Association between lifestyle values, lifestyle, and quality of life among the community-dwelling late middle-aged and older adults: A retrospective cross-sectional analysis
Article information
Abstract
Purpose
This study aims to investigate the association of lifestyle values with lifestyle and quality of life among community-dwelling late middle-aged and older adults.
Methods
This retrospective cross-sectional study analyzed secondary data of 200 late middle-aged and older adults. Lifestyle and lifestyle values were measured by Yonsei Lifestyle Profile (YLP) and YLP-Value, respectively. The mediator was quality of life, and a mediation analysis was conducted to examine the relationship between lifestyle values, lifestyle, and quality of life. Our study then repeated the analysis by dividing lifestyle into three components: physical activity, nutrition/eating habit, and activity participation.
Results
Mediation analysis revealed significant associations across all pathways (all p<.001). The lifestyle values were associated with lifestyle (β=.40). Both lifestyle value (β=.40) and lifestyle (β=.18) were positively associated with quality of life. The indirect effect of lifestyle values on quality of life, mediated by lifestyle, accounted for 14.58% of the total effect, with the direct effect constituting 85.42%.
Conclusion
Among the three components of lifestyle, a mediation effect was observed between lifestyle values, nutrition/eating habit, and quality of life. Our results indicate the need for education to increase lifestyle values within lifestyle programs, emphasizing the significance of lifestyle values in enhancing both lifestyle and quality of life among late middle-aged and older adults. Health professionals may integrate the results into interventions by recognizing the importance of lifestyle values.
INTRODUCTION
As lifestyle-related health risks are surging [1], a lack of physical activity, sedentary behavior, unhealthy eating habits, smoking, and harmful drinking are widespread in modern society [1,2]. The unhealthy lifestyle is closely linked to the onset of inevitable non-communicable diseases (NCDs), including overweight, obesity, elevated blood pressure, and increased serum cholesterol levels [3]. Due to an aging population and growing obesity worldwide, mortality related to NCDs and annual direct healthcare costs are expected to increase over the next decades [4]. To prevent this phenomenon, healthcare professionals encourage healthier eating, quitting smoking, limiting alcohol consumption during regular physical activities and NCD treatments [1]. However, the sustained adoption and maintenance of these healthy lifestyle behaviors often stem from individual’s underlying values and beliefs.
Health promotion through a healthy lifestyle aims at fostering self-realization, enabling individuals to sustain or enhance their health while actively cultivating new positive behaviors [5]. An optimally healthy lifestyle encompasses physical exercise, smoking cessation, moderate alcohol consumption, healthy dietary practices, increased social engagement, and active participation in various life domains [6,7]. Because healthy behavioral changes are often not maintained in the long term [8,9], it is important to maintain behavior after the initial changes [10]. Behavior maintenance theory suggests habit formation and the perceived value of a new behavior an important determinant of behavior in the long term [11]. While established health behavior theories broadly acknowledge the role of values and cognition, the present study specifically focuses on ‘lifestyle values’—the deeply held beliefs and priorities that guide individuals’ daily choices and serve as a crucial, yet often underexplored, foundation for sustained healthy lifestyle engagement, particularly in middle-aged and older adults.
Lifestyle is an important factor affecting quality of life, which is a comprehensive indicator of an individual’s health status, economic, social, environmental aspects, and subjective satisfaction [12]. Previous studies reported that healthy lifestyle factors (smoking, drinking, physical activity, diet, and body mass index) were associated with a high level of quality of life. In contrast, unhealthy lifestyle habits such as smoking, lack of physical activity, poor eating habits, and obesity are reported to be related to a low quality of life [13,14]. Crucially, lifestyles are not immutable; they are chosen according to individual values and beliefs in various environments, and can therefore be modified to improve health and quality of life [15]. Several studies have reported that lifestyle modification improves the quality of life and physical health, suggesting that healthcare is possible despite changes in individual behavior compared to immutable traits such as age and sex [16].
Existing studies have explored the relationship between quality of life and lifestyle, but there is a limit to not paying sufficient attention to the role of values in shaping healthy lifestyle choices and subsequent behavior [12-14]. This may have limitations in understanding the complex interactions between lifestyle choices and quality of life [15]. In addition, it is pointed out that existing studies have sparsely explored in detail the interactions and their effects between lifestyle factors, and have not fully addressed various aspects of the association of a particular lifestyle on quality of life. Thus, the specific mechanistic pathway by which lifestyle values lead to lifestyle behaviors and then impact quality of life remains underexplored. Understanding this value-behavior-outcome continuum, with lifestyle as a mediator, is crucial for developing effective interventions.
This study investigated the relationship between lifestyle values associated with lifestyle choices and the quality of life. This research differs from existing studies in that it explores lifestyle values and elucidating their association with quality of life. By examining the correlation between lifestyle values guiding lifestyle choices and their direct influence on overall quality of life, this study aims to offer new insights into how personal values shape lifestyle decisions and subsequently influence well-being. Emphasizing the significance of integrating values into lifestyle choices to enhance the overall quality of life serves as a crucial focus, seeking to bridge gaps in the current research by providing a deeper understanding of how values shape lifestyles and their implications for overall well-being. Therefore, this study aims to examine the mediating role of lifestyle (physical activity, nutrition/eating habit, activity participation) in the relationship between lifestyle values and quality of life among late middle-aged and older adults. Clarifying this value-behavior-outcome pathway may offer a deeper understanding of how values link to well-being, informing effective health promotion.
METHODS
Ethic statement: This study has been reviewed and approved by the Institutional Review Board of the Yonsei University Mirae Campus (1041849-202402-SB-022-01). We used the secondary data, collected at the previous study (IRB No. 1041849-202207-SB-135-03).
1. Study Participants and Data
This was a retrospective cross-sectional study, and data were collected through an online survey conducted by an online research company (Macromill Embrain; www.embrain.com) in the previous study (IRB No. 1041849-202207-SB-135-03). This data, collected by quota sampling based on age and sex, included a total of 200 participants. Specifically, 150 participants were assigned to the 55 to 64 age group and 50 participants to the 65 and older age group. Within each age group, sex was balanced as evenly as possible. The inclusion criteria were as follows: 1) adults aged above 55 years, 2) those who could read and understand sentences written in Korean, and 3) those who were not officially registered as persons with disabilities. After data collection, the company provided the raw data to the researcher after removing individual identification information. In total, 200 late middle-aged and older adults participated. This study has been approved by the institutional review board (IRB) of Yonsei University Mirae Campus (IRB No. 1041849-202402-SB-022-01). This study was reported in accordance with the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) guidelines (https://www.strobe-statement.org).
2. Study Variables
The dependent variable was quality of life, which was measured using the World Health Organization Quality of Life Brief version (WHOQOL-BREF). WHOQOL-BREF includes 26 items on general health (2 items), physical health (7 items), psychological health (6 items), social relationships (3 items), and environmental health (8 items), and it was scored on a 5-point Likert scale [17]. To calculate the total score, we transformed the total score for each category to range from 4 to 20. We then summed the total scores for each category and used the total score as the dependent variable, it indicates that higher score means the good status in quality of life. The internal consistency was .66 to .82 (Cronbach’s α), and the test-retest reliability was .66 to .87 [18].
The independent variable was lifestyle value, measured using the Yonsei Lifestyle Profile-Value (YLP-V). The YLP-V is an assessment tool one’s lifestyle values (e.g., I tend to enjoy hanging out with people and I tend to care about the health and well-being of my family) and was developed using the Delphi method [19]. This assessment tool consisted of three categories—activities, interests, and opinions—and included 24 lifestyle-related concepts (e.g., work, hobbies, rest, media, health issues, and education). The lifestyle values in this study refers to the degree to which individuals prioritize, enjoy, and consider certain lifestyle-related domains as important in their daily lives. For example, items such as hanging out with people are intended to reflect social engagement as a valued lifestyle domain. It consists of 24 items and scored on a 5-point Likert scale (1=strongly disagree to 5=strongly agree), with total scores ranging from 24 to 120. Higher scores indicated positive lifestyle values, indicating a more engaged and health-oriented lifestyle, and we used the sum of total score as the independent variable. This assessment tool demonstrated a content validity of .89, stability of .16, convergence of .42, and a consensus level of .76 [19].
The mediator was a lifestyle measure based on the YLP, which has been examined for validity [20]. This assessment tool examines multiple dimensions of the lifestyle of older adults, consisting of three domains (physical activity, nutrition/eating habit, and activity participation) and 22 items. The YLP has been scored on a 5-point Likert scale (1: 0 days per week, 2: 1~2 days per week, 3: 3~4 days per week, 4: 5~6 days per week, 5: every day per week), with total scores ranging from 22 to 110. We used the total score after summing all the items, and a higher YLP-V mean that they had a positive lifestyle. In our study, a positive lifestyle refers to regular and diverse engagement in physical activities, maintaining healthy eating habits (e.g., striving to consume nutritious food), and participating in a variety of meaningful activities. The internal consistency was .83 (Cronbach’s α), and the test-retest reliability was .97 [21].
The covariates included age, sex, educational attainment, residential area, marital status (1=yes, I have a spouse; 2=others), employment status (1=yes, I’m working now; 2=others), and monthly income based on the previous studies [22-24]. Educational attainment was categorized based on whether the individual had graduated from high school. In the original data, the scoring for residential areas included metropolitan areas, provincial capitals, medium-sized cities, and rural cities. However, due to the small sample size of participants living in rural cities, we combined medium-sized and rural cities into a single category. Monthly income was treated as a continuous variable and categorized as follows: 1=below 1,000,000 won; 2=1,000,000~2,999,999 won; 3=3,000,000~3,999,999 won; 4=4,000,000~4,999,999 won; 5=5,000,000~5,999,999 won; 6=6,000,000~6,999,999 won; 7=over 7,000,000 won.
3. Statistical Analysis
Demographic characteristics were presented as frequency and percentile for categorical variables, and numerical variables as mean and standard deviation. We used mediation analysis to examine the mediating role of lifestyle in the relationship between lifestyle and quality of life. Mediation analysis can examine the role of mediators between independent and dependent variables. Traditional mediation analysis, Baron and Kenny’s approach, examines these relationships through a simple linear regression analysis of pathways (i.e., first, independent variable on dependent variable; second, independent variable on mediator; third, mediator on the dependent variable). However, this approach has limitations as it cannot directly examine the significance of the indirect effect or calculate the magnitude of the mediation effect [25]. To address these limitations, we employed path analysis to examine the indirect effect of the mediator (lifestyle) between the independent variable (lifestyle value) and the dependent variable (quality of life). Then we conducted the sensitivity analysis by analyzing the association among these factors after dividing lifestyle into physical activity, nutrition/eating habit, and activity participation. We extracted the total, indirect, and direct effects respectively, and assessed their significance using a 95% confidence interval with 1,000 bootstrap resamples. Before the analysis, a statistical power analysis was performed using G*Power to determine the proper sample size. These results showed that, at a significance level of .05, the number of participants in this study was sufficient to detect the expected effect size with reasonable statistical power (usually set at 0.80). Data were cleaned and analyzed using SAS software (version 9.4; SAS Institute).
RESULTS
1. Demographic Characteristics of Participants
The demographic characteristics of study participants were presented in Table 1. The participants consisted of 100 males and 100 females with a mean age of 61.3±5.7 years. Most study participants lived in metropolitan areas (n=123, 61.5%) and possessed an educational background of university level or higher.
Demographic Characteristics of Study Participants
2. Correlations Among Variables
Table 2 shows the results of correlation analysis among the variables. Lifestyle was correlated with quality of life (r=0.45, p<.001) and lifestyle value (r=0.46, p<.001). In addition, lifestyle value was correlated with quality of life (r=0.55, p<.001).
The Correlation Analysis Among QoL, Lifestyle Value, and Lifestyle
3. Bootstrap Analysis and Path Among Lifestyle Value, Nutrition/Eating Habit, and Quality of Life
Figure 1 presents a diagram of our model. The model fit indices were not calculated because the model reached saturation. Table 3 displays the results of the bootstrap analysis for each path, where all paths demonstrated statistical significance with p-values of less than .05. Lifestyle value was found to be positively associated with lifestyle itself. Furthermore, positive associations were observed between lifestyle values and high quality of life, with standardized estimates of 0.40 (95% confidence interval [95% CI]=0.28~0.52), and between lifestyle values and lifestyle (β=.40, 95% CI=0.27~0.52). The path from lifestyle to quality of life also showed a positive association, with an standardized estimate of 0.18 (95% CI=0.06~0.31). The indirect effect of lifestyle values on quality of life, mediated by lifestyle, was 0.07, and the total effect was 0.48. The model explained 14.58% of the variance through indirect effects and 85.42% through direct effects.
The path diagram of study.
*p<.01.
Results for Bias-Corrected Bootstrap Analysis of Each Path (N=200)
Table 4 shows the direct, indirect, and total effects on the quality of life, lifestyle value, and nutrition/eating habit. The lifestyle value was associated with quality of life (β=.40, 95% CI=0.28~0.52) and nutrition/eating habit (β=.30, 95% CI=0.20~0.40), respectively. Nutrition/eating habit also was associated with quality of life (β=.24, 95% CI=0.08~0.40). There is an indirect effect between lifestyle value and quality of life, mediated by nutrition/eating habit (β=.07, 95% CI=0.03~0.13), and the total effect was 0.48 (95% CI=0.34~0.59). The model explained 14.58% of the variance through indirect effects and 85.42% through direct effects. The indirect effect was not observed in the other factors of lifestyle (e.g., physical activity and activity participation) (Supplementary Table 1, 2).
Results for Bias-Corrected Bootstrap Analysis of Each Path Among Lifestyle Value, Nutrition/Eating Habit, and QoL (N=200)
DISCUSSION
This study examined the pathways through which lifestyle values and behaviors such as lifestyle are associated with quality of life in late middle-aged and older adults. These age groups often establish intrinsic lifestyles, making the transition from unhealthy to healthy habits, challenging. Whereas previous studies have emphasized the importance of adopting healthier lifestyle practices, as unhealthy habits can increase mortality rates, chronic disease prevalence, and dependency in daily living, our research highlights that a higher quality of life is associated with positive lifestyle value and healthy lifestyle behaviors among late middle-aged and older adults.
In the context of lifestyle, our findings suggest the possibility that lifestyle values may be particularly important among late middle-aged and older adults. Many behavioral theories propose that values influence behavior, which in turn leads to positive outcomes such as quality of life and well-being [10,26,27]. Based on this theoretical framework, our study aimed to examine the pathways between lifestyle values and quality of life, with a specific focus on lifestyle as a potential mediator. However, the direct effect of lifestyle values on quality of life was greater than the indirect effect through lifestyle, explaining a larger proportion of the variance in quality of life. This may suggest that other factors exist between lifestyle values and quality of life. In other words, lifestyle values may influence quality of life not only through actual behavior, but also through psychological mechanisms such as self-efficacy, social support, or self-regulation.
The results of the study showed that lifestyle values have both direct effects on quality of life and indirect effects through lifestyle. This suggests that lifestyle redesign programs that focus solely on behavioral change need to be expanded to include educational components aimed at enhancing lifestyle values [28-30]. Uemura et al. [28] implemented an active learning-based educational program to promote healthy lifestyles among older adults. The program emphasized education rather than enforcing exercises under supervision, and included strategies that older adults could use to plan for a healthier lifestyle—for example, collecting health information from various media sources and sharing it with other group members. Park et al. [27] introduced the Lifestyle-Decision, Execution, Personal factor, Environment, Resources Model (Lifestyle-DEPER Model), which identifies lifestyle values as crucial factors influencing lifestyle creation. Moreover, lifestyle values can play a pivotal role in the knowledge strategies of the Intervention Strategies for Lifestyle Changes for Health [27]. This strategy refers to an exploration process during the lifestyle decision stage, and it promotes health and lifestyle awareness, motivating participants to prioritize a healthy lifestyle [27]. Thus, our findings support the approach of integrating lifestyle values into educational frameworks within lifestyle redesign programs. This approach not only promotes a deeper understanding and appreciation of healthy lifestyle choices among participants, but also promotes a shift towards continuous well-being and quality of life. This emphasizes the importance of holistic and value-driven methodologies in the design and implementation of health-promotion interventions.
Enhancement of quality of life among late middle-aged and older adults can be achieved through the elevation of lifestyle values and the adoption of healthy habits. Our findings corroborate this notion, aligning with previous research emphasizing the pivotal role of lifestyle values in overall well-being [31,32]. This study can only interpret the association between lifestyle values, lifestyle, and quality of life due to the use of a cross-sectional, and not an experimental approach. Similar to our study, Kangasniemi et al. [33] performed an intervention that focused on lifestyle values. They conducted acceptance and commitment therapy (ACT) to promote active lifestyles and well-being, focusing on selected life values to cultivate committed behaviors through reflection on personal values. As a result, physical activity of the participants in the ACT group increased [33]. However, studies employing experimental designs to investigate the impact of lifestyle values are scarce [33]. Thus, researchers interested in lifestyle are encouraged to explore the association of lifestyle values on the lifestyle, quality of life, and mental health of late middle-aged and older adults through systematic experimentation. In addition, researchers must investigate how differences in lifestyle values affect the lifestyle and quality of life of late middle-aged and older adults.
The nutrition/eating habits may be more sensitive the lifestyle value. Our results reveal that there is an indirect effect of nutrition/eating habits in the association between lifestyle value and quality of life, and there are no indirect effects on physical activity and activity participation. That means the increasing lifestyle value may helpful the good quality of life by having healthy lifestyle in terms of nutrition/eating habits. Previous literature showed the positive effect of educational intervention to change to healthy nutrition/eating habits [34-36]. Ortiz Segarra et al. [36] conducted a study using an educational intervention based on Ausubel’s theory of meaningful learning and Vygotsky’s sociocultural theory, aiming to promote understanding of the value of healthy eating. In addition, the systematic review study also reported that education or provide advice about the healthy eating was key focus of the intervention and demonstrated effectiveness [35]. Our findings can highlight the importance of education which enhances the lifestyle value in an aspect of nutrition/eating habits. To sum up, these educations have a role in helping individuals re-evaluate their lifestyles and maintain healthy nutrition/eating habits. Especially, through systematic and continuous educational programs, awareness of nutrition/food habits can be raised and substantial behavioral changes can be induced. This can contribute to improving quality of life in the long run.
This study had a few limitations. Our study used data collected by a company via a computer or phone, which can be associated with educational attainment. Regarding the demographics of the participants, the educational attainment of most was college level and higher. This may indicate bias in the selection of participants; thus, the findings should be carefully explained. Additionally, we adjusted the model using demographic covariates; however, the dataset did not include information on participants’ health status, such as disease prevalence or health management. These factors may be associated with lifestyle values, lifestyle, and quality of life. Therefore, this limitation should be considered when interpreting the findings.
CONCLUSION
This study explored the role of lifestyle values on lifestyle and quality of life among late middle-aged and older adults and uncovered significant associations among these factors, highlighting the importance of enhancing lifestyle values and incorporating education about these values into lifestyle interventions. The study results expand the framework and outcomes of previous research on lifestyle, and offer new insights into the development of more effective lifestyle redesign interventions by emphasizing the role of lifestyle values.
Notes
Authors' contribution
Conceptualization - SB, IH, and ARK; Data curation - SB, IH, and ARK; Formal analysis - SB, IH, and ARK; Methodology - SB, IH, and ARK; Supervision - IH and ARK; Writing–original draft and Writing–review & editing - SB, IH, and ARK.
Conflict of interest
No existing or potential conflict of interest relevant to this article was reported.
Funding
This work was supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF-2021S1A3A2A02096338).
Data availability
Please contact the corresponding author for data availability.
Acknowledgements
None.
Supplementary materials
Supplementary Table 1.
Result for Bias-Corrected Bootstrap Analysis of Each Path Among Lifestyle Value, Quality of Life, and Activity Participation (N=200)
Supplementary Table 2.
Result for Bias-Corrected Bootstrap Analysis of Each Path Among Lifestyle Value, Quality of Life, and Physical Activity (N=200).