issues and resilience against neuropsychiatric disorders (Coyte et al., 2021 ; Deane et al., 2020 ; Delfin etal., 2024 ; Kiecolt-Glaser et al., 2002 ; Lenferink et al., 2018 ; Pandey et al., 2023; Smith, 2022 ; Umberson & Montez, 2010 ). Aligned with literature showing that positive SEH is associated with enhanced cognitive functioning (Costa-Cordella et al., 2021 ; Haslam et al., 2005 ; Mogic et al., 2023 ), our study found that positive SEH factors (emotional support, instrumental support, and friendship) were significantly associated with higher fluid cognition. This protective association can be viewed through the Social Support Theory's stress-buffering hypothesis, which suggests that supportive relationships mitigate stressful events by lowering adverse physiological stress reactions and reducing physiological arousal (Bowen et al., 2014 ; Cohen & Wills, 1985 ; Cohen, 1983 ; Costa-Cordella et al., 2021 ; Seeman & Crimmins, 2001 ). Beyond stress reduction, supportive social engagement is also associated with increased cognitive reserve and direct neurochemical benefits (Uchino et al., 2018 ; Ybarra et al., 2008 ). Therefore, our finding suggests these positive social interactions may reduce stress and promote healthy coping, thereby protecting critical neural areas and enhancing resilience against cognitive impairment (Kelly et al., 2017 ). Conversely, negative SEH factors (loneliness, negative affect, and perceived stress) were significantly associated with lower fluid cognition. This pattern has strong neurobiological relevance and aligns with previous work linking loneliness and negative emotionality to increased physiological arousal (Hypothalamic-Pituitary-Adrenal axis and Sympathetic Nervous System activation), which is associated with poorer cognitive functioning and greater cognitive decline (Girotti et al., 2024 ; Luchetti et al., 2024 ; Sundstrom et al., 2020). Social disconnection and loneliness are also associated with structural brain differences, including reduced gray matter volume in frontal and temporal regions (Shamay-Tsoory & Kanterman, 2024 ). Likewise, chronic stress, linked to negative SEH factors, is also associated with structural changes in brain regions—such as the hippocampus and prefrontal cortex—which underpin cognitive functions like memory and executive control (Arnsten et al., 2015 ; Blum, 2024 ). Social-emotional health, fluid cognition, and age differences Our results demonstrated that associations between SEH and fluid cognition, compared to crystallized cognition, were robust and exclusive to later-life adults, persisting even after controlling for lifetime AUD status. Specifically, all three positive SEH factors were associated with higher fluid cognition, and all three negative SEH factors were associated with lower fluid cognition in later-life adults. The absence of significant associations of SEH and fluid cognition among younger adults may be attributed to their relatively high cognitive reserve (CR) (Stern, 2012 ; Wook Yoo et al., 2015 ). CR, the brain's capacity to function efficiently despite age-related changes or damage (Tucker-Drob, 2009 ), is actively accumulated through diverse life factors, including education, challenging work, and social activity (Fleck et al., 2019 ). Consequently, younger adults tend to possess a higher baseline CR, which may effectively shield their cognitive performance, potentially masking the influence of their social-emotional well-being on fluid cognition. In contrast, the strong association between SEH and fluid cognition in later life may be due to a natural age-related decline in brain function and a fundamental shift in social priorities. According to the Socioemotional Selectivity Theory (SST) (Carstensen, 1992 , 2006 ), due to a perceived limited future, later-life adults may gradually shift from expanding their social network to concentrating on deeply meaningful and emotionally rewarding, often smaller yet highly valued relationships (Carstensen et al., 1999 ). The quality of this restricted network is observed to have a stronger relationship with fluid cognition and overall well-being (Carstensen, 1992 ; Carstensen et al., 1999 ; Reed & Carstensen, 2012 ). This heightened importance of high-quality social support likely accounts for the robust positive association found between positive SEH factors and fluid cognition in this age group. Conversely, as the CR weakens with age, the brain's ability to cope with stress diminishes and negative emotionality (e.g., perceived stress) may dominate. This likely may make cognitive functioning, particularly fluid abilities, more sensitive to the influence of negative SEH factors. Furthermore, negative SEH factors (i.e., loneliness, negative affect, and perceived stress) gain increased salience in later life due to age-related stressors, including declining health, loss of loved ones, and social network attrition (Musich et al., 2015 ; Perissinotto et al., 2012 ) making the connection between negative SEH factors and cognition more prominent. This combination of a more vulnerable brain and an accumulation of negative psychosocial experiences may explain why the association between social-emotional well-being and fluid cognition is so clearly visible primarily in later life. Social-emotional health and gender differences The observed gender differences are a critical finding, highlighting a potentially distinct pathway through which SEH may affect overall well-being. The consistent and significant associations found between SEH factors and both physical functioning and fluid cognition in women across both age groups suggest that social-emotional well-being may be a uniquely salient factor for female health outcomes. This pattern is well-supported by the Tend-and-Befriend Theory (Taylor et al., 2000 ; McLean & Anderson, 2009 ), which posits that, under stress, women are more likely to engage in behaviors that promote affiliation and social support ("befriending"), while men tend to exhibit a classic fight-or-flight response. From a neurobiological perspective, women's stress response, mediated by oxytocin, promotes affiliation (befriending) and actively downregulates the stressful hypothalamic-pituitary-adrenocortical axis. This biologically-driven preference for affiliation suggests that social networks may serve as stress-buffering factors for women, directly influencing their physiological health (e.g., lower blood pressure, reduced cortisol) and cognitive resilience. Furthermore, this greater reliance on social networks could make the association of both positive and negative SEH factors (e.g., social support, negative affect) with cognitive function and overall health more pronounced. Supporting this premise, research by McLean and Anderson ( 2009 ) have shown that women are more likely to use coping strategies centered on emotional disclosure, which can mitigate the negative effects of chronic stress on fluid cognitive performance (Lupien et al., 2009 ). The greater consistency of these associations in women may therefore reflect the deeper, biologically-integrated connection between their social and emotional lives and their physiological and cognitive systems. In contrast, while men also showed some significant associations, their fewer and less consistent links suggest that perhaps different aspects may play a role in the relationship between their social-emotional state and their cognitive and physical health. This may be related to gendered socialization patterns, which often discourage men from outwardly expressing vulnerability or seeking emotional social support in the same way as women (Möller-Leimkühler, 2002 ). Consequently, the impact of their SEH on their health outcomes may be mediated by different, less direct pathways, such as internalizing stress or relying on non-social coping strategies, potentially dampening any significant association of SEH measures on their cognitive and physical health. Future research should aim to decipher these nuanced, gender-specific differences across the lifespan. Strengths and limitations The current study has several strengths. To our knowledge, this is the first study to examine the associations of SEH factors with fluid cognition, crystallized cognition and physical functioning with a focus on both age and gender differences. Notably, this work used standardized scores from the NIH-TB Cognition and Emotion batteries, making these findings more generalizable. Furthermore, this study stands out by uniquely exploring the relationship of fluid cognition (focus outcome) with a comprehensive range of social-emotional health factors, including both positive and negative aspects. Further, as comparative outcomes, crystallized cognition and physical functioning were also examined. Nevertheless, several limitations of this study should also be considered. Specifically, the cross-sectional design limits the ability to establish causal relationships between the SEH factors and the outcomes. Given the possibility that SEH and cognitive functioning may be bidirectional (Llewellyn et al., 2008 ), longitudinal studies are needed to further elucidate the directionality and temporal dynamics of these associations. Additionally, the reliance on self-reported measures of SEH and physical functioning may introduce reporting bias. Future research could benefit from incorporating objective measures of physical and alternate cognitive function assessments. In addition, the age-groups examined in this study are broad and may represent more than one developmental epoch. As the sample grows there will be more statistical power to examine more narrowly defined/meaningful age groups. Conclusion In conclusion, this study provides valuable insights into the complex interplay between social emotional health, fluid cognition, and physical functioning in younger and later-life adults, highlighting important gender differences. 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Alcohol use and cognitive decline: Longitudinal results from a family-based study. Journal of Studies on Alcohol and Drugs , 83 (4), 540–548. https://www.google.com/search?q=https://doi. org/10.15288/jsad.2022.83.540 Yu, L., Agrawal, A., & Wilson, R. S. (2021). Negative psychosocial factors and physical health: A review of recent evidence. Health Psychology Review , 15 (2), 180–195. https://www.google.com/search?q=https:// doi.org/10.1080/17437199.2020.1718525 Zelazo, P. D., Anderson, J. E., Richler, J., Wallner-Allen, K., Beaumont, J. L., & Weintraub, S. (2013). NIH Toolbox Cognitive Battery (CB): Measuring executive function and attention. Monographs of the Society for Research in Child Development , 78 (4), 16–33. https://doi.org/10.1111/mono.12032 Zhaoyang, R., Sliwinski, M. J., Martire, L. M., & Smyth, J. M. (2021). Social-emotional health and brain buffering against cognitive decline. Journals of Gerontology Series B: Psychological Sciences and Social Sciences , 76 (4), 680–692. https://doi.org/10.1093/geronb/gbaa089 Zhaoyang, R., Smyth, J. M., & Sliwinski, M. J. (2024). Gender differences in social support and physiological health: A longitudinal study. Health Psychology , 43 (2), 112–124. https://www.google.com/search?q=https:// doi.org/10.1037/hea0001334 Additional Declarations The authors have declared there is NO conflict of interest to disclose Supplementary Files SuppMatTP2.24.26.docx Article File Cite Share Download PDF Status: Under Review Version 1 posted Review # 1 received at journal 23 Mar, 2026 Reviewer # 1 agreed at journal 11 Mar, 2026 Reviewers invited by journal 02 Mar, 2026 Editor assigned by journal 02 Mar, 2026 Submission checks completed at journal 02 Mar, 2026 First submitted to journal 01 Mar, 2026 Unknown event 26 Feb, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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18:56:21","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8970690/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8970690/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":104182161,"identity":"7d19a79e-671c-4543-bb14-db020e17d889","added_by":"auto","created_at":"2026-03-08 17:34:17","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1006783,"visible":true,"origin":"","legend":"\u003cp\u003eBeta coefficients from regression models associating positive and negative SEH factors with fluid cognition, crystallized cognition, and physical functioning across younger and later-life participants.\u003c/p\u003e","description":"","filename":"Fig1TP2.24.26.png","url":"https://assets-eu.researchsquare.com/files/rs-8970690/v1/8bab4fd9e91a46d959f4ebf0.png"},{"id":104182162,"identity":"fe3d486d-c636-4eaf-a9b2-d7b25c2420d9","added_by":"auto","created_at":"2026-03-08 17:34:17","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1220903,"visible":true,"origin":"","legend":"\u003cp\u003eBeta coefficients from regression models associating positive and negative SEH factors with fluid cognition, crystallized cognition, and physical functioning in men and women across younger and later-life age groups.\u003c/p\u003e","description":"","filename":"Fig2TP2.24.26.png","url":"https://assets-eu.researchsquare.com/files/rs-8970690/v1/5178ca98b6d5ee3a1b7d378b.png"},{"id":104182163,"identity":"7c694e63-3746-433e-9a3b-8771e2701c6b","added_by":"auto","created_at":"2026-03-08 17:34:17","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":33179,"visible":true,"origin":"","legend":"Article File","description":"","filename":"SuppMatTP2.24.26.docx","url":"https://assets-eu.researchsquare.com/files/rs-8970690/v1/89b292c47fae252523626455.docx"}],"financialInterests":"The authors have declared there is \u003cb\u003eNO\u003c/b\u003e conflict of interest to disclose","formattedTitle":"Social-Emotional Health and Cognitive Functioning Among Individuals from Families Enriched for Alcohol Use Disorder","fulltext":[{"header":"Introduction","content":"\u003cp\u003eSocial-emotional health (SEH), which represents the quality of one\u0026rsquo;s social relationships, effective navigation of social situations, and the management of one\u0026rsquo;s emotions, is essential for one\u0026rsquo;s overall mental and physical health (Ramirez-Luzuriaga et al., \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Rutter et al., \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2020\u003c/span\u003e;). For example, people with strong SEH exhibit greater life-satisfaction, decreased risk for mental health problems (depression, anxiety, and substance use disorders), physical health conditions, and decreased mortality (Choi et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Holt-Lunstad et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Lennartsson et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Steptoe et al., \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). SEH has also been shown to play a crucial role in maintaining cognitive function throughout the lifespan (Cohn-Schwartz, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), with those with strong SEH performing better on cognitive tests and presenting a decreased risk for dementia (Kuiper et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Piolatto et al., \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Conversely, a lack of social connections and experiences of high perceived stress or negative emotions are associated with increased risk for cognitive decline (Aggarwal et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Jurgens et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Mahalingam et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe association between SEH and cognition is often understood by examining two distinct components of intelligence: 1) Fluid cognitive abilities\u0026mdash;dynamic thinking skills (e.g., executive functions, episodic memory) that reflect biologically based brain processes, which decline across the lifespan and are sensitive to acquired brain injury or disease (Horn, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e1968\u003c/span\u003e; Lovden et al., 2020; Murman, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). 2) Crystallized cognitive abilities\u0026mdash;accumulated knowledge, tend to stabilize or slightly improve with experience, and are less susceptible to injury (Tucker-Drob et al., \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Because of the distinct theoretical separation between these cognitive domains, there is a lack of empirical work examining the association of SEH separately with fluid and crystallized cognition, particularly when accounting for age and clinical risk factors. Chronic Alcohol Use Disorder (AUD) and related disorders can affect both SEH and cognitive abilities. There is evidence that AUD and SEH deficits are intertwined, reflecting a recognized bidirectional relationship: poor emotion regulation often precedes substance use (Khantzian, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e1990\u003c/span\u003e; Koob, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), and chronic alcohol consumption can impair social function and emotional competence (Maurage et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; The Ridge Ohio, \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Further, AUD is also associated with accelerated damage to brain structure and cognitive decline, particularly in fluid abilities (Wang et al., \u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Yen et al., \u003cspan citationid=\"CR96\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Our own work corroborates this, using a sample of individuals enriched for AUD from the COGA study (Collaborative study on the Genetics of Alcoholism), we showed that a lifetime history of AUD is linked to decreases in fluid cognition (Pandey et al., \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Given that maintaining good SEH strengthens neural circuits that buffer against cognitive decline (Zhaoyang et al., \u003cspan citationid=\"CR99\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Wilson et al., \u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e2003\u003c/span\u003e), understanding the SEH\u0026ndash;cognition link in later life is critical, particularly within a population enriched for AUD. While prior studies have demonstrated that social-emotional factors should be considered when examining brain functioning and AUD across the lifespan, the extent to which stressors and social supports have lasting, differential effects on cognitive functioning in younger and later-life adults remains largely unknown.\u003c/p\u003e \u003cp\u003eLeveraging data collected from the Collaborative Study on the Genetics of Alcoholism (COGA), this work examines how six specific measures of SEH (three positive factors: emotional support, instrumental support, friendship, and three negative factors: loneliness, negative affect, and perceived stress) are associated with fluid cognition and crystallized cognition. We also examine influences of SEH on physical functioning for comparison, given its established link to physical morbidity and mortality. To identify whether the observed associations are specific to a specific life-stage, we also perform analyses stratified by younger and later-life adults. This comparison is vital for establishing whether social and emotional well-being consistently shape cognitive outcomes throughout life, or if their effect is magnified by the unique convergence of cumulative neurophysiological vulnerability and significant psychosocial shifts (e.g., changes in vocational roles, caregiving status, and peer or partner loss) in later-life. Finally, given research that social networks/support systems differ significantly by gender (Antonucci \u0026amp; Akiyama, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e1987\u003c/span\u003e; Zhaoyang et al., \u003cspan citationid=\"CR100\" class=\"CitationRef\"\u003e2024\u003c/span\u003e, (Rogowska et al., \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Zhaoyang et al., \u003cspan citationid=\"CR100\" class=\"CitationRef\"\u003e2024\u003c/span\u003e)), we also examined associations separately in women and men.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e \u003cb\u003eSample.\u003c/b\u003e Data (\u003cem\u003eN\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1,476; 51% female; 61% with a lifetime history of AUD) are drawn from the Collaborative Study on the Genetics of Alcoholism (COGA). COGA is a longitudinal, family-based cohort that has characterized individuals from large pedigrees densely affected by AUD, alongside community comparison families, across clinical, behavioral, and neurobiological domains (Agrawal et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Dick et a., 2023; Meyers et al., \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Since its inception in 1989, COGA has assessed 17,878 individuals across 2,246 families. Data collection has focused on distinct participant subsets across four principal waves: (a) Wave 1 (1991\u0026ndash;1999) initial ascertainment; (b) Wave 2 (1996\u0026ndash;2005) follow-up and new family assessment; (c) the Prospective Wave (2004\u0026ndash;2019) focused on youth; and (d) the current Lifespan wave (2019-ongoing). The analytic sample for this study is derived exclusively from the Lifespan wave, in which previously assessed younger adult participants from the Prospective wave and later life adults (ages 50+) are re-assessed using updated protocols, including the NIH Toolbox (NIHTB) Emotion and Cognition batteries. The current study included all 1,476 individuals who completed both NIHTB batteries, comprising 558 younger adults (ages 22\u0026ndash;49; 56% with a lifetime AUD dx) and 918 later-life adults (ages 50+; 64% with a lifetime AUD dx). Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e presents descriptive statistics for the key variables across these age groups.\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 for the key variables in the overall sample and across younger and later-life adults with group differences.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"16\"\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=\"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 \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=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" 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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c15\" colnum=\"15\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c16\" colnum=\"16\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003eAll Subjects (\u003cem\u003eN\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1476)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c9\" namest=\"c7\"\u003e \u003cp\u003eYounger Adults (\u003cem\u003eN\u003c/em\u003e\u0026thinsp;=\u0026thinsp;558)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c13\" namest=\"c11\"\u003e \u003cp\u003eLater-life Adults (\u003cem\u003eN\u003c/em\u003e\u0026thinsp;=\u0026thinsp;918)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c16\" namest=\"c14\"\u003e \u003cp\u003e\u003cem\u003et\u003c/em\u003e-Test\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eN\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003e%\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eM(SD)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eN\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003e%\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cem\u003eM(SD)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cem\u003eN\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cem\u003e%\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cem\u003eM(SD)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cem\u003edf\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cem\u003et\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c16\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e \u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1476\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e100.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e52.30 (14.73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e558\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e100.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e35.91 (5.86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e918\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e100.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e62.26 (8.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWomen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1476\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e60.0%\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e558\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e59.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e918\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e60.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-Hispanic Whites\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1476\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e73.0%\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e558\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e67.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e918\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e76.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDSM-5 AUD dx\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1475\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e61.0%\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e557\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e55.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e918\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e64.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e1140.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e-3.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEmotional Support\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1462\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e99.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e47.31 (10.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e554\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e99.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e47.34 (11.21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e908\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e98.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e47.28 (9.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e1042.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e.104\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e.459\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInstrumental Support\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1462\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e99.1\u003csup\u003e%\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e48.12 (10.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e554\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e99.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e46.71 (10.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e908\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e98.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e48.98 (10.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e1460.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e-4.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFriendship\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1462\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e99.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e47.08 (10.51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e554\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e99.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e46.65 (10.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e908\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e98.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e47.34 (10.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e1460.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e-1.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e.111\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLoneliness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1462\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e99.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e54.07 (10.62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e554\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e99.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e55.60 (10.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e908\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e98.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e53.14 (10.31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e1460.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e4.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNegative Affect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1460\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e98.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e51.41 (10.62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e554\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e99.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e53.50 (11.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e906\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e98.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e50.13 (9.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e1049.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e5.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePerceived Stress\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1461\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e99.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e51.30 (9.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e554\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e99.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e53.60 (9.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e907\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e98.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e49.89 (8.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e1074.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e7.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFluid Cognition\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1422\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e96.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e50.09 (11.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e542\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e97.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e50.88 (12.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e880\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e95.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e49.60 (11.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e1011.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e1.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e.027\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCrystallized Cognition\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1430\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e96.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e52.18 (9.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e546\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e97.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e52.60 (10.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e884\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e96.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e51.92 (9.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e1058.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e1.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e.220\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePhysical Functioning\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1282\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e86.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e78.70 (25.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e468\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e83.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e87.03 (21.52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e814\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e88.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e73.91 (26.97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e1151.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e9.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"16\"\u003e\u003csup\u003ea\u003c/sup\u003eGender was coded 1\u0026thinsp;=\u0026thinsp;men, 2\u0026thinsp;=\u0026thinsp;women; proportion of women in the sample is presented. All participants gender identity matched their sex assigned at birth.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"16\"\u003e\u003csup\u003eb\u003c/sup\u003eRace/ethnicity was coded 1\u0026thinsp;=\u0026thinsp;Whites, 2\u0026thinsp;=\u0026thinsp;Blacks, 3\u0026thinsp;=\u0026thinsp;Other; proportion of Whites in the sample is presented\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"16\"\u003e\u003csup\u003ec\u003c/sup\u003eDSM-5 AUD dx 1\u0026thinsp;=\u0026thinsp;No AUD, 5\u0026thinsp;=\u0026thinsp;AUD; proportion of individuals with AUD lifetime diagnosis is presented. \u003csup\u003e#\u003c/sup\u003eTwo-sided \u003cem\u003ep.\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eMeasures\u003c/h2\u003e \u003cp\u003e \u003cb\u003eFluid Cognition.\u003c/b\u003e The fluid cognition data were obtained from the NIHTB Cognition battery (iPad version 2). The NIHTB Cognition Battery assesses neurocognitive domains grouped into fluid and crystallized cognitive abilities (Weintraub et al., 2013). The fluid cognition composite (α\u0026thinsp;=\u0026thinsp;.83) is an average of five tests assessing various domains: the dimensional change card sort test (cognitive flexibility), the flanker inhibitory control and attention test (inhibitory control), the list sorting working memory test, the picture sequence memory test (episodic memory), and the pattern comparison processing speed test. These tests cover domains related to logical reasoning and novel problem-solving (Cattell, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e1967\u003c/span\u003e; Dikmen et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Gershon et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Heaton et al., 2014; Karr et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Tulsky et al., 2014; Zelazo et al., \u003cspan citationid=\"CR98\" class=\"CitationRef\"\u003e2013\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cb\u003eCrystallized Cognition.\u003c/b\u003e The crystallized cognition composite (α\u0026thinsp;=\u0026thinsp;.84) is an average of the picture vocabulary test (identifying pictures corresponding to spoken words) and the oral reading recognition test (pronouncing printed words) (Akshoomoff et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Carlozzi et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Gershon et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2014\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Prior work from our research group has indicated diminished performance in both fluid (e.g., response inhibition) and crystallized (e.g., episodic memory) domains in individuals with AUD (Pandey, et al., \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eFor both fluid and crystallized cognition, we used the demographic-adjusted T-scores (M\u0026thinsp;=\u0026thinsp;50, SD\u0026thinsp;=\u0026thinsp;10) for both composites, which control for the effects of age, self-reported gender, education, and race/ethnicity (Casaletto et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cb\u003eSocial-Emotional Health (SEH) Factors.\u003c/b\u003e The SEH factors were assessed using the iPad version 2 of the NIHTB Emotion Battery. This battery assesses emotions via 17 individual scales grouped into four theoretically derived subdomains: psychological well-being, social relationships, negative affect, stress and self-efficacy (Salsman et al., 2013). The individual scales demonstrate high internal consistency (α typically\u0026thinsp;\u0026ge;\u0026thinsp;0.85; Salsman et al., 2013). We selected three positive scales (i.e., emotional support, instrumental support, friendship) and three negative scales (loneliness, negative affect, and perceived stress) to capture a comprehensive and balanced assessment of both protective and risk facets of social-emotional well-being. We utilized these six specific SEH factors in this study, rather than the broader subdomains, to achieve greater precision in examining the differential associations of discrete social components (support, loneliness) and emotional components (affect, stress) with our outcomes. The instrument employs Computer Adaptive Testing (CAT) and utilizes Item Response Theory scoring, yielding demographic-adjusted T-scores (M\u0026thinsp;=\u0026thinsp;50, SD\u0026thinsp;=\u0026thinsp;10) (Yang \u0026amp; Kao, \u003cspan citationid=\"CR94\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). This CAT approach generates individualized item sets for highly accurate and efficient assessment of each latent construct.\u003c/p\u003e \u003cp\u003e \u003cb\u003ePhysical functioning.\u003c/b\u003e Physical functioning was assessed using the Physical Functioning (PF) subscale from the 36-Item Short Form Health Survey (SF-36), a widely used, self-reported measure of general health status (Ware, \u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e2000\u003c/span\u003e; Ware \u0026amp; Sherbourne, \u003cspan citationid=\"CR89\" class=\"CitationRef\"\u003e1992\u003c/span\u003e). The inclusion of physical functioning provides a non-cognitive outcome measure known to be associated with both SEH and age, allowing for a comparative examination of the observed associations. The PF subscale consists of ten items that specifically assess the degree of limitation in common physical and mobility activities (e.g., walking specified distances, climbing stairs, carrying groceries) (Syddall et al., \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). For analysis, the PF subscale is scored such that higher scores reflect superior physical functioning and fewer self-reported limitations. Individual items are scored from 1\u0026thinsp;=\u0026thinsp;limited a lot to 3\u0026thinsp;=\u0026thinsp;not limited at all).\u003c/p\u003e \u003cp\u003e \u003cb\u003eDSM-5 AUD Lifetime Diagnosis\u003c/b\u003e. Information from participants\u0026rsquo; Semi-Structured Assessment for the Genetics of Alcoholism (SSAGA; Bucholz et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e1994\u003c/span\u003e) interview was used to classify AUD status. Specifically, interviewed subjects were coded as affected (1) or unaffected (0) based on whether they met lifetime criteria for DSM-5 AUD. That is, subjects who endorsed 2 or more criteria that clustered within a single 12-month period were diagnosed with AUD.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eStatistical Analyses\u003c/h3\u003e\n\u003cp\u003eThe data were analyzed using IBM SPSS AMOS, Version 29.0. First, bivariate correlation analysis (Pearson's coefficient) was computed to examine associations among the three outcome variables (Fluid Cognition, Crystallized Cognition, Physical Functioning) and the six social-emotional health (SEH) variables. Next, the primary analysis utilized Hierarchical Multiple Regression (HMR) to examine the unique and interactive effects of each of the six SEH factors on the three outcomes. Each model included one continuous SEH factor as the primary predictor, moderated by Gender, Age Group, and AUD Dx. Each model included only one SEH factor as the independent variable because we wanted: 1. To more accurately capture each factor\u0026rsquo;s unique contribution to cognition and physical functioning, 2. To avoid multicollinearity among SEH constructs, and 3. To facilitate interpretation of higher-order interaction effects. We specifically included interaction terms involving AUD Dx to assess its role as a moderator. The continuous SEH factor was grand-mean centered, and all categorical moderators were entered using effect coding.\u003c/p\u003e \u003cp\u003eThe HMR primary analysis was performed to determine the significance of the two-way and three-way interaction terms. Given that the HMR revealed significant interactions only for Age Group and Gender (and not for AUD Dx; See Tables S1 and S2), simple slopes analyses were performed as planned comparisons exclusively to probe the moderating effects of these two variables. The main effect of AUD Dx was not statistically significant across any of the HMR models for fluid and crystallized cognition outcomes (all \u003cem\u003ep\u003c/em\u003es\u0026thinsp;\u0026ge;\u0026thinsp;0.321). Similarly, the interactions involving AUD Dx were consistently non-significant for all six SEH factors (all \u003cem\u003ep\u003c/em\u003es\u0026thinsp;\u0026ge;\u0026thinsp;0.212), including the 2-way and 3-way AUD interactions, and therefore, no further testing was conducted to probe AUD moderation. However, all estimates of simple slopes reported here reflect models that were fully adjusted for lifetime AUD diagnosis.\u003c/p\u003e \u003cp\u003eThe Benjamini-Hochberg (BH) False Discovery Rate (FDR) procedure was applied separately for each outcome variable (Fluid Cognition, Crystallized Cognition, and Physical Functioning) to control the rate of Type I errors (FDR controlled at Q\u0026thinsp;=\u0026thinsp;0.05). For each outcome, the simple slopes tests were grouped into two distinct families of tests: 1. Age Group: The 12 \u003cem\u003ep\u003c/em\u003e-values resulting from testing the effect of all six SEH factors within the later-life adult group and the younger adult group (6 SEH factors x 2 groups\u0026thinsp;=\u0026thinsp;12 tests) were pooled. 2. Gender Group: The 12 \u003cem\u003ep\u003c/em\u003e-values resulting from testing the effect of all six SEH factors within the men and women groups (6 SEH factors x 2 groups\u0026thinsp;=\u0026thinsp;12 tests) were pooled. Only simple slopes tests meeting the adjusted BH threshold for their respective family were declared statistically significant. Descriptive statistics for key variables in the study for the overall sample and separately for younger and later-life adults are reported in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e (See Table S3 for bivariate correlations among key variables).\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eOverall, as shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, conditional effects of SEH on fluid cognition were highly specific to age (see Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Among younger adults, no significant associations emerged between any of the six SEH factors and fluid cognition. This contrasted sharply with the findings in later-life adults, where all three positive SEH factors (i.e., emotional support, instrumental support, and friendship) were significantly associated with higher fluid cognition (all \u003cem\u003ep\u003c/em\u003es\u0026thinsp;\u0026le;\u0026thinsp;0.003, BH corrected), and conversely, all three negative SEH factors (i.e., loneliness, negative affect, and perceived stress) were significantly associated with lower fluid cognition (all \u003cem\u003ep\u003c/em\u003es\u0026thinsp;\u0026le;\u0026thinsp;0.009, BH corrected). Associations with crystallized cognition were notably weaker: only two negative SEH factors (i.e., negative affect and perceived stress) were significantly associated with lower crystallized cognition in later life (all \u003cem\u003ep\u003c/em\u003es\u0026thinsp;\u0026le;\u0026thinsp;0.001, BH corrected), while, interestingly, loneliness was positively associated with higher crystallized cognition in younger men (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.004, BH corrected).\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\u003eAssociations of social-emotional factors with Fluid cognition, Crystallized cognition, and physical functioning in younger and later-life adults (adjusted for DSM-5 AUD lifetime dx)\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=\"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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eYounger Adults\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e\u003cem\u003eFluid Cognition\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003e\u003cem\u003eCrystallized Cognition\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c12\" namest=\"c10\"\u003e \u003cp\u003e\u003cem\u003ePhysical Functioning\u003c/em\u003e\u003c/p\u003e \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\u003eSE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cem\u003ep\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\u003eEmotional Support\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.185\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e.412\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e.18\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e.04\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInstrumental Support\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.326\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e.670\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e.157\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFriendship\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.226\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e.994\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e.19\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e.04\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLoneliness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.820\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e.14\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e.04\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e.001\u003c/b\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e\u0026minus;\u0026thinsp;.17\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e.04\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003csup\u003ea\u003c/sup\u003e \u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNegative Affect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.473\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e.175\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e\u0026minus;\u0026thinsp;.24\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e.04\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePerceived Stress\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.250\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e.912\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e\u0026minus;\u0026thinsp;.25\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e.04\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eLater-life Adults\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e\u003cem\u003eFluid Cognition\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003e\u003cem\u003eCrystallized Cognition\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c12\" namest=\"c10\"\u003e \u003cp\u003e\u003cem\u003ePhysical Functioning\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eB\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eSE\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003ep\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003eB\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003eSE\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003ep\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003eB\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003eSE\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003ep\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEmotional Support\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e.15\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e.03\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e.425\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e.14\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e.03\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInstrumental Support\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e.14\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e.03\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e.975\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e.200\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFriendship\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e.10\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e.03\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.003\u003c/b\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e.806\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e.20\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e.03\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLoneliness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e\u0026minus;\u0026thinsp;.10\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e.03\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e.009\u003c/b\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e.625\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e\u0026minus;\u0026thinsp;.19\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e.03\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNegative Affect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e\u0026minus;\u0026thinsp;.13\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e.03\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e\u0026minus;\u0026thinsp;.14\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e.03\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e\u0026minus;\u0026thinsp;.22\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e.03\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePerceived Stress\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e\u0026minus;\u0026thinsp;.13\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e.03\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e\u0026minus;\u0026thinsp;.16\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e.03\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e\u0026minus;\u0026thinsp;.18\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e.03\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"12\"\u003eStatistically significant associations are bolded. \u003csup\u003ea\u003c/sup\u003eAssociations that withstood Benjamini Hochberg multiple test correction with a False Discovery Rate of 0.05.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFurther, as shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, stratification by gender revealed that these robust later-life associations were predominantly driven by women (see Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). In later-life women, emotional support and instrumental support were significantly associated with higher fluid cognition, and although friendship was also associated with higher fluid cognition (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.030), it did not withstand the BH correction. On the other hand, all three negative SEH factors were significantly associated with lower fluid cognition (all \u003cem\u003ep\u003c/em\u003es\u0026thinsp;\u0026le;\u0026thinsp;0.014, BH corrected). In contrast, later-life men showed a more limited pattern, with only instrumental support positively associated with fluid cognition, and only negative affect and perceived stress negatively associated. For physical functioning, associations were robust across all groups: emotional support and friendship were consistently associated with significantly better functioning, while loneliness, negative affect, and perceived stress were consistently associated with significantly poorer functioning in all groups (all \u003cem\u003ep\u003c/em\u003es\u0026thinsp;\u0026lt;\u0026thinsp;0.001, BH corrected), except for later-life men, where only negative affect was significant. These findings suggest that the protective benefits of positive social connections and social support are most prominently limited to fluid cognition (vs. crystallized cognition), particularly among later-life adults, and that the detrimental effects of negative SEH factors were robustly associated with impairment across all three outcomes. Notably, later-life women presented both the strongest positive SEH effects on fluid cognition and the most widespread detrimental effects of negative SEH on fluid cognition, crystallized cognition, and physical functioning.\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\u003eAssociations of social-emotional factors with Fluid cognition, Crystallized cognition, and physical functioning in men and women across younger and later-life age groups (adjusted for DSM-5 AUD lifetime dx)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"22\"\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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c15\" colnum=\"15\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c16\" colnum=\"16\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c17\" colnum=\"17\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c18\" colnum=\"18\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c19\" colnum=\"19\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c20\" colnum=\"20\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c21\" colnum=\"21\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c22\" colnum=\"22\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eYounger Adults\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"10\" nameend=\"c11\" namest=\"c2\"\u003e \u003cp\u003e\u003cem\u003eMen\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"10\" nameend=\"c22\" namest=\"c13\"\u003e \u003cp\u003e\u003cem\u003eWomen\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e\u003cem\u003eFluid Cognition\u003c/em\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003e(n\u0026thinsp;=\u0026thinsp;222)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003e\u003cem\u003eCrystallized Cognition\u003c/em\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003e(n\u0026thinsp;=\u0026thinsp;223)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c11\" namest=\"c9\"\u003e \u003cp\u003e\u003cem\u003ePhysical Functioning\u003c/em\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003e(n\u0026thinsp;=\u0026thinsp;183)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c15\" namest=\"c13\"\u003e \u003cp\u003e\u003cem\u003eFluid Cognition\u003c/em\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003e(n\u0026thinsp;=\u0026thinsp;316)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c19\" namest=\"c17\"\u003e \u003cp\u003e\u003cem\u003eCrystallized Cognition\u003c/em\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003e(n\u0026thinsp;=\u0026thinsp;318)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c22\" namest=\"c20\"\u003e \u003cp\u003e\u003cem\u003ePhysical Functioning\u003c/em\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003e(n\u0026thinsp;=\u0026thinsp;283)\u003c/em\u003e\u003c/p\u003e \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\u003eSE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c13\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c14\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c17\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c18\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c19\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c20\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c21\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c22\"\u003e \u003cp\u003e\u003cem\u003eP\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\u003eEmotional Support\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.861\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e.555\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e.20\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e.08\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e.006\u003c/b\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e.074\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e\u003cb\u003e.13\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e\u003cb\u003e.05\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e\u003cb\u003e.029\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e\u003cb\u003e.17\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e\u003cb\u003e.06\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e \u003cp\u003e\u003cb\u003e.003\u003c/b\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInstrumental Support\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.402\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e.946\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e.570\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e.475\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e.680\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e \u003cp\u003e.174\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFriendship\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.996\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e.211\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e.25\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e.08\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e.103\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e.885\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e\u003cb\u003e.15\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e\u003cb\u003e.06\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e \u003cp\u003e\u003cb\u003e.012\u003c/b\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLoneliness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.110\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e.18\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e.06\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e.004\u003c/b\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e.120\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e.209\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e.084\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e\u003cb\u003e\u0026minus;\u0026thinsp;.21\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e\u003cb\u003e.06\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNegative Affect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.657\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e.073\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e\u0026minus;\u0026thinsp;.18\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e.08\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e.014\u003c/b\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e.217\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e.526\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e\u003cb\u003e\u0026minus;\u0026thinsp;.28\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e\u003cb\u003e.06\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePerceived Stress\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.819\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e.693\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e\u0026minus;\u0026thinsp;.22\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e.08\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e.010\u003c/b\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e.203\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e.873\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e\u003cb\u003e\u0026minus;\u0026thinsp;.29\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e\u003cb\u003e.05\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003csup\u003ea\u003c/sup\u003e\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=\"10\" nameend=\"c11\" namest=\"c2\"\u003e \u003cp\u003e\u003cem\u003eMen\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"10\" nameend=\"c22\" namest=\"c13\"\u003e \u003cp\u003e\u003cem\u003eWomen\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eLater-life Adults\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e\u003cem\u003eFluid Cognition\u003c/em\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003e(n\u0026thinsp;=\u0026thinsp;344)\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003e\u003cem\u003eCrystallized Cognition\u003c/em\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003e(n\u0026thinsp;=\u0026thinsp;345)\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c11\" namest=\"c9\"\u003e \u003cp\u003e\u003cem\u003ePhysical Functioning\u003c/em\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003e(n\u0026thinsp;=\u0026thinsp;309)\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c15\" namest=\"c13\"\u003e \u003cp\u003e\u003cem\u003eFluid Cognition\u003c/em\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003e(n\u0026thinsp;=\u0026thinsp;530)\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c19\" namest=\"c17\"\u003e \u003cp\u003e\u003cem\u003eCrystallized Cognition\u003c/em\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003e(n\u0026thinsp;=\u0026thinsp;533)\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c22\" namest=\"c20\"\u003e \u003cp\u003e\u003cem\u003ePhysical Functioning\u003c/em\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003e(n\u0026thinsp;=\u0026thinsp;498)\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEmotional Support\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.168\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e.229\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e.839\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e.18\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e.05\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e.965\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e\u003cb\u003e.24\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e\u003cb\u003e.05\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInstrumental Support\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e.17\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e.05\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e.283\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e.410\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e.13\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e.05\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e.003\u003c/b\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e.399\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e \u003cp\u003e.416\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFriendship\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.080\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e.971\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e.117\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e.10\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e.05\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e.030\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e.672\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e\u003cb\u003e.28\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e\u003cb\u003e.05\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLoneliness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.217\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e.846\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e.096\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e\u0026minus;\u0026thinsp;.11\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e.05\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e.014\u003c/b\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e.670\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e\u003cb\u003e\u0026minus;\u0026thinsp;.24\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e\u003cb\u003e.05\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNegative Affect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e\u0026minus;\u0026thinsp;.16\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e.05\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e.003\u003c/b\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e\u0026minus;\u0026thinsp;.15\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e.05\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e.003\u003c/b\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e\u0026minus;\u0026thinsp;.13\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e.05\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e.024\u003c/b\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e\u0026minus;\u0026thinsp;.12\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e.05\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e.009\u003c/b\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e\u003cb\u003e\u0026minus;\u0026thinsp;.13\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e\u003cb\u003e.04\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e\u003cb\u003e.006\u003c/b\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e\u003cb\u003e\u0026minus;\u0026thinsp;.29\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e\u003cb\u003e.05\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePerceived Stress\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e\u0026minus;\u0026thinsp;.18\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e.05\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e\u0026minus;\u0026thinsp;.19\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e.05\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e.244\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e\u0026minus;\u0026thinsp;.11\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e.05\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e.014\u003c/b\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e\u003cb\u003e\u0026minus;\u0026thinsp;.15\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e\u003cb\u003e.04\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e\u003cb\u003e.001\u003c/b\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e\u003cb\u003e\u0026minus;\u0026thinsp;.24\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e\u003cb\u003e.05\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"22\"\u003eStatistically significant associations are bolded. \u003csup\u003ea\u003c/sup\u003eAssociations that withstood Benjamini Hochberg multiple test correction with a False Discovery Rate of 0.05.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study provides novel insights into how specific facets of SEH are differentially associated with fluid cognition, crystallized cognition, and physical functioning across the adult lifespan, and differences as a function of age and gender. The findings revealed a pronounced pattern of associations where the influence of SEH was primarily restricted to later-life adults and was most robust in later-life women. Specifically, positive SEH factors (emotional support, instrumental support, and friendship) were consistently and significantly correlated with higher fluid cognition and better physical functioning among later-life adults. Conversely, negative SEH factors (perceived stress, negative affect, and loneliness) were robustly correlated with lower fluid cognition and poor physical functioning in this age group. Interestingly, the most comprehensive pattern of associations emerged among later-life women. They demonstrated the greatest number of significant correlations\u0026mdash;both positive and negative\u0026mdash;across all three outcomes (fluid cognition, crystallized cognition, and physical functioning). Our data show that strong social connections and positive psychosocial factors are associated with higher fluid cognition and better physical capabilities, while negative psychosocial aspects correlate with detrimental outcomes. These results corroborate previous research linking social engagement, support, and positive emotionality to a healthy brain and body (Cyranowski et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Holt-Lunstad et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Kelly et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Kuiper et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Furthermore, the negative associations align with studies highlighting the deleterious effects of negative psychosocial factors on mental and physical well-being (Steptoe \u0026amp; Kivim\u0026auml;ki, \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Sundstrom et al., 2020; Wilson et al., 2007; Yu et al., \u003cspan citationid=\"CR97\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\n\u003ch3\u003eSocial-Emotional Health and Fluid Cognition\u003c/h3\u003e\n\u003cp\u003eFluid Cognition, a core cognitive ability involving logical reasoning and problem-solving in novel situations (Cattell, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e1967\u003c/span\u003e), is closely linked to executive functions essential for optimal social adaptation (Opitz et al., \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Stawski et al., \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2011\u003c/span\u003e) and is vital for overall healthy aging. The role of SEH in overall health is well-documented: positive SEH factors are linked to lower incidence of major physical health issues and resilience against neuropsychiatric disorders (Coyte et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Deane et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Delfin etal., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Kiecolt-Glaser et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Lenferink et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Pandey et al., 2023; Smith, \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Umberson \u0026amp; Montez, \u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Aligned with literature showing that positive SEH is associated with enhanced cognitive functioning (Costa-Cordella et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Haslam et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Mogic et al., \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), our study found that positive SEH factors (emotional support, instrumental support, and friendship) were significantly associated with higher fluid cognition. This protective association can be viewed through the Social Support Theory's stress-buffering hypothesis, which suggests that supportive relationships mitigate stressful events by lowering adverse physiological stress reactions and reducing physiological arousal (Bowen et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Cohen \u0026amp; Wills, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e1985\u003c/span\u003e; Cohen, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e1983\u003c/span\u003e; Costa-Cordella et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Seeman \u0026amp; Crimmins, \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). Beyond stress reduction, supportive social engagement is also associated with increased cognitive reserve and direct neurochemical benefits (Uchino et al., \u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Ybarra et al., \u003cspan citationid=\"CR95\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). Therefore, our finding suggests these positive social interactions may reduce stress and promote healthy coping, thereby protecting critical neural areas and enhancing resilience against cognitive impairment (Kelly et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eConversely, negative SEH factors (loneliness, negative affect, and perceived stress) were significantly associated with lower fluid cognition. This pattern has strong neurobiological relevance and aligns with previous work linking loneliness and negative emotionality to increased physiological arousal (Hypothalamic-Pituitary-Adrenal axis and Sympathetic Nervous System activation), which is associated with poorer cognitive functioning and greater cognitive decline (Girotti et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Luchetti et al., \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Sundstrom et al., 2020). Social disconnection and loneliness are also associated with structural brain differences, including reduced gray matter volume in frontal and temporal regions (Shamay-Tsoory \u0026amp; Kanterman, \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Likewise, chronic stress, linked to negative SEH factors, is also associated with structural changes in brain regions\u0026mdash;such as the hippocampus and prefrontal cortex\u0026mdash;which underpin cognitive functions like memory and executive control (Arnsten et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Blum, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eSocial-emotional health, fluid cognition, and age differences\u003c/h2\u003e \u003cp\u003eOur results demonstrated that associations between SEH and fluid cognition, compared to crystallized cognition, were robust and exclusive to later-life adults, persisting even after controlling for lifetime AUD status. Specifically, all three positive SEH factors were associated with higher fluid cognition, and all three negative SEH factors were associated with lower fluid cognition in later-life adults. The absence of significant associations of SEH and fluid cognition among younger adults may be attributed to their relatively high cognitive reserve (CR) (Stern, \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Wook Yoo et al., \u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). CR, the brain's capacity to function efficiently despite age-related changes or damage (Tucker-Drob, \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2009\u003c/span\u003e), is actively accumulated through diverse life factors, including education, challenging work, and social activity (Fleck et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Consequently, younger adults tend to possess a higher baseline CR, which may effectively shield their cognitive performance, potentially masking the influence of their social-emotional well-being on fluid cognition.\u003c/p\u003e \u003cp\u003eIn contrast, the strong association between SEH and fluid cognition in later life may be due to a natural age-related decline in brain function and a fundamental shift in social priorities. According to the \u003cem\u003eSocioemotional Selectivity Theory\u003c/em\u003e (SST) (Carstensen, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e1992\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2006\u003c/span\u003e), due to a perceived limited future, later-life adults may gradually shift from expanding their social network to concentrating on deeply meaningful and emotionally rewarding, often smaller yet highly valued relationships (Carstensen et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e1999\u003c/span\u003e). The quality of this restricted network is observed to have a stronger relationship with fluid cognition and overall well-being (Carstensen, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e1992\u003c/span\u003e; Carstensen et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e1999\u003c/span\u003e; Reed \u0026amp; Carstensen, \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). This heightened importance of high-quality social support likely accounts for the robust positive association found between positive SEH factors and fluid cognition in this age group. Conversely, as the CR weakens with age, the brain's ability to cope with stress diminishes and negative emotionality (e.g., perceived stress) may dominate. This likely may make cognitive functioning, particularly fluid abilities, more sensitive to the influence of negative SEH factors. Furthermore, negative SEH factors (i.e., loneliness, negative affect, and perceived stress) gain increased salience in later life due to age-related stressors, including declining health, loss of loved ones, and social network attrition (Musich et al., \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Perissinotto et al., \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) making the connection between negative SEH factors and cognition more prominent. This combination of a more vulnerable brain and an accumulation of negative psychosocial experiences may explain why the association between social-emotional well-being and fluid cognition is so clearly visible primarily in later life.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eSocial-emotional health and gender differences\u003c/h3\u003e\n\u003cp\u003eThe observed gender differences are a critical finding, highlighting a potentially distinct pathway through which SEH may affect overall well-being. The consistent and significant associations found between SEH factors and both physical functioning and fluid cognition in women across both age groups suggest that social-emotional well-being may be a uniquely salient factor for female health outcomes. This pattern is well-supported by the Tend-and-Befriend Theory (Taylor et al., \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e2000\u003c/span\u003e; McLean \u0026amp; Anderson, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2009\u003c/span\u003e), which posits that, under stress, women are more likely to engage in behaviors that promote affiliation and social support (\"befriending\"), while men tend to exhibit a classic fight-or-flight response. From a neurobiological perspective, women's stress response, mediated by oxytocin, promotes affiliation (befriending) and actively downregulates the stressful hypothalamic-pituitary-adrenocortical axis. This biologically-driven preference for affiliation suggests that social networks may serve as stress-buffering factors for women, directly influencing their physiological health (e.g., lower blood pressure, reduced cortisol) and cognitive resilience. Furthermore, this greater reliance on social networks could make the association of both positive and negative SEH factors (e.g., social support, negative affect) with cognitive function and overall health more pronounced. Supporting this premise, research by McLean and Anderson (\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2009\u003c/span\u003e) have shown that women are more likely to use coping strategies centered on emotional disclosure, which can mitigate the negative effects of chronic stress on fluid cognitive performance (Lupien et al., \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). The greater consistency of these associations in women may therefore reflect the deeper, biologically-integrated connection between their social and emotional lives and their physiological and cognitive systems.\u003c/p\u003e \u003cp\u003eIn contrast, while men also showed some significant associations, their fewer and less consistent links suggest that perhaps different aspects may play a role in the relationship between their social-emotional state and their cognitive and physical health. This may be related to gendered socialization patterns, which often discourage men from outwardly expressing vulnerability or seeking emotional social support in the same way as women (M\u0026ouml;ller-Leimk\u0026uuml;hler, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). Consequently, the impact of their SEH on their health outcomes may be mediated by different, less direct pathways, such as internalizing stress or relying on non-social coping strategies, potentially dampening any significant association of SEH measures on their cognitive and physical health. Future research should aim to decipher these nuanced, gender-specific differences across the lifespan.\u003c/p\u003e\n\u003ch3\u003eStrengths and limitations\u003c/h3\u003e\n\u003cp\u003eThe current study has several strengths. To our knowledge, this is the first study to examine the associations of SEH factors with fluid cognition, crystallized cognition and physical functioning with a focus on both age and gender differences. Notably, this work used standardized scores from the NIH-TB Cognition and Emotion batteries, making these findings more generalizable. Furthermore, this study stands out by uniquely exploring the relationship of fluid cognition (focus outcome) with a comprehensive range of social-emotional health factors, including both positive and negative aspects. Further, as comparative outcomes, crystallized cognition and physical functioning were also examined.\u003c/p\u003e \u003cp\u003eNevertheless, several limitations of this study should also be considered. Specifically, the cross-sectional design limits the ability to establish causal relationships between the SEH factors and the outcomes. Given the possibility that SEH and cognitive functioning may be bidirectional (Llewellyn et al., \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2008\u003c/span\u003e), longitudinal studies are needed to further elucidate the directionality and temporal dynamics of these associations. Additionally, the reliance on self-reported measures of SEH and physical functioning may introduce reporting bias. Future research could benefit from incorporating objective measures of physical and alternate cognitive function assessments. In addition, the age-groups examined in this study are broad and may represent more than one developmental epoch. As the sample grows there will be more statistical power to examine more narrowly defined/meaningful age groups.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn conclusion, this study provides valuable insights into the complex interplay between social emotional health, fluid cognition, and physical functioning in younger and later-life adults, highlighting important gender differences. The findings underscore the significant role of social emotional well-being, particularly for later-life women, in maintaining both physical and cognitive health across the adult lifespan. These results have implications for interventions aimed at promoting social connectedness and mitigating negative emotional states to support healthy aging.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eConflict of Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no conflict of interest.\u003c/p\u003e\n"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAggarwal, N. T., Wilson, R. S., Beck, T. L., Rajan, K. B., Mendes de Leon, C. F., Evans, D. A., \u0026amp; Everson-Rose, S. A. (2014). 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Gender differences in social support and physiological health: A longitudinal study. \u003cem\u003eHealth Psychology\u003c/em\u003e, \u003cem\u003e43\u003c/em\u003e(2), 112\u0026ndash;124. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.google.com/search?q=https://\u003c/span\u003e\u003cspan address=\"https://www.google.com/search?q=https://\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003edoi.org/10.1037/hea0001334\u003c/span\u003e\u003cspan address=\"10.1037/hea0001334\" 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":"translational-psychiatry","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"tp","sideBox":"Learn more about [Translational Psychiatry](http://www.nature.com/tp/)","snPcode":"41398","submissionUrl":"https://mts-tp.nature.com/cgi-bin/main.plex","title":"Translational Psychiatry","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-8970690/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8970690/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eSocial-Emotional Health (SEH)\u0026mdash;the quality of social relationships and emotional well-being\u0026mdash;is crucial for maintaining health and cognitive functioning. Given elevated cognitive impairment risk in aging and Alcohol Use Disorder (AUD) populations, we investigated associations between specific SEH factors and cognitive and physical functioning in individuals from families enriched for AUD.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eData from the Collaborative Study on the Genetics of Alcoholism (COGA, analytic \u003cem\u003eN\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1,476, 61% lifetime AUD) were analyzed, grouping participants into younger (22\u0026ndash;49 years) and later-life (50\u0026thinsp;+\u0026thinsp;years) adults. Six SEH factors, fluid cognition (e.g., logical reasoning), and crystallized cognition (e.g., vocabulary) were measured via the NIH Toolbox Cognition and Emotion batteries. Physical functioning (SF-36), a self-reported measure of general health, was included as a non-cognitive comparison, with age and gender tested as moderators.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eSEH associations with fluid cognition and physical functioning were robust and conditional on age and gender. In later-life adults, all three positive SEH factors (Emotional Support, Instrumental Support, Friendship) were associated with higher fluid cognition, while all three negative factors (Loneliness, Negative Affect, Perceived Stress) were associated with lower fluid cognition. These associations were predominantly observed in later-life women and were independent of lifetime AUD history. While physical functioning showed widespread SEH associations across groups, SEH was not associated with fluid cognition in younger adults.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eSEH shows robust, age- and gender-specific associations with fluid cognition and physical health. The SEH-fluid cognition link appears to be a late-life phenomenon particularly salient for women and independent of an individual\u0026rsquo;s lifetime AUD history.\u003c/p\u003e","manuscriptTitle":"Social-Emotional Health and Cognitive Functioning Among Individuals from Families Enriched for Alcohol Use Disorder","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-08 17:34:12","doi":"10.21203/rs.3.rs-8970690/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"This content is not available.","date":"2026-03-23T13:57:04+00:00","index":1,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2026-03-11T13:34:31+00:00","index":1,"fulltext":"This content is not available."},{"type":"reviewersInvited","content":"","date":"2026-03-02T23:02:58+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-02T12:12:06+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-02T11:30:18+00:00","index":"","fulltext":""},{"type":"submitted","content":"Translational Psychiatry","date":"2026-03-01T17:17:36+00:00","index":"","fulltext":""},{"type":"checksFailed","content":"","date":"2026-02-26T11:15:24+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"translational-psychiatry","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"tp","sideBox":"Learn more about [Translational Psychiatry](http://www.nature.com/tp/)","snPcode":"41398","submissionUrl":"https://mts-tp.nature.com/cgi-bin/main.plex","title":"Translational Psychiatry","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"0c4418d2-26c5-4453-b9f2-ee5d7fefa1f5","owner":[],"postedDate":"March 8th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":63803579,"name":"Health sciences/Diseases/Psychiatric disorders/Addiction"},{"id":63803580,"name":"Biological sciences/Psychology/Human behaviour"}],"tags":[],"updatedAt":"2026-03-08T17:34:13+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-08 17:34:12","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8970690","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8970690","identity":"rs-8970690","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}