Typically, Older People Rate Their Health in a Negative Fashion

Wellness Psychol. Author manuscript; available in PMC 2015 Jun 15.

Published in final edited form as:

PMCID: PMC4467537

NIHMSID: NIHMS697184

Social Relationships, Leisure Activity, and Health in Older Adults

Abstract

Objective

Although the link betwixt enhanced social relationships and ameliorate health has more often than not been well established, few studies take examined the role of leisure activity in this link. This study examined how leisure influences the link betwixt social relationships and health in older age.

Methods

Using data from the 2006 and 2010 waves of the nationally representative U.S. Health and Retirement Study and structural equation modelling analyses, we examined data on ii,965 older participants to determine if leisure activities mediated the link between social relationships and wellness in 2010, decision-making for race, teaching level, and health in 2006.

Results

The results demonstrated that leisure activities mediate the link between social relationships and health in these age groups. Perceptions of positive social relationships were associated with greater interest in leisure activities, and greater involvement in leisure activities was associated with better health in older historic period.

Give-and-take & Conclusions

The contribution of leisure to health in these age groups is receiving increasing attention, and the results of this study add to the literature on this topic, by identifying the mediating effect of leisure activeness on the link between social relationships and wellness. Future studies aimed at increasing leisure activity may contribute to improved health outcomes in older adults.

Keywords: leisure activity, social relationships, health, older age, structural equation model

With aging, individuals often decline in concrete and cognitive functions, and social networks may narrow (Chen & Feeley, 2013). Considering much literature demonstrates that social relationships are positively associated with health condition across the life bridge (e.g., Cohen, 2004; Uchino, Cacioppo, & Kiecolt-Glaser, 1996), the narrowing of social networks (as one mensurate of social relationships) may be problematic for wellness in older age and lessen subjective well-being, life satisfaction, and quality of life (Berkman & Syme, 1979; Cohen, 2004). Thus, identifying modifiable factors that may aid in more limited establishing social relationships is important: Health-promoting behaviors, such as leisure activity, may strengthen the link between social relationships and health.

Cohen and Wills (1985) proposed a chief effects model to test that link: Positive social relationships (i.east., college social support or lower social strain) benefit on health outcomes in adults, regardless of the stress they experience, in office by motivating the utilise of wellness-promoting behaviors (Smith & Christakis, 2008). Individuals with enhanced social relationships not only ameliorate psychological well-being (e.yard., by gaining a sense of belonging and lessening low), but also physical health (east.g., by enhancing immune function and reducing heart attack risks) (Cohen, 2004). Employing this main furnishings framework, Chen and Feeley (2013) used structural equation modelling and 2008 Wellness and Retirement Report data to examine the link betwixt social relationships and well-existence, finding that well-beingness improves with higher levels of social support or lower levels of strain, which indirectly mediated individuals' loneliness. Although their findings supported a main effects model, their cross-sectional sample did not provide sufficient evidence of positive changes in well-existence. Thus, they recommended that futurity research explore other potential mediators betwixt social relationships and well-being.

Leisure action has been examined as such a mediator (e.g., Cohen-Mansfield, et al., 2012). In this context, leisure activities are divers as preferred and enjoyable activities participated in during one's free time (Kleiber & Nimrod, 2009), and characterized as representing freedom and providing intrinsic satisfaction (Kelly, 1996). Individuals can recover from stress; restore social and concrete resources (Pressman et al., 2009) through leisure activities. Leisure activities with others may provide social support and, in turn, mediate the stress-health relationship (Coleman & Iso-Ahola, 1993), enrich pregnant of life (Carruthers & Hood, 2004), recovery from stress, and restoration of social and physical resources (Pressman, et al., 2009), as well as helping older adults arrange to potential restrictions of chronic conditions (Hutchinson & Nimrod, 2012) and overcome negative life events (e.grand., losing a loved one) (Janke, Nimrod, & Kleiber, 2008).

Because engaging in leisure activities may affect different aspects of well-being (Gautam, et al., 2007), the specific type of leisure activity may be particularly salient, with some types of activities providing more benefit than others. Paillard-Borg and colleagues (2009) examined v types of leisure activities in older adults — mental, social, physical, productive, and recreational to assess how participation affects health condition. They establish that mental activities (e.thousand., writing, reading) were not only the most popular type of leisure activities, simply besides enhanced well-existence the nigh In dissimilarity, Silverstein and Parker (2002) divided fifteen leisure activities into half-dozen domains: culture-amusement, productive-personal growth, outdoor-physical, recreation-expressive, friendship, and formal-group. They found that engaging in friendship-blazon leisure activities (due east.chiliad., visiting friends) resulted in the highest quality of life in older Swedish adults. Finally, in a recent review of literature on social and leisure activities and well-beingness in older adults, Adams and colleagues (2011) concluded that informal social activity (due east.g., going to clubs) benefited well-being the most.

Previous studies have widely investigated the link between social relationships and health, also as between leisure and wellness, but comparatively piffling research has examined if leisure mediates the link between social relationships and health in older adults based on a main furnishings model. We adopted this model to examine both psychological (i.east., social relationships) and behavioral (i.e., leisure activities) influences on older adults' wellness, supplementing the findings of earlier studies. Nosotros investigate if leisure mediates the association between social relationships and health outcomes (i.due east., physical health and psychological well-existence), using Wellness and Retirement Study data in 2006 and 2010 and structural equation modelling. Our conceptual model (figure 1) indicates that although social relationships independently predict both concrete health and psychological well-beingness, we hypothesize that leisure activeness volition mediate these links. We posit that higher levels of positive social relationships are associated with ameliorate wellness, and that leisure activities will explain part of that relationship.

Methods

Participants

Data were drawn from the Health and Retirement Study (HRS), originally launched in the U.S. in 1992, supported past the National Institute on Aging (NIA U01AG009740) and the Social Security Administration, and designed to monitor health and related social roles in adults over age 50. Core interviews were conducted in the participants' homes in 1992; follow-upwards interviews were conducted past phone every 2 years thereafter. The HRS surveys a representative sample of 26,000 Americans every 2 years (http://hrsonline.isr.umich.edu). Starting in 2006, the HRS also began collecting psychosocial information (due east.1000., life satisfaction and leisure activities) through self-administered questionnaires on a random sample of 50% of core interview participants (i.due east., thirteen,000 Americans). One-half of those participants were interviewed in 2006 (n=6,500), and i-one-half in 2008 (n=6,500). Those who were interviewed in 2006 were re-interviewed in 2010. The present written report was based on information from the subsample of HRS respondents in 2006 and 2010 cadre interviews who besides completed the psychosocial questionnaire in 2006 and 2010 (n= 4,697). We eliminated cases for participants who had missing information on any of the fundamental analytic variables (social support, social strain, and leisure activity in 2010; physical health and psychological well-being in both 2006 and 2010). The final analytic sample included 2,965 older adults betwixt ages fifty-96 (M=64.62; SD=9.92), most of whom were married (91.8%) and White (83.1%); half (50.2%) were female (Table ane). Compared to the overall sample in 2010 (average historic period = 69.79; female = 54.viii%; married = 59%; White = 83.55%), the analytic sample was quite similar.

Table 1

Sociodemographic Characteristics of Written report Sample, 2006, Wellness and Retirement Study

Variables	Frequency (%)
Historic period
50-64	1029 (34.7)
65-74	1142 (38.5)
75-84	667 (22.5)
Over 85	127 (4.3)
Instruction
Less than high school	585 (19.7)
High school	1491 (50.3)
Some higher	152 (v.one)
4-year college	437 (fourteen.7)
More than than college	300 (10.1)
Sex
Male	1476 (49.8)
Female person	1489 (50.2)
Marital Status
Never married	17 (0.half-dozen)
Widowed	76 (ii.6)
Separated	147 (v.0)
Married	2725 (91.9)
Race
White	2608 (88.0)
Blackness	276 (ix.three)
Others	81 (two.7)

Note: Due north=2965.

Measures

Our latent constructs were developed with scaled HRS data that assessed self-reported social relationships in 2010, leisure activities in 2010, psychological well-being in both 2006 and 2010, and physical health in both 2006 and 2010. Each scale was tested for reliability before conducting the main effects model; and factor assay tested latent variable quality based on the principal furnishings model (Cohen & Wills, 1985). For case, the six health-related scales described below (i.e., number of comorbidities, trunk mass index, self-reported health, depressive symptoms, life satisfaction, and insomnia) were combined into two latent variables, concrete health and psychological well-being, based on factor analytic results and previous literature (e.g., Hopman, et al., 2009). Detailed information on the written report mensurate follows and is summarized in Tabular array 2.

Tabular array 2

Summary of Latent Variable Descriptions

Latent Variables	Measurements	Years	Coding
Social relationships	Social back up	2010	Sum score of all items
	Social strain	2010	Reversed all items then sum score of all items
Leisure activities	Mental	2010	Hateful score of all items
	Concrete	2010	Mean score of all items
	Social	2010	Mean score of all items
	Productive	2010	Mean score of all items
Concrete wellness	BMI	2006, 2010	1 (normal) to 4 (very severely underweight/overweight)
	Number of comorbidities	2006, 2010	Total number of chronic conditions
	Self-reported physical wellness	2006, 2010	Reversed the item*
Psychological well-existence	CES-D	2006, 2010	Sum score of all items*
	Insomnia	2006, 2010	Sum score of all items*
	Life satisfaction	2006, 2010	Reversed all items and then mean score of all items*

Social relationships

The independent latent variable 'social relationships' represents the quality of social integration: level of social support and strain experienced from a spouse/partner, other family members, children, or friends, adult past Walen and Lachman (2000), and found to be reliable in previous studies (e.m., Chen & Feeley, 2013). Social back up was measured by three-signal items, anchored by ane (non at all) and 3 (a lot). A sample item of social support was "How much practise they actually understand the way yous experience virtually things?" Social strain was measured with four 3-point items, anchored by i (non at all) and 3 (a lot). A sample detail of social strain was "How oftentimes do they make besides many demands on y'all?" A higher score stand for higher social strain/social support. In order to combine social strain and social back up into the latent variable 'social relationship', the social strain items were reverse-coded and summed then that a higher score indicated lower social strain. A factor assay for all social support/strain and the concepts of main outcome model supported combining this overall latent variable for two support and strain items.

Leisure activities

Frequency of leisure activities ranged from 1 (never) to 6 (daily), based on participants' previous leisure experiences with 18 dissever leisure activities. A sample question was "How often y'all do each activity: Watch television?" The latent variable 'leisure activities, which was viewed as a mediator between social relationships and physical health every bit well as psychological well-beingness, measured iv types of leisure activities (i.e., mental, e.one thousand., read books, watch Telly; social, e.g., do action with grandchildren, go to a club; physical, e.thou., do home maintenance, walk; and productive, east.one thousand., cook, make dress), based on previous literature (i.e., Adams, et al., 2011; Paillard-Borg, et al., 2009) and Exploratory factor analytic (EFA) results. Noting that leisure is defined every bit non involving paid employment (Kleiber, et al., 2011), we also included household chores (e.m., do dwelling house maintenance, cook) equally a type of leisure activity (e.g., Paillard-Borg, et al., 2009). The scales were averaged as indicators for participation levels in the four types of leisure activities, with higher scores reflecting greater participation.

Physical wellness

The latent variable 'physical health' included body mass index (BMI), cocky-reported physical health, and number of comorbidities, measured as controls in 2006 and outcomes in 2010. Combining these variables into such latent variables was referred to in previous studies (east.g., Hopman, et al., 2009) and supported by our gene analyses. In guild to create a BMI indicator where the larger score indicated riskier BMI, we calculated BMI past dividing respondents' self-measured weight past squared acme and categorized it as: 1 (normal, BMI = xviii.5 – 25), 2 (underweight/overweight, BMI = 16 – eighteen.5or 25 – 30), 3 (moderately to severely underweight/overweight, BMI = 15 – xvi or xxx – xl), and iv (very severely underweight/overweight, BMI = BMI < 15 or > 40), according to the Earth Health Arrangement's definition and categorization of BMI. Self-reported physical health measured respondents' subjective health, ranging from 1 (poor) to 5 (fantabulous), derived from the National Wellness Interview Survey (Wallace & Herzog, 1995). The number of comorbidities was based on the total diagnosed chronic conditions (high claret pressure, diabetes, cancer, lung affliction, middle condition, and stroke) reported by participants ("Has a doctor ever diagnosed you with….?").

Psychological well-beingness

The latent variable 'psychological well-being' represented the effects of depressive symptoms, life satisfaction, and insomnia. Depressive symptoms were measured past the abbreviated viii-item Center for Epidemiologic Studies Depression Scale (CES-D; Radloff, 1977), the items summed to create an indicator for psychological distress, with a college score reflecting greater depressive symptomatology. Life satisfaction was measured by Diener'southward (1994) 5-item Subjective Well-being Scale, with responses ranging from 1 (strongly disagree) to 6 (strongly agree). Full scores were created past reversing the scales and summing the responses with a higher score indicating a lower level of life satisfaction. Insomnia was measured by iv items of yes/no questions regarding slumber quality and summed into a scale score with a higher score indicating a lower slumber quality. Nosotros included indisposition in our latent variable 'psychological well-being' based on its association with negative resources (e.g., stress, mental disorder) and psychological well-being (Bastien, et al., 2001), as well as our gene analyses. These scales are often established and found to be reliable (east.g., Gallo & Rabins, 1999).

Demographic

Variables found to exist correlates of social relationships and health were as well included in the model as control variables: age, race, and educational activity at baseline in 2006. These information were drawn from the core interviews: age (50-64 = 0, 65-74 = ane, 75-84 = ii, 85 above = iii), race (white = 1, black = 2, others = 3), and highest caste of pedagogy (less than high schoolhouse = 0, some college = i, four-twelvemonth college = ii, more than higher = 3).

Analytic Procedures

Analyses were performed using structural equation modeling (SEM) in Amos (Version 20; SPSS, Chicago; Arbuckle, 2006). A ii-step procedure tested the theoretically-based relationships amid the four latent variables (i.east., social relationships, leisure activities, concrete health, and psychological well-being).

First, in examining the hypothesized mediating effects of leisure activity in the link betwixt social relationships and health, we used Baron and Kenny's (1986) four condition test: (a) the independent variable 'social relationships' must affect the mediator 'leisure activities'; (b) the contained variable 'social relationships' must touch on the dependent variables 'psychological well-being' and 'physical health' without the mediator 'leisure activities'; (c) the mediator 'leisure activities' must affect the dependent variables of 'psychological well-existence' and 'physical wellness'; and the independent variable 'social relationships' affects the dependent variables 'psychological well-being' and 'concrete health' via the mediator 'leisure activities'; and (d) one time the previously-stated weather all concord every bit expected, the effect of the independent variable 'social relationships' on the dependent variables 'psychological well-being' and 'physical health' must be significantly smaller in the third condition than in the 2nd. Additionally, the Sobel test is recommended to test the significance of the change in the coefficient in the fourth status (Hsu, et al., 2010). The mediating role of leisure activities is supported if all four conditions are satisfied.

Second, SEM was used to test our conceptual model: (a) to examine the mediating effect of leisure activities in path models; and (b) to evaluate the tested conceptual model (Figure one). Noting that the arbitration SEM analysis was developed to examine if the event of ane variable (due east.g., social relationships) on another (e.g., physical health and psychological well-being) is mediated past an intermediate variable (e.g., leisure activities), information technology is "inherently noncausal" (Bollen & Pearl, 2013, p.1). Furthermore, because the purpose of SEM is to examine relationships between variables and to clarify relationships between latent variables (Stoelting, 2002), its focus is on understanding this mechanism rather than establishing causal relationships (Stavola & Daniel, 2012). The concluding structural model was constructed with a directional path leading from the latent independent variable (social relationships in 2010) impacting the mediator (leisure activities in 2010), in plough impacting the latent dependent variables (psychological well-existence and physical health in 2010). Additionally, latent variables measured in 2006 (psychological well-beingness, and physical health) were included as control variables, which help to avoid potential biases that participants' previous health conditions may pose to their current wellness conditions. Model fit was evaluated with three goodness-of-fit indices: the comparative fit alphabetize (CFI; Bentler, 1990), the Tucker-Lewis index (TLI; Tucker & Lewis, 1973), and the root-mean-foursquare fault of approximation (RMSEA; Steiger, 1990). Minimum TLIs and CFIs of .90 were required for model credence, and values of .95 or greater were regarded as an indication of good model fit. RMSEAs of less than .06 were indicators of a good-fitting model (Hu & Bentler, 1998).

Results

Descriptive Statistics

As shown in Table 3, nearly all variables are significantly correlated with each other, and in the expected management. Physical wellness (BMI, self-reported wellness, the number of comorbidities) and psychological well-beingness (CES-D, insomnia, life satisfaction) were coded then that the larger the value, the lower the level of concrete health and psychological well-being. Therefore, for instance, the negative correlation between leisure mental activities and CES-D tin exist interpreted as if individuals increase their frequency of engaging in mental leisure activities, their levels of depressive symptoms subtract or, in dissimilarity, if individuals report lower levels of depressive symptoms, they may appoint in more mental leisure activities.

Tabular array 3

Correlation Coefficients of the Study Variables

Variables	1	2	iii	iv	5	6	seven	8	9	10	11	12
1. Social support
ii. Social strain	.21**
3. Mental activity	.07**	.03
4. Social activity	.09**	−.06**	.29**
5. Productive activeness	.thirteen**	−.07**	.31**	.28**
half dozen. Physical activity	.xiii**	.02	.34**	.xxx**	.27**
vii. CES-D	−.x**	−.17**	−.17**	−.09**	−.03	−.24**
8. Insomnia	−.07**	−.xiii**	−.04*	−.05**	.03	−.12**	.42**
9. Life satisfaction	−.22**	−.20**	−.xiv**	−.08**	−.08**	−.20**	.32**	.18**
10. BMI	−.05**	−.10**	−.01	.02	.03	−.15**	.04*	.05**	.08**
11. Self-reported health	−.12**	−.eleven**	−.25**	−.17**	−.16**	−.16**	.37**	.29**	.33**	.15**
12. Comorbidities	−.05**	−.033	−.15**	−.07**	−.10**	−.24**	.16**	.14**	.15**	.19**	.42**
Mean	iii.x	iii.38	iii.92	ii.49	2.81	4.07	1.07	vi.62	2.37	2.12	2.72	1.46
Standard Deviation	.59	.53	.96	1.04	.98	1.35	1.65	1.97	.87	.84	i.03	1.12

Path Models for Mediating the Consequence of Leisure

According to Businesswoman and Kenny's (1986), the kickoff three conditions were met with significant path coefficients betwixt social relationships, leisure activities, and psychological and physical wellness (Table 4). For the fourth condition, the Sobel test indicated that changes in the coefficient in one case the mediator was introduced were meaning for psychological well-being (t= −two.410, p<.05) and concrete health (t= −ii.993, p<.001). Therefore, our analyses indicated that leisure activity partly mediated the relationships between social relationships, psychological well-beingness, and physical wellness.

Table iv

Modified Path Model and Test of the Mediating Effect

Path	Standardized β (S.E.)
Beginning status
Social relationships → Leisure activities	.182 (.023)
Second condition
Social relationships → Psychological well-being	−.598 (.103)
Social relationships → Physical wellness	−3.795 (.407)
Third condition
Social relationships → Psychological well-existence	−.488(.082)
Social relationships → Physical health	−3.113(.349)
Social relationships → Leisure activities	−.785 (.230)
Leisure activities → Psychological well-existence	−.137 (.022)
Leisure activities → Physical health	−.252 (.074)

Note: All paths significant at the p < .05 level.

SEM Evaluation of the Tested Conceptual Model

The final model (Figure 2) represented a adept fit for the data: χ² (148, N=2965) = 1210.774, p <.001, CFI = .937, TLI = .919, RMSEA = .049. As illustrated in Figure 2, there were meaning direct effects between (a) social relationships and leisure activities; (b) social relationships and psychological well-being; (c) social relationships and concrete wellness; (d) leisure activities and psychological well-being; and (e) leisure activities and physical health, decision-making on education, race, psychological well-beingness, and physical health in 2006. As posited, social relationships predicted psychological well-being and concrete wellness, and leisure activity partially mediated these relationships. More specifically, the levels of contribution from social support (standardized β = 1.000) and social strain (standardized β = 1.194) to the latent variable 'social relationships' were like to each other. While psychological well-existence was positively affected by social relationships and leisure activities more than was physical health, the coefficient for physical health changed the nigh when leisure activities were added every bit a mediator to this model. Furthermore, physical leisure activities (standardized β = 1.541) contributed the most while productive leisure activities (standardized β = .454) contributed least to the latent variable 'leisure activities.' The outcome of CES-D (standardized β = three.117) in 'psychological well-being' and self-rated wellness (standardized β = 5.675) in 'concrete wellness' were the ii most impacted outcome variables.

Final master effects model in the current study. All paths pregnant at the p < .05 level.

Annotation: Decision-making for education, race, concrete wellness and psychological well-beingness in 2006.

Discussion and Conclusions

The results of this study confirmed our hypothesis that the links between social relationships and physical health or psychological well-beingness were enhanced in the presence of leisure activities every bit a mediator, supporting a principal effect model (Cohen & Wills, 1985), where adults with higher quality social relationships may exist motivated to appoint in health-promoting behaviors such every bit leisure activity and, in plough, reap more health benefits. Their social networks may value and so encourage participation in leisure activities every bit a vehicle to maintain health (e.g., Coleman & Iso-Ahola, 1993). Additionally, the physical type of leisure activity contributed the greatest effect to the latent variable 'leisure activity.' The contribution of physical leisure activities may be most important for improving health when emotional or psychological needs accept been satisfied past the high quality of older adults' social relationships.

The results that leisure activities, especially physical ones, mediate the link betwixt social relationships and wellness replicates findings in previous studies which examined the main upshot model in leisure and health (e.g., Cohen-Mansfield, et al., 2009). Differences in specific criteria used to define leisure could contribute to the differences between the present and previous studies: Many researchers only examined "leisure-time physical action" in their models (eastward.1000., Bassett & Martin, 2011), whereas the nowadays study included four types of leisure activities. Indeed, physical leisure activeness is most beneficial among the four types of leisure activities, while mental leisure activeness also significantly correlated to wellness in our model. Since older adults may be involved in fewer and fewer concrete activities during aging process, mental activities may exist an alternative to improving health.

Although the positive event of leisure activeness on psychological well-being was greater than on physical wellness in the overall model, the coefficient change in physical health was greater when leisure action was added equally a mediator. Physical reject is a common and largely progressive outcome of the aging process (Chen & Feeley, 2013), whereas psychological well-being may vary past person. Noting that self-reported physical health measurement contributes about to the latent variable 'physical wellness' in the presented model, there may accept been bias because information technology is a self-reported measurement. Individuals may report their physical health as better than it actually was.

The results provided boosted evidence that leisure action is a health-promoting behavior that may mediate the link between social relationships and health, which accept both research and practical implications. First, leisure provides a broader concept of health-promoting behaviors, including more than physical activity. In a meta-analysis study reviewing articles relating to the NIH Cognitive and Emotional Health Projection, Hendrie and colleagues (2006) indicated that physical activity may protect against cognitive decline in older adults, but did not discuss other health-promoting behaviors. Our findings also suggested that other types of leisure activities may provide insightful information when examining the link between social relationships and health outcomes. 2nd, engaging in leisure is a healthy lifestyle that nigh prevention research and interventions are designed to promote (east.g., Hutchinson & Nimrod, 2012). Leisure activity is a relatively inexpensive and easy accessible for older adults' health comeback. Leisure activity may as well help explain the impact of positive social relationships on physical health improvements in older adults. Intervention programmers may create environments to develop friendships in older participants as a first step. Adding regular leisure activities, especially physical types of leisure activities (e.thou., walking), into the intervention could be the second step to broaden the positive event of social relationships on concrete wellness. Finally, equally a health-promoting behavior, leisure, may improve long-term psychological well-being and concrete health in older adults, such equally improvements of physiological and cardiovascular fitness (Iwasaki, et al., 2005). The present study not only provides evidence as to how older adults can improve their health, but also how researchers can inform healthcare delivery. For example, interventions for older adults—such as support for clinical assessments and handling services—may be developed whereby leisure activities are defined every bit "behavioral medicine" aimed at improving older adults' health. The findings may also help to place which types of leisure activities may provide the greatest wellness benefit as part of those clinical assessments or handling services. Finally, future intervention researchers may examine the effect of unlike physical types of leisure activities on the link between social relationships and health comeback for older adults.

Despite the big number of participants (Northward =ii,965) and the variety of measurements involved in, the design of the present report was non without limitations, First, although we controlled for age, race, education, and health status at baseline, other unmeasured factors, such as gender and marital condition, may have influenced the results. Given that the power of personal characteristics in wellness has been widely discussed in, hereafter research is necessary to explore differences beyond population subgroups based on a life-bridge developmental perspective in order to capeesh the ability of early-life, ascribed and achieved social condition (Alwin & Wray, 2005). 2d, the psychosocial data used in the current study were merely from the offset moving ridge in 2006, the year the HRS started collecting data on leisure activity and life satisfaction. Although data in 2006 were included equally controls, those in this tested model were cantankerous-sectional. Causal relationships cannot be examined in a cross-sectional information since SEM only tests directionality in longitudinal data (Stoelting, 2002). Future inquiry could examine a longitudinal alter and causality in the current model once the HRS launches next wave of psychosocial data in 2014.

The present study underscores the contributions of leisure in the link between social relationships and health among older adults based on the main upshot model. An improved understanding of the mediating upshot of leisure activities in such a link is of import for improvement and maintenance of health among the older population, which can be applied to effective intervention development to help older adults during aging process. Leisure is a much broader concept than physical activity, which equally shown in the present study other types of non-physical leisure activeness mediated the link between social relationships and wellness as well. The findings have demonstrated the complex relationships between social relationships and health, and highlighted the power of leisure activities for developing time to come wellness policies and/or clinical interventions for older adults in the health promotion area.

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