Abstract
Background
Investigating the relationship between cultural leisure activities participation and subjective well-being (SWB) in older adults not only deepens our understanding of their cultural needs and leisure activities participation but also provides a scientific basis for enhancing their SWB and promoting active aging.
Methods
Data from the 2021 China General Social Survey (CGSS) was used in this study. An Ordinary Least Squares (OLS) regression model was employed to examine how participation in cultural leisure activities influences the subjective well-being of older adults.
Results
The study revealed that cultural leisure activities participation was significantly positively associated with SWB among older adults. This conclusion remained robust even after addressing endogeneity concerns using the propensity score matching method. Heterogeneity analysis indicated that the associations between cultural leisure activities participation and SWB were most pronounced among older adults in rural areas, with lower levels of education, and living in western regions. Mediation analysis further demonstrated that cultural leisure activities participation enhanced SWB by improving self-reported health and mental health.
Conclusions
It was recommended that relevant authorities encourage older adults to participate in cultural leisure activities through favorable policies and improved cultural facilities, enhance the age-friendliness of cultural services, increase cultural investments in rural areas, and promote social engagement and community connections to boost the SWB of older adults.
Keywords: Cultural leisure activities participation, Subjective well-being, Self-reported health, Mental health, Older adults
Introduction
The world’s population has been aging rapidly. As the country with the largest population of older adults, China's aging rate has surpassed the global average [1]. It is estimated that China's older adults aged 60 and above will exceed 358 million by the end of 2030 [2], presenting substantial challenges to healthcare and public service provision. As early as 1999, the World Health Organization (WHO) proposed the concept of "active aging," viewing aging as a positive and dynamic process that emphasizes the importance of a healthy lifestyle and contributions to society by the older adults.
Subjective well-being (SWB) refers to an individual's overall satisfaction and happiness with their life. It is a subjective evaluation that reflects an individual's perception and assessment of their life state, emotional experiences, and quality of life. From an individual perspective, happiness is a fundamental rational pursuit, representing the meaning and purpose of life. The report of the 19th National Congress of the Communist Party of China explicitly states that improving people's SWB is the ultimate goal of development [3]. High levels of SWB can help older adults achieve active aging, thereby enhancing their physical and mental health and quality of life.
Leisure activity mainly consisted of physical activity and cultural activity [4]. Cultural activities mainly included attending cultural events as well as participating in activities such as dancing, sports, music-making, or drama [5]. Prior studies found a correlation between cultural leisure activities participation and SWB, with some scholars asserting that cultural leisure activities participation was significantly positively correlated with SWB among Chinese older adults [6]. Mence [7] found that daily participation in leisure activities was positively associated with happiness and functional ability among older adults in South Korea. A study in Canada provides evidence of the importance of engaging in leisure activities within social contexts for the well-being of older adults [8]. Drawing on the 2020 Health and Retirement Study Core Early Release, Kim et al. (2022) [9] reported that leisure-time physical activity and sedentary leisure activities both have a significant positive correlation with happiness among older adults in the U.S.
While the relationship between cultural leisure activity participation and subjective well-being (SWB) has been widely studied in the general population, limited attention has been given to older adults. This study utilized the China General Social Survey (CGSS 2021) and focused on the older adults. It incorporated the mediating variables of health status to explore the relationship between cultural leisure activities participation and SWB in the older adults. Moreover, we conducted a heterogeneity analysis to further elucidate the association between cultural leisure activities and SWB across different population groups. Given the unique dual economic and social structure in China, substantial disparities exist between urban and rural areas in terms of cultural infrastructure and accessibility. Urban older adults have greater access to diverse leisure activities such as attending theater performances, concerts, art exhibitions, and visiting museums, whereas rural older adults tend to engage in traditional and accessible cultural activities, such as watching TV, playing card games (e.g., mahjong or poker), participating in square dancing, and consuming digital leisure content (e.g., short videos and live streaming platforms). These structural differences may lead to varying patterns of cultural leisure participation and their differential impacts on SWB, highlighting the importance of investigating potential heterogeneity in these associations.
Literature review
The Impact of cultural leisure activities participation on the SWB of the older adults
Due to differences in interests, values, and education levels, the demand for cultural leisure activities participation among people was characterized by multiple layers and dimensions [10]. Scott and Willits (1998) categorized cultural leisure activities participation activities into four types: social activities, artistic activities, intellectual activities, and physical activities [11]. Lloyd and Auld (2002) [12] further divided leisure activities into six categories: mass media, social activities, outdoor activities, sports activities, cultural activities, and relaxation activities.
Numerous scholars confirmed a significant positive correlation between cultural leisure activities participation and the SWB of the older adults. Sener et al. (2007) [13] emphasized the importance of active leisure participation for the positive psychological health of the older adults. Leisure activities participation was crucial for the older adults as it helped them develop a positive outlook on life and avoid stress (Stathi et al., 2002) [14]. Menec et al. (1997) [15] uncovered that participation in cultural leisure activities, such as visiting friends and relatives, exercising, watching television, and listening to the radio, significantly improved the SWB of older adults. Similarly, Toepoel (2011) [16] unveiled that participating in either lowbrow cultural activities alone or in both highbrow and lowbrow cultural activities was positively related to life satisfaction among older adults in the Netherlands. Although there is no consensus in the literature regarding the classification of leisure activities, researchers generally agreed that leisure activities showed a positive relationship with SWB (Iwasaki, 2007; Rodríguez et al., 2008) [17, 18]. Based on the existing research findings, this paper hypothesizes:
Hypothesis H1: Cultural leisure activities participation has a significant positive impact on the SWB of the older adults.
The mediating role of health status
According to the United Nations, health was a state of complete physical, mental, and social well-being [19]. Maintaining the physical and mental health of the older adults was crucial for enhancing their quality of life [20] and SWB.
First, cultural leisure activities participation showed a positive correlation with both the psychological and physiological health of older adults (Pressman et al., 2009; Chang et al., 2014) [21, 22]. Menec (2003) [23] found that social and productive activities contributed to better physical health, while solitary leisure activities, such as reading, enhanced the psychological health of the older adults. Nimrod (2007) [24] also indicated that leisure participation was an important factor influencing life satisfaction among Jewish retirees aged 50 and above.
Second, health status of the older adults was significantly positively correlated with their SWB. Soósová et al. (2021) [25] discovered a significant positive relationship between psychological health and SWB among older individuals. Based on these findings, the following hypothesis is proposed:
Hypothesis H2: Self-reported health mediates the relationship between cultural leisure activities participation and the SWB of the older adults.
Hypothesis H3: Mental health mediates the relationship between cultural leisure activities participation and the SWB of the older adults.
Methods
Data sources
The China General Social Survey (CGSS), launched in 2003, is the earliest nationwide, comprehensive, and continuous academic survey project in China. One of its major strengths lies in its large-scale, nationally representative sample, which systematically collects information at the societal, community, family, and individual levels. However, a notable limitation is that the CGSS is not a longitudinal survey but rather a repeated cross-sectional survey, which restricts the ability to track the same individuals over time.
This empirical study utilizes the publicly available data from the China General Social Survey (CGSS 2021) provided by Renmin University of China. The database contains a total of 8,148 valid questionnaires. The sample selected for this study consists of individuals aged 60 and above. After excluding missing and invalid variables, 1,840 valid samples were obtained. Data cleaning and statistical analysis were conducted using R software and STATA 16.0.
Variables and measurements
Dependent variable
In the CGSS 2021 survey on SWB, the questionnaire consists of 20 items. Each item is rated on a scale from 1 to 6 (1 = Strongly Disagree; 2 = Disagree; 3 = Slightly Disagree; 4 = Slightly Agree; 5 = Agree; 6 = Strongly Agree). The 20 items are summed to create a proxy measure for SWB, with a range from 43 to 120. The Cronbach's α for the SWB scale is 0.76, indicating a good level of internal consistency.
Using principal component analysis with varimax rotation, ten common factors were forcibly extracted from the 20 items of the Short Form of the Chinese Urban Residents’ Subjective Well-being Scale (Xing, 2003) [26]. The exploratory factor analysis results were relatively satisfactory. The cumulative variance contribution of these ten factors was 67.01%. These ten factors correspond to the ten dimensions of the scale: goal and value experience, physical health experience, contentment and abundance experience, psychological health experience, growth and progress experience, emotional balance experience, social confidence experience, interpersonal relationship experience, self-acceptance experience, and family atmosphere experience.
Independent variable
The independent variable in this study is cultural leisure activities participation. It is measured using the question, “Over the past year, how often have you engaged in the following activities during your leisure time?” The selected activities include watching movies, watching television or DVDs, reading books, newspapers, or magazines, participating in cultural events (e.g., attending concerts, performances, and exhibitions), listening to music at home, watching live sports events, and browsing the Internet. Responses are categorized into five frequency levels: "Never," "A few times a year or less," "A few times a month," "A few times a week," and "Every day," with values assigned from 1 to 5.
Mediating variables
Health status was assessed across two dimensions: mental health and self-rated health. Following the methodology of Jiang and Chen (2021) [27], mental health was measured by the item: 'In the past four weeks, how often have you felt depressed or downhearted?', while self-rated health was evaluated with the item: 'What do you think is your current physical health condition?'.
Control variables
The following variables were included as covariates in this study: age, gender (male, female), marital status (none, married), residence (rural, urban), educational attainment, employment status, family income (logarithmic scale), number of houses, number of chronic diseases, number of children, insurance coverage, subjective social class (1 = Very low, 2 = Low, 3 = Middle, 4 = High, 5 = Very high), social equity (1 = Completely unfair, 2 = Somewhat unfair, 3 = Neither fair nor unfair, 4 = Somewhat fair, 5 = Completely fair), and region (Eastern, Central, Western).
Results
Basic characteristics of the respondents
Table 1 presents the descriptive statistics of the variables. Overall, the results suggest that older adults report a generally high level of SWB but relatively low levels of cultural leisure activities participation. Regarding control variables, the sample shows a balanced gender distribution, with most participants being married and residing in rural areas. Most older adults are unemployed, and many possess relatively low levels of education.
Table 1.
Basic characteristics of participants a(N = 1840)
| Variable | Variable definition | Total sample |
|---|---|---|
| SWBb | Range: 46–119 | 88.43 ± 9.93 |
| Cultural leisure activities participationb | Range: 7–35 | 14.83 ± 4.38 |
| Self-reported healthb | 1 = Very Unhealthy,2 = Unhealthy, 3 = Neutral,4 = Healthy,5 = Very Healthy | 3.15 ± 1.10 |
| Mental healthb | 1 = Always, 2 = Often, 3 = Sometimes,4 = Seldom, 5 = Never | 3.93 ± 1.13 |
| Ageb | Range: 60–92 | 69.58 ± 6.44 |
| Gender (%) | Male | 922(50.1) |
| Female | 918(49.9) | |
| Marital Status (%) | None | 490(26.6) |
| Married | 1350(73.4) | |
| Residence (%) | Rural | 1033(56.1) |
| Urban | 807(43.9) | |
| Education Level (%) | Primary school or below | 900(48.9) |
| Junior/Senior high school | 840(45.7) | |
| College or above | 100(5.4) | |
| Employment Status (%) | Unemployed | 1351(73.4) |
| Employed | 489(26.6) | |
| Family incomeb | Continuous variable (logarithmic) | 11.03 ± 3.40 |
| Number of housesb | Range: 0–5 | 1.11 ± 0.38 |
| Number of Chronic Diseasesb | Range: 0–7 | 1.27 ± 0.90 |
| Number of children b | Range: 0–12 | 2.20 ± 1.22 |
| Insurance (%) | None | 54(2.9) |
| Yes | 1786(97.1) | |
| Subjective social class b | 1 = Very Low, 2 = Low, 3 = Middle, 4 = High, 5 = Very High | 2.50 ± 0.99 |
| Social equity b | 1 = Completely Unfair, 2 = Somewhat Unfair, 3 = Neither Fair nor Unfair, 4 = Somewhat Fair, 5 = Completely Fair | 3.61 ± 0.97 |
| Region (%) | Eastern | 830(45.1) |
| Central | 547(29.7) | |
| Western | 463(25.2) |
aData are presented as counts (percentage) unless otherwise indicated
bFor continuous variables, the mean and standard deviation (SD) are reported
Benchmark regression
As illustrated in Table 2, the regression results from Model 1 reveal a significant positive correlation between cultural leisure activities participation and the SWB of the older adults. In Model 2, when incorporating control variables such as age, gender, marital status, household registration, education level, economic status, number of properties, employment status, number of chronic diseases, social class, and perceived social fairness, cultural leisure activities participation remains significantly positively correlated with the SWB of the older adults. Model 3 further includes regional variables, and the positive association between cultural leisure activities participation and the SWB of the older adults remains robust. The regression coefficients in Models 2 and 3 are 0.245 and 0.214, respectively, both significant at the 0.001 level. This indicates that the level of cultural leisure activities participation among the older adults is significantly positively correlated with their SWB, thus validating Hypothesis H1. According to Model 3, individuals who are female, married, urban residents, or living in the central and eastern regions, and those with higher economic status, social class, and sense of social equity, exhibit stronger SWB. Conversely, variables such as age, education level, employment status, and number of chronic diseases show no significant relationship with the older adults' SWB.
Table 2.
Relationship between cultural leisure activities participation and SWB among Chinese older adults (N = 1840)
| Variable | Model 1 | Model 2 | Model 3 |
|---|---|---|---|
| Cultural leisure activities | 0.450*** (0.052) | 0.245*** (0.058) | 0.214*** (0.058) |
| Age | 0.022 (0.039) | 0.006 (0.039) | |
| Gender (Ref. = Male) | −1.493*** (0.461) | −1.662*** (0.459) | |
| Marital Status (Ref. = None) | 1.233** (0.514) | 1.102** (0.512) | |
| Residence (Ref. = Rural) | 1.822*** (0.554) | 1.526*** (0.556) | |
|
Education Level (Ref. = Primary school or below) |
0.121 (0.452) | 0.037 (0.450) | |
| Employment Status (Ref. = Unemployed) | 0.163 (0.552) | 0.412 (0.551) | |
| Family income | 0.205*** (0.065) | 0.221*** (0.065) | |
| Number of houses | 1.042* (0.582) | 0.854 (0.579) | |
| Number of Chronic Diseases | −0.314 (0.244) | −0.308 (0.243) | |
| Number of children | −0.142 (0.200) | 0.044 (0.203) | |
| Insurance (Ref. = None) | −0.147 (1.296) | 0.462 (1.294) | |
| Subjective social class | 1.898*** (0.228) | 1.864*** (0.227) | |
| Social equity | 1.171*** (0.230) | 1.237*** (0.229) | |
| Eastern | 2.893*** (0.580) | ||
| Central | 1.507** (0.590) | ||
| R2 | 0.039 | 0.127 | 0.139 |
*p < 0.05
**p < 0.01
***p < 0.001
Results of robustness analysis
To address the endogeneity issues arising from sample selection bias, this study employs the Propensity Score Matching (PSM) method to group and match the older adults. Initially, the "cultural leisure activities participation" variable is dichotomized. Based on the distribution of cultural leisure activities participation scores in the sample, individuals scoring between 0 and 3 are classified into the "low-frequency cultural leisure activities participation" group, serving as the control group, while those scoring between 4 and 7 are classified into the "high-frequency cultural leisure activities participation" group, serving as the treatment group. To perform the propensity score matching, a balance test is first conducted to ensure that, after matching, there are no significant differences in the explanatory variables between the two groups, aside from the core explanatory variable.
This study employs the radius matching method to align the treatment and control groups. As shown in Table 3, post-matching, the standard deviations for all variables are less than 6%. Furthermore, no significant differences are observed between the treatment and control groups across various indicators. This indicates that matching has effectively mitigated the potential selection bias inherent in the baseline model, resulting in a more balanced experimental and control group, thereby meeting the fundamental requirements for a randomized experiment.
Table 3.
Results of balance test
| Variable | Mean | Deviation rate (%) | t-test | |||
|---|---|---|---|---|---|---|
| Treatment group | Control group | t-value | p >|t| | |||
| Age | Unmatched | 68.782 | 69.950 | −18.300 | −3.640 | 0.001 |
| Matched | 68.818 | 68.474 | 5.400 | 0.930 | 0.354 | |
| Gender | Unmatched | 0.466 | 0.514 | −9.700 | −1.940 | 0.053 |
| Matched | 0.466 | 0.455 | 2.200 | 0.370 | 0.708 | |
| Marital Status | Unmatched | 0.799 | 0.703 | 22.400 | 4.380 | 0.001 |
| Matched | 0.797 | 0.796 | 0.400 | 0.060 | 0.904 | |
| Residence | Unmatched | 0.653 | 0.338 | 66.400 | 13.300 | 0.001 |
| Matched | 0.649 | 0.648 | 0.400 | 0.070 | 0.946 | |
| Education Level | Unmatched | 1.883 | 1.416 | 82.500 | 16.830 | 0.001 |
| Matched | 1.871 | 1.870 | 0.200 | 0.030 | 0.979 | |
| Employment Status | Unmatched | 0.201 | 0.296 | −22.300 | −4.350 | 0.001 |
| Matched | 0.203 | 0.194 | 2.000 | 0.360 | 0.718 | |
| Family income | Unmatched | 11.269 | 10.915 | 10.800 | 2.080 | 0.037 |
| Matched | 11.258 | 11.317 | −1.800 | −0.330 | 0.740 | |
| Number of houses | Unmatched | 1.139 | 1.099 | 10.500 | 2.150 | 0.032 |
| Matched | 1.134 | 1.135 | −0.100 | −0.020 | 0.986 | |
| Number of Chronic Diseases | Unmatched | 1.255 | 1.276 | −2.400 | −0.470 | 0.636 |
| Matched | 1.249 | 1.228 | 2.400 | 0.420 | 0.674 | |
| Number of children | Unmatched | 1.951 | 2.324 | −31.900 | −6.170 | 0.001 |
| Matched | 1.954 | 1.933 | 1.800 | 0.320 | 0.704 | |
| Insurance | Unmatched | 0.986 | 0.963 | 14.800 | 2.750 | 0.001 |
| Matched | 0.986 | 0.986 | 0.200 | 0.050 | 0.960 | |
| Subjective social class | Unmatched | 2.660 | 2.426 | 24.100 | 4.740 | 0.001 |
| Matched | 2.646 | 2.640 | 0.700 | 0.110 | 0.908 | |
| Social equity | Unmatched | 3.600 | 3.612 | −1.200 | −0.240 | 0.813 |
| Matched | 3.596 | 3.566 | 3.300 | 0.570 | 0.571 | |
The results presented in the table are derived from the radius matching method
To enhance the robustness of the results, this study employs four methods—radius matching, kernel matching, nearest-neighbor matching, and Mahalanobis matching—to estimate the average treatment effect on the treated (ATT) of cultural leisure activities participation on the SWB of the older adults. Table 4 reveals that, prior to matching, cultural leisure activities participation was associated with an approximately 5.76% increase in the SWB of the older adults. However, after matching, cultural leisure activities participation continues to exert a statistically significant positive effect on the SWB of the older adults. The regression coefficients obtained from all four matching methods are consistent in both significance and direction, indicating that cultural leisure activities participation has a uniform and stable effect on enhancing the SWB of older adults.
Table 4.
The average treatment effect of cultural leisure activities participation on the SWB
| Matching method | Treatment group (1) | Control group (2) | Att value | Standard deviation | t-value |
|---|---|---|---|---|---|
| Before the match ATT | 90.361 | 87.528 | 2.833 | 0.492 | 5.76*** |
| After the match ATT | - | - | - | - | - |
| Radius matching | 90.273 | 89.096 | 1.176 | 0.597 | 1.97* |
| Kernel matching | 90.273 | 89.164 | 1.108 | 0.568 | 1.96* |
| Caliper nearest neighbor matching | 90.265 | 89.081 | 1.183 | 0.639 | 1.87* |
| Mahalanobis matching | 90.360 | 89.150 | 1.210 | 0.614 | 1.97* |
*p < 0.05
**p < 0.01
***p < 0.001
Heterogeneity analysis
This study conducts a heterogeneity analysis along three dimensions: residence, educational level, and regional, to elucidate how cultural leisure activities participation influences the SWB of individuals across different subgroups. The results of the individual heterogeneity analysis are detailed in Table 5.
Table 5.
Heterogeneity analysis of the impact of cultural leisure activities participation on the SWB
| Variable | Residence | Education Level | Region | |||||
|---|---|---|---|---|---|---|---|---|
| Rural | Urban | Primary school or below | Junior/Senior high school | College or above | Eastern | Central | Western | |
| Cultural leisure activities participation | 0.232** (0.087) | 0.202** (0.076) | 0.258** (0.093) | 0.185* (0.079) | 0.472 (0.251) | 0.182* (0.079) | 0.223* (0.111) | 0.330* (0.129) |
| Control variable | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes |
 |
1033 | 807 | 900 | 840 | 100 | 830 | 547 | 463 |
 |
0.112 | 0.114 | 0.129 | 0.114 | 0.080 | 0.151 | 0.082 | 0.167 |
*p < 0.05
**p < 0.01
***p < 0.001
Although the formal moderation tests did not indicate statistically significant differences between subgroups, the data suggest a trend that the association between participation in cultural leisure activities and SWB may be stronger among older adults living in rural areas (0.232, p < 0.01) compared to those in urban areas (0.202, p < 0.01). Similarly, a trend was observed suggesting a stronger association among older adults with primary school education or below (0.258, p < 0.01) compared to those with junior/senior high school education (0.185, p < 0.05). Across regions, the coefficients indicate a possible gradient, with the largest association observed in the western region (0.330, p < 0.05), followed by the central (0.223, p < 0.05) and eastern regions (0.182, p < 0.05). These findings suggest potential heterogeneity in the effect, though the differences should be interpreted with caution given the lack of statistical significance in the moderation tests.
Mechanism analysis
According to Table 6, a multiple mediation model was employed with both mediators included simultaneously, utilizing the bias-corrected Bootstrapping method with 2000 bootstrap samples. The total indirect effect was 0.164 (95% CI = [0.059, 0.273]).
Table 6.
Estimation results of indirect effects
| Path | Effect (Boot Se) | CI = 95% | |
|---|---|---|---|
| LLCI | ULCI | ||
| TOTAL | 0.164** (0.055) | 0.059 | 0.273 |
| Direct effect | 0.090 (0.051) | −0.008 | 0.190 |
| Indirect effect | |||
| Self-reported health | 0.041* (0.014) | 0.013 | 0.069 |
| Mental health | 0.033* (0.014) | 0.008 | 0.061 |
Boot SE Bootstrap standard error, LLCI Lower limit confidence interval, ULCI Upper limit confidence interval
*p < 0.05
**p < 0.01
Specifically, the indirect effect through self-reported health was 0.041 (95% CI = [0.013, 0.069]), and the indirect effect through mental health was 0.033 (95% CI = [0.008, 0.061]). The 95% confidence intervals for both mediators do not include zero, indicating that self-reported health and mental health significantly mediate the relationship between cultural leisure activities participation and SWB. Hypotheses H2 and H3 are supported.
Discussion
This study utilizes data from the CGSS 2021 to explore the relationship between participation in cultural leisure activities and subjective well-being (SWB) among Chinese older adults, and draws the following conclusions.
First, significant positive correlations were observed between participation in cultural leisure activities and subjective well-being (SWB) among older adults, aligning with previous research [28, 29]. Cultural leisure activities can enhance physical activity, provide opportunities for social interaction, reduce stress, and foster emotional regulation, thereby improving SWB in older adults.
Second, heterogeneity analysis suggested trends indicating that the associations may be more pronounced among those in rural areas, with lower educational attainment, and residing in western regions. However, formal moderation tests did not show statistically significant differences, so these subgroup patterns should be interpreted with caution. This trend may be attributed to the uneven distribution of cultural resources in the urban–rural dichotomy. Wu et al. (2022) [30] demonstrated that cultural consumption in China shows urban–rural and regional differences, with urban residents consistently exhibiting higher total and relative levels than rural residents. For rural older adults, cultural leisure activities participation can be a relatively rare and valuable experience, thus enhancing its effect. Compared to high-education older adults, cultural leisure activities participation has a more pronounced positive impact on low-education older adults. This is partly because high-education older adults may have encountered similar cultural experiences before,which reduces the novelty effect and weakens their impact on SWB. Moreover, the CGSS database primarily covers widely accessible, recreational cultural activities, with fewer high-demand or high-level cultural leisure activities participation types included. [31] Therefore, such lower-demand cultural leisure activities participation better meets the needs of lower-education older adults, whereas its impact on those with higher education levels is less pronounced. Regional differences also manifest in the impact of cultural leisure activities participation on SWB. Compared with the eastern region, the effect is stronger in the western and central regions, which is consistent with the findings of Peng ang Yang (2021) [32]. This may be due to the relative scarcity of cultural resources and facilities in these areas. In such areas, engaging in cultural leisure activities offers older adults meaningful novelty and well-being.
Third, self-reported health and mental health mediates the relationship between cultural leisure activities participation and the SWB of the older adults. Cultural leisure activities participation positively influences psychological and self-reported health by providing enjoyable experiences, promoting social interactions, and stimulating mental engagement (Everard et al., 2000; Liechty et al., 2017; Shah et al., 2017) [33–35]. As psychological and self-reported health improve, the older adults may experience greater SWB.
Based on the comprehensive research conclusions, this study offers the following policy recommendations to enhance the SWB of the older adults through cultural leisure activities participation in the context of active aging: First, the government and society should encourage older adults to engage in cultural leisure activities participation by offering discounts on cultural venue tickets and other incentives. Additionally, promoting digital cultural resources is essential. Platforms such as online libraries and cultural arts websites should be developed to provide older adults with convenient access to cultural leisure activities participation. Second, when planning cultural activities, particular attention should be given to the interests and needs of the older adults. It is crucial to offer cultural content that aligns with their preferences, such as classical concerts, traditional opera performances, and calligraphy courses, to increase their engagement and participation. Third, given the significant impact of cultural leisure activities participation on the SWB of older adults in rural areas, the government should intensify investment in cultural resources for these regions. This includes organizing a diverse range of cultural activities, such as traditional folk performances, literary events, art exhibitions, and craft workshops, to meet the varied needs of rural older adults. Additionally, improving and establishing cultural facilities in rural areas will provide older adults with accessible venues and resources, thereby supporting their active aging.
The present study has various strengths. This study utilized data from the Chinese General Social Survey (CGSS), which is the earliest nationwide, comprehensive, and continuous academic survey project in China. Moreover, our study incorporated health status as a mediating variable, which provides deeper insights into the underlying mechanisms through which cultural leisure activities influence SWB. In addition, while previous studies on Chinese residents’ subjective well-being have often relied on a single-item measure, our study utilized a validated 20-item SWB scale, which offers enhanced reliability and measurement precision.
However, it is important to acknowledge the limitations of our study. The study relies on cross-sectional rather than longitudinal data, which limits the ability to examine causal relationships or track changes in individuals’ WSB over time. In addition, it uses secondary data from the CGSS, meaning that some potentially important variables (such as personality traits, lifestyle preferences, and the balance of leisure time distribution) are not included. Future research could address these limitations by using longitudinal designs and collecting more comprehensive individual-level data to better understand the mechanisms linking cultural leisure participation and SWB among older adults.
Conclusion
This study confirms significant positive correlations of cultural leisure activities participation with subjective well-being (SWB) among older adults in China. The heterogeneous effects across rural areas, lower educational groups, and western regions should be cautioned noted for public health policy makers and future studies. The findings provide evidence that could help policymakers design, implement, and manage targeted interventions for successful aging promptly
The findings underscore the critical role of cultural leisure activities in promoting the subjective well-being (SWB) of older adults in China, considering its unique socio-cultural and regional contexts. This study deepens the understanding of the relationship between cultural leisure participation and SWB among Chinese older adults, offering practical insights for enhancing well-being in China’s rapidly aging population.
Authors’ contributions
Conceptualized the paper and designed the methodology, W.C.; data analysis, W.C. and R.J.; writing—original draft preparation, W.C.; writing—review and editing, W.C., C.Z., and Y.S.; All authors have read and agreed to the published version of the manuscript.
Funding
This research is funded by the Social Science Foundation ofHunan Province (23YBA055).
Data availability
Restrictions apply to the availability of these data. Data were obtained from the National Survey Research Center at the Renmin University of China and are available http://cgss. ruc.edu.cn/(accessed on 22 February 2024) with the permission of the National Survey Research Center at Renmin University of China.
Declarations
Ethics approval and consent to participate
Ethical approval was not required. This article does not contain any studies with human participants performed by any of the authors.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
Restrictions apply to the availability of these data. Data were obtained from the National Survey Research Center at the Renmin University of China and are available http://cgss. ruc.edu.cn/(accessed on 22 February 2024) with the permission of the National Survey Research Center at Renmin University of China.