Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 5, 69-82 2025 Publisher: Learning Gate DOI: 10.55214/25768484.v9i5.6799 © 2025 by the authors; licensee Learning Gate © 2025 by the authors; licensee Learning Gate History: Received: 4 February 2025; Revised: 8 April 2025; Accepted: 11 April 2025; Published: 3 May 2025 * Correspondence: jh6857@kduniv.ac.kr An investigation into the community health survey 2019 to analyze the health-related quality of life Jeongju Hong1, Jae-Hee Kim2* 1,2Dept. School of Nursing, Kyungdong University 815, Gyeonhwon-ro, Munmak-eup, Wonju-si, Gangwon-do, Republic of Korea; jjribe@kduniv.ac.kr (J.H.) jh6857@kduniv.ac.kr (J.H.K.) Abstract: This study aimed to investigate the factors influencing health-related quality of life (HRQoL) among Korean adults using data from the 2019 Community Health Survey (CHS). A cross-sectional analysis was performed utilizing a nationally representative dataset. HRQoL was measured through the EuroQol-5 Dimension (EQ-5D) instrument. Descriptive statistics, t-tests, analysis of variance (ANOVA), and multiple regression analyses were conducted to examine the associations between HRQoL and various demographic and behavioral variables. The findings revealed that age, gender, educational attainment, and household income were significantly associated with HRQoL. Furthermore, health behaviors, including smoking, alcohol consumption, and physical activity, exhibited substantial impacts on HRQoL. These results underscore the necessity of developing tailored public health interventions that address both sociodemographic and behavioral determinants to enhance population health outcomes. The study offers practical implications for policymakers and healthcare professionals in formulating effective strategies aimed at improving quality of life across diverse demographic groups. Keywords: Community health survey, Health behaviors, Health-related quality of life, Social capital, Sociodemographic factors. 1. Introduction In a society where the population is aging and the birth rate is low, the average life expectancy has increased in recent years. This is due to better income and advancements in medical technology. As a result, people are now more aware of their health and are focusing on living a healthy life even with chronic diseases. This approach to health is known as “Health-realted of Quality of Life (HR-QoL)" and involves maintaining not just physical health but also social and mental health i.e more than just being disease-free but living satisfactorily and enjoying the life [1, 2]. It is believed that the health of people is strongly linked to their life in older age, and there is a growing trend of placing more emphasis on the quality of life about health [2]. The quality of life related to health is determined by several factors, including unique features an individual and environmental factors such as physical and socio-economic surroundings. To improve community health, many health institutions are undertaking projects aimed at disease prevention. However, it is important to accurately assess the community's health status and develop a strategy based on the findings to carry out effective projects that promote community health. In Korea, the Community Health Survey (CHS) serves as a pivotal tool for deriving health statistics that are instrumental in formulating a strategic regional health business plan. Aligned with the Health Statistics Act, the CHS entails a direct assessment involving approximately 900 individuals, focusing on inquiries pertaining to the health habits of residents aged 19 years and above. Incorporating this approach into the development of strategies aimed at mitigating disparities in healthcare enhance endeavors to identify root causes and potential solutions for healthcare discrepancies in regions beyond urban centers [3]. The notion of well-being within a society is a multifaceted and inclusive notion that differs according to the distinct viewpoint and objective of each individual researcher. Johnson, et al. [4] https://orcid.org/0000-0002-1343-9624 https://orcid.org/0000-0003-4484-2114 70 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 5: 69-82, 2025 DOI: 10.55214/25768484.v9i5.6799 © 2025 by the authors; licensee Learning Gate as well as Lee, et al. [5] denoted this phenomenon as a state of subjective contentment and overall well- being articulated or encountered by individuals within physical, social, and economic contexts [5, 6]. As stated by Holmes and Dickerson [7] it signifies a composite term denoting the impact of psychological, social, and physical elements [7]. Previous research examining variables linked to quality of life revealed that socioeconomic status [8, 9] self-worth, and familial backing (physical capability and despondency have an influence on quality of life [10-12]. HR-QoL at the individual level has been demonstrated to enhance the effectiveness of both individuals and society in relation to aspects such as social support, capital, health, and socioeconomic status [13]. The development of social capital by individuals through social connections has a beneficial impact on quality of life by diminishing stress and bolstering coping mechanisms via networking, trust, and social engagement [14]. Furthermore, interactions and connections concerning social capital in rural regions hold a higher level of significance compared to urban settings; this element exerts a more pronounced influence on the quality of life related to health [15]. EQ-5D is capable of recognizing health-related issues affecting individuals at the communal scale and facilitating the development of health enhancement strategies including essential resources, their allocation, and the methodologies for community intervention [16]. EQ-5D index is a HR-QoL score which gives weightage to each variable. Prior research indicates that social capital and health behaviors are key determinants of HRQoL [17, 18]. However, urban-focused studies dominate existing literature. This study incorporates recent findings to investigate rural populations, providing a more inclusive understanding. Health-related quality of life (HRQoL) is an essential aspect of public health measurement [17]. As chronic diseases increase, understanding HRQoL, especially among rural populations, becomes vital. Studies show social and behavioral factors greatly influence HRQoL, but rural-specific analyses remain limited. This study uses CHS 2019 data to fill that gap. 2. Objectives • The present study’s goals are listed below: • Identification of general features, health characteristics and social capital. • Identification of health-related behaviors, and variations of symptoms of melancholy, HR-QoL (EQ-5D index) and life satisfaction in relation to social capital. • To study the interconnectedness of the symptoms of melancholy, life satisfaction, and EQ-5D index. • To investigate the factors influencing the HR-QoL. 3. Methods 3.1. Investigation Design This study analyzes the data obtained from the Community Health Survey (CHS), 2019. This survey was conducted to examine the characteristics of melancholy, life satisfaction, health behaviors and social capital of people residing in a city of South Korea. This is a cross-sectional study which focused on the characteristics and factors that affects the health-related QoL. 3.2. Subjects of Investigation The CHS, 2019 involved participants from a public health center who were adults with 19 years of age or older. They were divided into groups according to the housing type. A sampling frame was established through the linkage of population data and housing data from the Ministry of Land, Infrastructure, and Transport. Subsequently, following the extraction of sampling points using first-order probability proportional sampling, the ultimate sample was obtained through second-order systematic sampling [19]. In this way, a total of 892 people were included in the survey. 71 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 5: 69-82, 2025 DOI: 10.55214/25768484.v9i5.6799 © 2025 by the authors; licensee Learning Gate 3.3. Research Tools Through a thorough examination of existing literature, specific items from the Korea Centers for Disease Control and Prevention [20] health questionnaire were chosen for inclusion. Demographic features included age, gender, education, marital status, monthly earnings, and family size. Based on their education, they were categorized into elementary school or below, middle school, high school, and university or higher groups. The attributes related to their health included in the study were smoking, alcohol consumption, physical activity, self-reported health status, and the presence of hypertension and diabetes. Smoking habits were divided into categories including total lifetime consumption, current usage, and age of initiation. Details regarding alcohol consumption encompassed lifelong drinking patterns, age of onset, recent drinking behavior, frequency, and quantity consumed per occasion. In relation to physical activity, the focus was on the frequency of moderate exercise and walking within the past week. The sociocultural traits of the subjects encompassed variables such as engagement in religious, social, leisure, and charitable activities, as well as the frequency of interactions with family members, neighbors, and friends. The frequency of these interactions was classified into various categories ranging from less than once a month to every week. A score indicating higher social capital was associated with more frequent interactions. 3.3.1. Melancholy Symptoms of melancholy were ascertained through an examination of responses to a specific inquiry regarding the frequency of nine distinct symptoms experienced within a two-week timeframe. These symptoms included interest, melancholy, sleep disturbances, fatigue, changes in appetite, feelings of unhappiness, difficulties with concentration, anxious behaviors, and self-abasement, all of which may disrupt one's daily functioning. Participants' responses were recorded using a 4-point scale, indicating the duration of each symptom as "not at all," "for several days," "more than a week," or "almost every day." The cumulative score derived from these responses ranged from 9 to 36, with a higher score signifying a greater severity of melancholic symptoms. 3.3.2. Life Satisfaction The survey inquired about participants' level of contentment regarding their recent life by using a 10-point scale, which included options from "very unsatisfactory" to "very satisfied." Participants were required to rate their satisfaction level on a scale from 0 to 10, where higher scores signified greater life satisfaction. 3.3.3. HR-QoL To investigate the HR-QoL, the CHS data was utilized to assess the Korean version of the Euro- QoL 5-dimension 3 level (EQ-5D-3L) tool developed by the Euro QoL group. This tool examines five dimensions - motor skills (M), self-care (SC), daily activities (UA), pain or discomfort (PD), and anxiety or melancholy (AD). Each dimension is rated on a scale from 1 (no issue) to 3 (severe problems). The EQ-5D-3L index scores were computed based on the weighting provided in the CHS data. “The EQ-5D-3L index was calculated using the formula: 1 - (0.050 + 0.096M2 + 0.418M3 + 0.046SC2 + 0.136SC3 + 0.051UA2 + 0.208UA3 + 0.037PD2 + 0.151PD3 + 0.043AD2 + 0.158AD3 + 0.050*N3)” The numerals "2" or "3" after each letter signify the response level for that variable. The reliability and validity of the Korean version of the EQ-5D-3L tool for the general public was assessed by Lee [21] with Overall Percent Agreement (OPA) of 79-97%, Kappa values of 0.32 to 0.64 and Intraclass Correlation Coefficient (ICC) values of 0.65 and 0.61. 4. Data Collection The Korea Centers for Disease Control and Prevention [20] utilized in this study is a nationwide sample survey conducted annually across 17 cities and provinces, targeting all adults aged 19 and above 72 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 5: 69-82, 2025 DOI: 10.55214/25768484.v9i5.6799 © 2025 by the authors; licensee Learning Gate [19]. This survey follows a standardized implementation system designed to assess the health status of residents and aid in the establishment and evaluation of community health care plans. Data collection involved sending household selection notices to chosen households, followed by visits from trained surveyors. Subjects were briefed on the purpose of the investigation and the CHS, and an electronic survey administered via laptop computers was utilized. Data collection included face-to-face interviews using individual survey questionnaires for household members and a separate household survey, requiring responses from a single representative per household. 4.1. Data Analysis The study utilized SPSS/WIN 28.0 for data analysis. Initially, descriptive statistics were employed to analyze various characteristics of the subjects, including general, health-related, and social capital attributes, as well as symptoms of melancholy, life satisfaction, and HR-QoL. Subsequently, differences across subjects' characteristics based on social capital traits were examined using independent t-tests and ANOVA. Pearson's correlation method was then used to explore relationships between symptoms of melancholy, life satisfaction, and HR-QoL. Finally, Multiple Linear Regression Analysis was conducted to identify factors impacting HR-QoL. 4.2. Ethical Considerations for Research The Community Health Survey (CHS) strictly adheres to the guidelines specified by the Korea Centers for Disease Control and Prevention and the Personal Information Protection Act and the Statistical Act. Publicly accessible data were provided to researchers after the exclusion of personal details related to the participants, and the data were distributed in a de-identified format for downloading purposes. 5. Results Older age, female gender, low education, low income, smoking, and inactivity were associated with poorer HRQoL. Positive health behaviors and strong social capital correlated with higher HRQoL. Subjective health status and chronic diseases significantly impacted quality of life. 5.1. Demographic variations of Life satisfaction Index (LSI), Melancholy Index (MI) and HR-QoL Index Life Satisfaction Index (LSI) The mean age of the participants was 53.04 years, and the mean score for the life satisfaction index(LSI) was 7.10. The highest score of LSI (7.24) was observed for the subjects in the age range of 19 to 44 years, however, this difference with other age groups was not statistically significant (F = 1.63, ρ = .180). The subjects with higher education degrees had higher scores than the married subjects for LSI. The LSIs for those having an income of 5,000,000-7.99 million won and 8,000-9,990,000 won were statistically significantly higher as compared to those having lower incomes. (F = 6.54, ρ < .001). The people belonging to families having 4 family members had a higher life satisfaction index than those having fewer family members. 5.2. Melancholy Index (MI) The mean for the melancholy index (MI) was 11.81. For females, the MI was 12.44, higher than the males (11.10) and was statistically significant (t = -5.45, ρ = < .001) The MI for people above the age of 75 years, the MI was the highest (Statistically significant at the level of 0.05) than those in the lower age range. For educational level, those having no education had the highest mean score for MI. Divorced or widowed subjects showed higher b=values for MI than the married subjects (F=4.52, ρ<.001). Like was the participants in the lowest income group showed the highest value for the Melancholy index (F = 3.60, ρ = .003). There was no difference in the MI (F = 1.75, ρ = .121) for the different groups based on the number of family members (Table 1). 73 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 5: 69-82, 2025 DOI: 10.55214/25768484.v9i5.6799 © 2025 by the authors; licensee Learning Gate 5.3. Health-related Quality of Life (HR-QoL) The mean score for HR-QoL was 0.89 (± 0.13). The males showed statistically significantly higher values (0.91± 0.07) as compared to females (t = 5.73, ρ = <.001). The mean scores of HR-QoL according to age groups in order of decreasing values were “19-44 years old” subjects, “45-64 years old” subjects, “65-74 years old” subjects, and “75 years old or older” subjects. These differences were statistically significant (F=57.67, ρ<.001). The university graduate subjects had the highest score for HR-QoL. Table 1. Demograhy of the participants and their scores of LSI, MI and HR-QoL (N = 892). Characteristics Categories n % Satisfaction of Life (LSI) Melancholy Index (MI) HR-QoL (HR-QoL) M±SD t or F (ρ) M±SD t or F (ρ) M±SD t or F (ρ) Gender Male 416 46.6 7.14±1.69 0.65 (.051) 11.10±1.07 -5.45 (<.001) 0.91±0.07 5.73 (<.001) Female 476 53.4 7.07±1.68 12.44±4.07 0.87±0.13 Total 892 100.0 7.10±1.68 11.81±3.76 0.89±0.11 Age (Years) 19-44a 269 30.2 7.24±1.50 1.63 (.180) 11.92±3.82 3.18 (.023) b=75d 111 12.5 6.96±1.87 12.76±4.67 0.78±0.18 M±SD 53.04±17.03 Education Never attended schoola 35 3.9 6.63±1.96 6.03 (<.001) a,bc,d >e 9.87±1.51 52.23 (<.001) a,bd,e b>c>d,e Goodb 237 26.6 7.63±1.36 10.51±2.32 0.94±0.03 Moderatec 420 47.1 6.96±1.63 11.56±3.13 0.91±0.07 Badd 123 13.8 6.54±1.81 14.45±5.02 0.83±0.11 Very bade 51 5.7 5.69±1.83 16.02±5.79 0.66±0.26 Presence of hypertension Have 249 27.9 6.90±1.79 -2.17 (.030) 11.96±4.14 0.72 (.469) 0.85±0.14 -5.80 (<.001) None 643 72.1 7.18±1.62 11.76±3.61 0.91±0.08 Presence of diabetes mellitus Have 113 12.7 6.75±1.67 -2.35 (.019) 12.46±4.22 1.94 (.052) 0.83±0.16 -4.50 (<.001) None 779 87.3 7.15±1.67 11.72±3.69 0.90±0.09 5.10. LSI, MI and HR-Qol With Respect to the Social Capital Features Table 3 provides insights into the characteristics of social capital among community participants and their associations with satisfaction of life, symptoms of melancholy, and HR-QoL. 5.11. Religious Activity Participants engaging in religious activities demonstrated higher LSI values compared to those not engaging in religious activities (t = 3.02, p = 0.003). However, there were no significant difference in MI values (t = -12.4, p = 0.213) as well as in HE-QoL compared to those not engaging in religious activities (t = -0.68, p = 0.494). 5.12. Social Activities Participants engaging in social activities showed higher LSI (t = 3.17, p = 0.002), lower MI values (t = -4.04, p < 0.001).and higher HR-QoL values compared to those not engaging in social activities (t = 3.12, p = 0.002). 5.13. Leisure Activities Similar to results of social activities, the participants engaging in leisure activities demonstrated higher LSI, lower MI and higher HR-QoL compared to those not engaging in leisure activities (t = 3.08, p = 0.002; t = -3.64, p < 0.001; t = 7.24, p < 0.001, respectively). 77 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 5: 69-82, 2025 DOI: 10.55214/25768484.v9i5.6799 © 2025 by the authors; licensee Learning Gate 5.14. Frequency of Contact with Comparatives (including Family Members) Participants who had contact with comparatives less than once a month showed lower LSI compared to those with higher contact frequency (t = 3.15, p = 0.008), higher MI values compared to those with higher contact frequency (t = 4.56, p < 0.001). However, no significant difference in HR-QoL was found compared to those with higher contact frequency (t = 0.59, p = 0.708). 5.15. Frequency of Contact with Neighbors Participants who had contact with neighbors less than once a month showed lower LSI compared to those with higher contact frequency (t = 3.25, p = 0.006). However, no significant differences were found in values of in MI and HR-QoL compared to those with higher contact frequency (t = 2.20, p = 0.053 and t = 1.63, p = 0.149, respectively). 5.16. Frequency of Contact with Friends Participants who had contact with friends less than once a month showed no significant difference in LSI compared to those with higher contact frequency (t = 0.73, p = 0.601). on the other hand, higher MI and lower HR-QoL were observed as compared to those with higher contact frequency (t = 3.20, p = 0.007 and t = 11.30, p < 0.001, respectively). These findings suggest that frequency of contact with comparatives, neighbors, and friends has varying associations with satisfaction of life, symptoms of melancholy, and HR-QoL, highlighting the importance of social connections in overall well-being. 78 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 5: 69-82, 2025 DOI: 10.55214/25768484.v9i5.6799 © 2025 by the authors; licensee Learning Gate Table 3. Characteristics of Social capital and their scores for LSI, Par MI and HR-QoL (N=892). Characteristics Categories n (%) Satisfaction of Life Melancholy HR-QoL M±SD t or F (ρ) M±SD t or F (ρ) M±SD t or F (ρ) Religious activity Yes 279 31.3 7.35±1.69 3.02 (.003) 11.58±3.40 -12.4 (.213) 0.89±0.10 -0.68 (.494) No 613 68.7 6.99±1.66 11.92±3.91 0.89±0.11 Social activities Yes 498 55.8 7.26±1.54 3.17 (.002) 11.34±3.03 -4.04 (<.001) 0.90±0.08 3.12 (.002) No 394 44.2 6.90±1.82 12.41±4.46 0.88±0.14 Leisure Activities Yes 302 33.9 7.33±1.47 3.08 (.002) 11.23±3.02 -3.64 (<.001) 0.92±0.05 7.24 (<.001) No 590 66.1 6.98±1.76 12.11±4.06 0.88±0.12 Charity work Yes 94 10.5 7.63±1.45 3.23 (.001) 11.08±2.69 -1.99 (.046) 0.90±0.06 1.76 (.079) 798 89.5 7.04±1.69 11.90±3.86 0.89±0.11 No Frequency of contact with comparatives (including family members) less than once a montha 94 10.5 6.53±2.09 3.15 (.008) a