Moderating Effects of Leisure Time Physical Activity on Curvilinear Relationships between Working Hours and Life Satisfaction in China

Chen, Nan; Kim, Chang Gyeong; Nan Chen; Chang Gyeong Kim

doi:10.15857/ksep.2025.00115

Exerc Sci > Volume 34(2); 2025 > Article

Chen and Kim: Moderating Effects of Leisure Time Physical Activity on Curvilinear Relationships between Working Hours and Life Satisfaction in China

Original Article

Exerc Sci.. 2025; 34(2): 159-169.

Published online: May 30, 2025

DOI: https://doi.org/10.15857/ksep.2025.00115

Moderating Effects of Leisure Time Physical Activity on Curvilinear Relationships between Working Hours and Life Satisfaction in China

Nan Chen PhD¹

, Chang Gyeong Kim PhD^2,

¹Department of Chinese Studies, Kosin University, Busan, Korea

²Department of Chinese Studies, Pukyong National University, Busan, Korea

Corresponding author: Chang Gyeong Kim Tel +82-51-629-5342 Fax +82-51-629-7051 E-mail cgkim@pknu.ac.kr

Received Mar 8, 2025 Revised May 1, 2025 Accepted May 7, 2025

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

PURPOSE

Previous research has documented the correlations among working hours, leisure-time physical activity (LTPA), and life satisfaction; however, the extent to which LTPA impacts the effect of working hours on life satisfaction has rarely been studied. The article focuses on this under-researched topic in the context of overworked adults from diverse demographic backgrounds in China.

METHODS

Data collected from 11,065 participants in the 2015 China Health and Nutrition Survey (CHNS) were analyzed. Playing sports and walking were included in statistical testing as two types of LTPA. Curvilinear hierarchical regression models were employed to assess the impact of weekly working hours on life satisfaction within different demographic groups. To confirm the moderation effect of LTPA on the curvilinear relationship between weekly working hours and life satisfaction, curvilinear moderation models were applied.

RESULTS

Curvilinear hierarchical regression revealed an inverse relationship between working hours and life satisfaction across gender and age demographics. The older generation demonstrated greater benefits from extended working hours, while female workers exhibited fewer benefits. Furthermore, the curvilinear relationship between working hours and life satisfaction was moderated by LTPA. The beneficial effects of LTPAs on overworked adults varied across age and gender groups. Specifically, engaging in walking activity during leisure time was associated with higher life satisfaction among younger adults who worked excessive hours.

CONCLUSIONS

The findings of this study highlight the significance of LTPA as a coping mechanism for job overload and enhancing life satisfaction. Based on these results, targeted well-being intervention programs can be developed for overworked adults across different demographic groups. When establishing workplace well-being policies, practitioners should consider the varied benefits that different forms of LTPAs offer to employees working excessive hours.

Keywords: Leisure time physical activity, Overwork, Life satisfaction, Nonlinear relationship, China

INTRODUCTION

Long working hours have been understood as constituting an occupational risk factor. Exposure to long working hours causes physical illness (e.g., ischemic heart disease or stroke) and mental difficulties [1,2]. In response to the stress induced by long working hours, overworked people may experience physiological reactions such as fatigue, burnout, and un-healthy lifestyles, and these changes may affect their life satisfaction [3]. Many countries in the world have defined standard working hours as 40 hours/week, and some countries have set the maximum number of weekly working hours at 48 hours [4]. Nevertheless, overworking remains a common phenomenon worldwide. In terms of the methods used to cope with work stress induced by overworking, researchers have found that leisure time physical activity (LTPA) contributes to personal well-being and that leisure participation can operate as a buffer against negative job demands and thus predict better mental or physical health [5,6].

Among working adults worldwide, those in China have some of the longest working hours and the least leisure time [7]. According to the Chinese Leisure and Wellbeing Index, 48.6% of respondents had an average of less than 10 hours of leisure time per week in 2018, and 73.6% of the respondents reported that their discretionary time was insufficient in 2020 [8,9]. According to the 2016 China Labor Dynamics Survey (CLDS), working adults averaged more than 44 hours of work per week, and 43% reported working over 50 hours [10]. Moreover, a Chinese time use survey reported that women spent more time performing paid and unpaid work but had less leisure time than men [11]. Compared with people who do not have much time to participate in leisure activities, people who have time to participate in leisure activities are more likely to recover from the pressures caused by overworking [12]. Moreover, research found that playing sports significantly impacted the effect of perceived stress on subjective well-being among young and middle-aged working adults [13]. Thus, reducing the negative effect of overworking by promoting LTPA is a critical issue related to the improvement of life satisfaction.

Although previous studies have made empirical contributions to this research, there are still some unresolved issues regarding the relationships among overworking, LTPA, and life satisfaction. First, previous research has focused primarily on the linear relationship between working hours and life satisfaction, suggesting that long work hours are negatively related to job burnout and subjective well-being regardless of work schedule [14]. However, in a curved relationship, the change in life satisfaction associated with a one-unit shift in working hours may not be a constant value and may vary based on the point on the regression line [15]. The potential nonlinear effect of excessive working load on life satisfaction has been examined in only a few studies [16,17]. Although these studies have measured the nonlinear impact of working hours on life satisfaction, it remains unclear how this curvature relationship differs between genders and across age groups. Thus, further exploration by reference to a diverse sample would yield more generalizable results.

Second, leisure participation acts as a resource that can facilitate psychological detachment from work engagement, which may mitigate stress and improve personal quality of life [6]. However, the extent to which leisure participation buffers the curvilinear effect of working hours on life satisfaction is worth exploring. Specifically, whether leisure participation can allow overworked adults with different demographics to deal with stress and enhance their life satisfaction remains unknown. Thus, further research in this context could facilitate interventions in the circumstances faced by vulnerable working groups and help disadvan-taged overworked groups recover from the excessive job demands they face. In the present study, data collected from the 2015 China Health and Nutrition Survey (CHNS) were used to obtain a more specific un-derstanding of the curvilinear relationship between working time and life satisfaction as well as of the curvilinear moderating effect of leisure participation in LTPA on this relationship.

METHODS

1. Participants

This study utilized cross-sectional data obtained from the 2015 CHNS. The sample process for CHNS 2015 involved a stratified proba-bility method encompassing twelve provinces and cities, using a multi-stage, random-cluster design. A total of 360 communities, 7,319 house-holds, and 16,622 individuals were initially included in the survey. Based on the research purpose, we restricted the age of participants to between 20 and 65 years. As a result, 5,557 individuals were excluded. Finally, a total of 11,065 participants were included in the statistical analysis. These twelve areas (Beijing, Liaoning, Heilongjiang, Shanghai, Jiangsu, Shandong, Henan, Hubei, Hunan, Guangxi, Guizhou, and Chongqing) col-lectively account for approximately 45% of the Chinese population. The individual questionnaire within CHNS 2015 comprises sections on ‘ Work Activities,’ ‘ Physical Activities,’ and ‘ Health Services and Disease History.’ These sections contain specific information, including ‘ weekly working hours,’ ‘ leisure time physical activities,’ and ‘ life satisfaction.’ These variables are directly relevant to the research objectives of this study. The research was approved by Kosin University Institutional Re-view Board (IRB approval no: 1040549-230105-SB-0002-01). Table 1 summarized the descriptive statistics of all variables in terms of means, standard deviations (SDs), or percentages.

Table 1.

Descriptive statistics of study variables (Restricted to ages 20-65)

Variables	Mean	SD	Percentage (%)	Sample size (N)
Life Satisfaction: LS	3.73	.83		10,391
Weekly working hours				4,239
35-44 hours/week			51.8	2,196
45-54 hours/week			19.7	835
55 hours/week			28.5	1,208
LTPA (per day)				9,166
Playing sports	.11	.59		9,166
Walking	.47	1.07		9,166
Age				11,065
20-35 (1980-1995)			18.9	2,091
36-50 (1979-1965)			36.5	4,039
51-65 (1964-1950)			44.6	4,935
Education				8,339
Primary school or none			19.9	1,659
Lower middle school			37.3	3,110
Upper middle school			16.9	1,409
Technical degree			8.9	743
University degree			15.3	1,276
Master's degree or higher			1.7	142
Sex				11,065
Man			47.3	5,234
Woman			52.7	5,831
Household registration				11,065
Rural			53.8	5,953
Urban			46.2	5,512
Regions				11,065
North			23.1	2,556
East			25.8	2,855
Middle			25.9	2,866
West			25.2	2,788
Marital status				11,065
Others			13.6	1,505
Married			86.4	9,560

2. Measures

1) Life satisfaction

Life satisfaction is a key part of subjective well-being that reflects overall well-being. Previous studies indicated that both single-item life satisfaction measures and the multiple-item Satisfaction with Life Scale (SWLS) had very similar validity [18]. In this study, life satisfaction was assessed using a single-item scale that asked the participants to respond to the following question: “ How satisfied are you with your current life?” In the questionnaire, the respondents were provided with five response categories ranging from 1 (very bad) to 5 (very good). Thus, a higher value indicated higher life satisfaction.

2) Working hours

The main independent variable used to explain life satisfaction was weekly working hours, including overtime. For workers whose regular working hours were fixed (full-time job) or not fixed (part-time job), total weekly working hours were calculated based on the sum of their weekly regular and overtime working hours. Concerning the time of overwork, approximately 36% of countries worldwide have set legal weekly working hour limits of 40 hours, while others have legislation that exceeds 40 hours per week [4]. For comparison with standard working hours of 35-40 hours/week, occupational epidemiologists generally divide overworked hours into three categories of 41-48, 49-54, and ≥55 hours/week [19]. According to the 2016 CLDS, working adults averaged more than 44 hours of work per week [10]. Therefore, to verify whether LTPA improves life satisfaction for overworked adults through the figure, the current study categorized weekly working hours as 35-44 (standard working time), 45-54 (overworked time), and ≥55 hours/week (ex-tremely overworked time) in the Chinese context.

3) LTPA

A total of seven types of active leisure activities were included: “ Martial arts”, “ Gymnastics, dancing, acrobatics”, “ Track and field, swimming”, “ Walking”, “ Soccer, basketball, tennis”, “ Badminton, volleyball”, and “ Others” were included. One item was utilized to assess leisure participation: “ Do you participate in this activity?” In response to this question, participants indicated their participation experience about each leisure time activity (1=No, 2=Yes). Some similar activities were operational-ized to form a broader category due to the low response rate. For exam-ple, activities related to sports were combined into one category, which was named “ Playing sports.” Thus, this study utilized leisure time participation in “ Playing sports” and “ Walking” as moderating variables.

4) Covariates

Age, gender, marital status, household registration, education, and re-gion, were used as control variables in this study. To determine whether the relationship between working hours and life satisfaction differs based on age, working adults were categorized into a young group (20-35 years old), a middle-aged group (36-50 years old), and an older group (50-65 years old). Gender, marital status, and household registration were coded as dummy variables (‘ female’=0 and ‘ male’=1 for gender; ‘ others’ (never married, divorced, widowed, separated)=0 and ‘ married’=1 for marital status; and ‘ rural’=0 and ‘ urban’=1 for household registration). Level of education was measured using an ordinal scale (‘ no education and grad-uated from primary school’=1, ‘ lower middle school degree’=2, ‘ upper middle school degree’=3, ‘ technical or vocational degree’=4, ‘ university or college degree’=5, ‘ master's degree or higher’=6). Considering the characteristics of the survey areas in the CHNS, the 12 regions were di-vided into four categories: “ North (Beijing, Liaoning, Heilongjiang),” “ East (Shanghai, Jiangsu, Shandong),” “ Middle (Henan, Hubei, Hunan),” and “ West (Guangxi, Guizhou, Chongqing).”

3. Statistical analysis

In the initial section of the results, we employed curvilinear hierarchical regression models to assess the impact of weekly working hours on life satisfaction within distinct demographic groups, including male working adults, female working adults, young working adults, middle-aged working adults, and older working adults. The focus of this analysis was on exploring the nonlinear relationship between working hours and life satisfaction, wherein working hours may initially increase and subse-quently decrease life satisfaction. To address potential multicollinearity concerns, we centred the independent variables before conducting statistical analyses [20]. To assess the curvilinear effects, we introduced squared terms of working hours into the models. Initially, the models included weekly working hours and control variables, followed by the squared working hours to assess whether it added a significant incre-ment to the model. Previous research has shown that when a linear moderation model is applied to bivariate relationships that are actually curvilinear, researchers cannot accurately detect the true underlying curvilinear moderation [21]. Therefore, to confirm the moderation effect of leisure participation on the curvilinear relationship between weekly working hours and life satisfaction, we employed a curvilinear moderation model. In terms of moderating, the first step incorporated weekly working hours and various aspects of leisure activities, while the second step included the linear interaction term. Subsequently, the third step introduced squared working hours, and the fourth step incorporated the interaction term between squared working hours and the various aspects of leisure activities. The presence of the quadratic interaction term between squared working hours and leisure participation signifies that the quadratic relationship between working hours and life satisfaction varies depending on the value of leisure participation [22]. All statistical analyses were conducted using SPSS 27. Statistical significance was de-termined at the conventional level of p <.05 for all analyses in this study.

RESULTS

1. Curvilinear hierarchical regression

In this study, a series of regression analyses were first conducted to investigate whether there were significant linear relations between different working hours and life satisfaction. In light of demographic differences in terms of working hours and life satisfaction, we conducted separate regressions for each gender and age group. Table 2 showed different U-shaped curvilinear relationships between weekly working hours and life satisfaction across various age and gender groups. Specifically, the square terms of working hours had significant incremental effects on life satisfaction beyond their linear effects for male working adults (β=-.105, p < .01), female working adults (β=-.129, p <.01), and older working adults (β=-.153, p <.01) while the effects for the young and middle-aged working groups were not significant. Education and residential areas were significant predictors of life satisfaction across all demographic groups while marital status was only significant for some age and gender groups. The other demographic variable was not statistically significant. A visual rep-resentation of the associations between working hours and life satisfaction is shown in Fig. 1. Working hours and life satisfaction exhibited inverted U-shaped relationships across the three demographic groups, thus indicating that more working hours do not always lead to higher or lower life satisfaction, especially for both genders and older working adults. We then calculated the vertex of each group to verify the maximum point of these equations’ parabola and found that the most ideal quanti-ties of weekly working hours for life satisfaction were 55 hours for older working adults (X-vertex=55.3, Y-vertex=3.81), 50 hours for male working adults (X-vertex=50.1, Y-vertex=3.81), and 43 hours for female working adults (X-vertex=43.5, Y-vertex=3.82). Thus, the older generation (51-65 years old) benefits more from overworked hours than younger generations do. Female workers prefer to work within standard working hours and benefit less from overworking than males do.

Fig. 1.

Curvilinear relationship between working hours and life satisfaction of working adults in different demographics.

Table 2.

Results of curvilinear regression analysis for life satisfaction

	All	Men	Women	Young	Middle	Old
Step 1
Gender	-.019	n/a	n/a	-.035	-.023	-.024
Age	-.02	-.024	-.021	n/a	n/a	n/a
Marital Status	.092^**	.141^**	.039	-.03	.176^**	.377^***
Household	.016	.029	.001	-.028	.03	.031
Education	.094^***	.087^***	.101^***	.087^***	.084^***	.111^***
North	.448^***	.472^***	.417^***	.566^***	.408^***	.438^***
East	.473^***	.494^***	.445^***	.623^***	.426^***	.426^***
Middle	.256^***	.268^***	.24^***	.342^***	.228^***	.228^***
Working hours	-.014	-.008	-.025	-.001	-.028	-.014
Value	.111	.111	.111	.143	.099	.115
Step 2
Gender	-.019	n/a	n/a	-.036	-.023	-.026
Age	-.017	-.021	-.016	n/a	n/a	n/a
Marital Status	.091^**	.14^**	.038	-.032	.176^**	.367^***
Household	.012	.026	-.008	-.026	.025	.026
Education	.091^***	.084^***	.098^***	.089^***	.082^***	.104^***
North	.449^***	.473^***	.417^***	.563^***	.408^***	.44^***
East	.465^***	.489^***	.442^***	.621^***	.422^***	.416^***
Middle	.258^***	.268^***	.245^***	.34^***	.228^***	.232^***
Working hours	.081^**	.091^*	.093	-.062	-.069	.127^*
Working hours x Working hours	-.104^**	-.105^**	-.129^**	.064	-.101	-.153^**
Change	.001	.001	.002	.000	.001	.004

^* p<.05,

^** p<.01,

^*** p<.001.

2. Moderation effects

An additional aim of this study is to examine whether participation in LTPA moderates the curvilinear relationship between working hours and life satisfaction. In the first step, we incorporated weekly working hours and various aspects of LTPA (walking and sports participation) as main effects, which allowed us to establish their direct relationships with life satisfaction. The second step included the linear interaction terms between working hours and LTPA components, enabling us to determine whether the linear relationship between working hours and life satisfaction varies depending on LTPA participation. In the third step, we introduced the squared term of working hours to capture the curvilinear (U-shaped) relationship between working hours and life satisfaction. Finally, the fourth step incorporated the interaction terms between squared working hours and the various aspects of LTPA, which revealed whether the curvilinear relationship (shape of the U-curve) differs between LTPA participants and non-participants. The results showed that the coefficient related to the interaction terms between squared working hours and life satisfaction was significant. However, the pattern of LTPA varies somewhat across different demographic subsamples. For younger overworked adults, participation in walking activities (β=.199, p <.05) benefits their life satisfaction. However, the moderation effect of LTPA is not significant for other age groups Table 3. Furthermore, participation in LTPA during leisure time does not contribute to life satisfaction of overworked adults in either gender group Table 4. The significant inter-actions between squared working hours and life satisfaction are dis-played in Fig. 2. This figure show that the relationship between weekly working hours and life satisfaction followed a U-shape in situations in which young working participants reported participating in walking. Specifically, compared with standard working hours (35-44 hours/week), when overworking reached the upper time limit (≥55 hours/week), young working adults who engaged in walking activity were more likely to have higher life satisfaction than their counterparts who were not involved in walking activity.

Fig. 2.

Curvilinear interaction effect of working hours and walk activity on life satisfaction for younger working adults.

Table 3.

Results of moderated curvilinear regression predicting life satisfaction with physical activities as moderator for different ages

	Sports		Walking
	β	∆R²	β	∆R²
Young
Step 1
Working hours	-.001		-.001
Leisure activity	.035	.143	.018	.142
Step 2
Working hours×Leisure activity	.001	.000	-.011	.000
Step 3
Working hours²	.063	.000	.059	.000
Step 4
Working hours² ×Leisure activity	.107	.000	.199^*	.003
Middle
Step 1
Working hours	-.029		-.026
Leisure activity	.040	.100	.052^**	.101
Step 2
Working hours×Leisure activity	.002	.000	-.012	.000
Step 3
Working hours²	-.103	.001	-.094	.001
Step 4
Working hours² ×Leisure activity	.029	.000	-.100	.001
Old
Step 1
Working hours	-.015		-.012
Leisure activity	.028	.112	.096^***	.119
Step 2
Working hours×Leisure activity	.005	.000	-.002	.000
Step 3
Working hours²	-.152^**	.004	-.149^**	.003
Step 4
Working hours² ×Leisure activity	.105	.001	.016	.000

^* p<.05,

^** p<.01,

^*** p<.001.

Table 4.

Results of moderated curvilinear regression predicting life satisfaction with physical activities as moderator for different genders

	Sports		Walking
	β	∆R²	β	∆R²
Men
Step 1
Working hours	-.006		-.003
Leisure activity	.043^**	.111	.048^**	.111
Step 2
Working hours×Leisure activity	.005	.000	-.014	.000
Step 3
Working hours²	-.108^*	.001	-.112^*	.001
Step 4
Working hours² ×Leisure activity	.027	.000	-.021	.000
Women
Step 1
Working hours	-.028		-.026
Leisure activity	.032	.114	.065^**	.117
Step 2
Working hours×Leisure activity	.002	.000	-.001	.000
Step 3
Working hours²	-.135^*	.002	-.131^*	.002
Step 4
Working hours² ×Leisure activity	.094	.001	.077	.001

^* p<.05,

^** p<.01, ***p<.001.

DISCUSSION

With cases ranging from a series of suicides of young migrant workers at Foxconn facilities in 2010 to the ‘996’ working hour system in 2016, the issue of work-life balance in China has drawn worldwide attention [23,24]. ‘ The 996 working hours system’ refers to a work schedule where employees work from 9 a.m. to 9 p.m., six days a week (72 hours weekly), which became prevalent in many Chinese technology companies and other industries [25]. However, the coping strategies used to improve the life satisfaction of overworked adults are inadequate. Thus, this study aimed to investigate the curvilinear relationship between working hours and life satisfaction and the buffering effect of leisure participation on this relationship. Previous studies have mostly focused on investigating the linear relationship between working hours and life satisfaction; however, they have neglected the potential curvilinear relationship between these factors [26,27]. The findings of the current study illustrate the complex relationships between working hours and life satisfaction across different demographic groups, which have not been captured by previous studies.

In line with previous research, the results of this study provide evidence for an inverted U-shaped relation between working hours and life satisfaction [16,17]. Overall, a moderate level of working hours is more closely related to higher life satisfaction than either low or high levels of working hours. As working hours increase from zero, the initial positive slope may reflect the psychological benefits of employment that contribute to life satisfaction. Previous studies have found that moderate levels of work engagement can promote life satisfaction through fostering social connection, achievement and competence [28,29]. The subsequent decline in life satisfaction beyond the threshold may relate to potential mechanisms such as reduced recovery time and physical health impacts of overwork [30,31]. For demographic groups, the life satisfaction of female working adults increase less with working hours and peaks at lower working hours than that of male working adults. These results are consistent with role conflict theory, which posits the different role expectations for different genders and emphasizes the breadwinner role of fathers as well as the caregiver role of mothers [32]. In addition, the life satisfaction of older working adults increases more with working hours and peaks at higher working hours than that of younger groups. This result emphasizes the importance of accounting for curvilinear effects when examining the relationship between working hours and life satisfaction. This finding extends research on the antecedents of working hours because most extant studies in this field have not focused on demographic differences. The results of our study suggest that different genders and generation have distinct perspectives on overworking in China. Long working hours have more detrimental effects on the life satisfaction of female than on that of the male working adults.

As a second result, it was found in this study that LTPA buffers the negative effect of working hours on life satisfaction, especially in cases of overworking. Our findings are consistent with those of previous research, which has shown that leisure participation is related to individuals’ well-being and happiness [13,33]. Among a few of LTPAs, walking may facilitate mental disengagement from work-related thoughts, which is crucial for maintaining life satisfaction despite longer working hours [34]. The rhythmic nature of walking may promote a meditative state that enhanc-es this detachment process. Additionally, walking might buffer against stress hormones associated with overwork through physiological mechanisms. Research by demonstrates how moderate-intensity walking can optimize cortisol patterns, potentially counteracting the dysregulated stress response associated with excessive working hours [35].

Moreover, the positive effects of leisure participation were identified as based on effective activity to promote recovery from work stress among working groups with specific demographics. Our results reveal that different leisure activities may offer unique benefits to overworked adults with different demographics. Specifically, walking during leisure time improves life satisfaction for overworked young adults. Walking, especially in natural outdoor environments, promotes positive emotions and provides cognitive restoration, which may help young workers experiencing high cognitive demands to build psychological resources for managing stress [36,37]. Although moderate- to vigorous-intensity sports rather than walking may enhance cognitive functions and mental health in general young adults [38], for those experiencing excessive workloads, such activities may require substantial recovery resources and induce physical fatigue that interferes with their work demands [39,40].

The accumulation of career experiences, family responsibilities, and health conditions across the lifespan creates age-specific contexts that influence how LTPA interacts with work demands [41]. Among middle-aged and older adults, individuals may choose different types of leisure activities that align with their strengths while compensating for age-relat-ed limitations [42]. Consequently, their motivations may shift toward emotionally meaningful experiences rather than physical achievement, potentially altering how they benefit from different forms of LTPAs [43]. In the Chinese context, people tend to prefer sedentary over active leisure activities. Previous studies have found that the top three favorite activities among working adults were internet surfing, drinking tea and chatting, and traveling [44]. In our study, the moderating effect of LTPAs (e.g., walking, sports) on the relationship between working hours on life satisfaction was not observed in middle or old age groups. This result may be attributed to both lifespan-related factors and cultural characteristics specific to Chinese middle-aged and older adults. On the one hand, compared to younger adults, middle-aged and older workers may benefit more from low-intensity activities when experiencing work overload. On the other hand, Chinese middle-aged and older adults may prefer sedentary rather than active leisure activities as a way to buffer work-related stress.

The current study has some limitations. The first limitation is its cross-sectional design. Thus, the direction of causality regarding the relationships among weekly working hours, life satisfaction, and LTPA cannot be tested. The second limitation pertains to the specialization of the study findings. We utilized a heterogeneous sample that included various occupations, organizational contexts, and employment conditions. Therefore, the findings of the present study should be interpreted carefully because ways of dealing with job overload via leisure participation may be occupation-specific and may depend on work environments [45,46]. The specialization of the benefits of LTPA in different occupational types should be examined in the future. Third, the secondary data utilized in this current study are relatively old (i.e., 2015). At this point, they do not reflect any changes through the COVID-19 pandemic. Thus, future research could focus on this special period to investigate the effect of social distancing on the life satisfaction of overworked adults, who are facing more sedentary working condition. Fifth, it is important to ac-knowledge that our study measured participation in LTPA without cap-turing crucial details about intensity, time, and duration of these activities. This simplified assessment approach may have obscured more nuanced relationships between physical activity patterns and the work-life satisfaction relationship. Additionally, our exclusive focus on LTPA over-looked other important domains of physical activity, specifically occupation-related physical activity (OPA) and transportation-related physical activity (TPA), which could interact differently with working hours to influence life satisfaction. Future research should examine how different intensities of physical activity (light, moderate, vigorous) might differen-tially moderate the relationship between working hours and wellbeing outcomes. Furthermore, investigating potential interaction effects between different physical activity domains (LTPA, OPA, and TPA) could provide more nuanced insights into how overall physical activity patterns influence the work-life satisfaction relationship across different gender and age groups.

CONCLUSION

This study underscores the significance of participating in LTPA as an effective mechanism for mitigating burnout caused by job overload and enhancing life satisfaction. Our findings provide a foundation for developing targeted well-being intervention programs for overworked adults across diverse demographic groups. The results confirm that older adults derive greater benefits from extended working hours, while female workers show preference for standard working hours. In addressing job overload within the Chinese context, our analysis reveals that engaging in walking during leisure time is most effective in enhancing life satisfaction among young workers. When formulating workplace well-being policies, practitioners should consider the differential benefits of various LTPA for employees working excessive hours.

Notes

CONFLICT OF INTEREST

We declare that we did not receive any financial or other support from any organization in writing this paper, and that there are no relationships that could influence the paper.

AUTHOR CONTRIBUTIONS

Conceptualization: N Chen, C kim; Data curation: N Chen; Formal analysis: N Chen; Funding acquisition: C Kim; Methodology: N Chen, C Kim; Project administration: C Kim; Visualization: N Chen; Writing - original draft: N Chen; Writing - review & editing: N Chen, C Kim.

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