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Abstract

This study aimed to identify factors influencing subjective health status (SHS, an individual’s self-rated perception of their overall health) among frail older adults using data from the 9th Korean Longitudinal Study of Aging (KLoSA). By examining multidimensional variables, the study seeks to inform tailored interventions designed to enhance perceived health and prevent frailty progression in frail community-dwelling older adults. A secondary data analysis was conducted utilizing the 9th wave of KLoSA. The sample comprised 447 community-dwelling older adults classified as frail. SHS served as the dependent variable. Data were analyzed using a complex samples general linear model with IBM SPSS Statistics version 26.0. The mean SHS score was 2.48 ± 0.04 on a 5-point scale. Factors significantly associated with higher SHS scores among frail older adults included physical activity at least once a week (P = .040), absence of cognitive impairment (P < .001), fewer chronic diseases (P = .032), lower depression scores (P = .033), better instrumental activities of daily living function (P < .001), and higher life satisfaction (P = .036). These findings underscore the multidimensional nature of SHS, reflecting both overall health and early indicators of frailty progression and functional decline. Based on these findings, community-based interventions emphasizing physical activity, mental health management, functional rehabilitation, and life satisfaction enhancement are suggested for frail older adults. Further longitudinal research and intervention development guided by these findings are needed.

Keywords

chronic diseases cognitive impairment depression elderly frailty life satisfaction physical activity subjective health status

Highlights

● This study identified multidimensional factors influencing subjective health status (SHS) among frail community-dwelling older adults using national survey data.

● Higher SHS was associated with regular physical activity, preserved cognitive function, fewer chronic diseases, lower depression, and greater life satisfaction.

● SHS serves as an integrated indicator for early detection of frailty progression, supporting holistic community-based interventions.

Introduction

Globally, the proportion of older adults aged 65 years and over is increasing rapidly, projected to reach 16% by 2050 compared to 10% in 2022.¹ In South Korea, this trend is even more pronounced, with the proportion of adults aged 65 and over expected to exceed approximately 20% by 2025, classifying the nation as a super-aged society.¹ This rapid demographic shift profoundly affects healthcare systems and society as a whole, underscoring the need to shift the understanding of elderly health from mere survival to a quality of life perspective.² Older adults can be categorized into healthy, frail, or disabled groups based on their health status.³ Healthy older adults maintain normal cognitive and daily functioning, disabled older adults require assistance due to decreased physical or mental function, and frail older adults represent an intermediate state between healthy and disabled statuses.³

Upon reaching old age, individuals typically experience numerous physical and psychological changes over an expected lifespan exceeding 20 years, often culminating in frailty.³ Frailty, defined as a geriatric syndrome rather than a single disease, involves cumulative declines in physical functioning and physiological vulnerability, marking an intermediate stage between healthy aging and disability.⁴ While frailty is closely associated with negative outcomes such as falls, long-term care, hospitalization, and increased mortality, timely assessment and management can reverse physical and mental impairments, highlighting its reversible nature.⁴ Recent studies suggest that interventions focusing on exercise, nutrition, and social interaction can mitigate frailty, emphasizing the need for systematic healthcare management to prevent frailty progression.⁵ In regions such as the United States and Europe, frailty classification facilitates effective primary interventions aimed at preventing its progression.⁴ Similarly, Japan has established health policies categorizing older adults to maintain their health status and improve residual functions through various preventive programs, supporting independent living.³

Within this context, effectively addressing frailty among older adults requires a comprehensive approach that considers subjective health status (SHS) alongside physical disease or functional decline. SHS refers to an individual’s overall self-assessment of their health, encompassing physical, mental, and social dimensions in a single integrative measure.⁶ Unlike objective indicators such as disease diagnosis, biomarker levels, or performance-based functional assessments, SHS captures personal perceptions shaped by cultural, psychological, and social contexts.^7,8 Previous studies have shown that SHS is a strong independent predictor of mortality, hospitalization, and functional decline, even after adjusting for objective health measures.^6,7 Moreover, SHS reflects broader aspects of well-being, including emotional stability, social engagement, and perceived autonomy, which are often overlooked by purely clinical measures.^8
-10 This multidimensionality makes SHS particularly valuable in frailty research, where complex interactions between physical, cognitive, and psychosocial factors shape health trajectories.⁷ Given that frailty encompasses complex declines in physical, cognitive, psychological, and social functioning, SHS can effectively capture this multifaceted condition.⁴ Furthermore, SHS acts not only as an outcome of frailty but also contributes to its exacerbation through reduced health behaviors and diminished self-efficacy, representing a cyclic causal structure.⁹ This bidirectional relationship emphasizes the need to analyze frailty and SHS as interacting components of a complex system rather than as isolated phenomena.

Higher perceived SHS is associated with improved health behaviors, which in turn can delay aging processes, maintain high physical functioning, and prevent progression to disability.¹⁰ Therefore, SHS represents a key target in developing health intervention strategies for frail older adults due to its significant potential for intervention and strong linkage with health behavior practices. Its associations with regular exercise, life satisfaction, emotional stability, and social support enable practical intervention designs and meaningful evaluations of health programs.^5,11 Previous research on frailty has primarily focused on physical function and health behaviors,^12,13 subjective health status,^2,12 and health-promoting behaviors.¹² However, studies often emphasize the relationships between frailty and individual factors such as physical function decline, fall risk, and healthcare utilization or explore isolated correlations, resulting in a limited comprehensive understanding of the structural relationship between frailty and SHS.^13,14 Given their bidirectional interactions, there is a critical need to holistically examine factors influencing SHS among frail older adults to effectively enhance their health.

Therefore, this study aims to comprehensively analyze factors affecting SHS among community-dwelling older adults aged 65 and over, classified as frail, using data from the 9th wave of the Korean Longitudinal Study of Aging (KLoSA, 2022). Findings from this study are anticipated to serve as foundational data for developing effective health promotion strategies informed by perceptions of health among frail older adults.

Methods

Study Design

This study is a secondary analysis conducted to identify factors influencing SHS among community-dwelling frail older adults aged 65 and over, using data from the 9th KLoSA, conducted in 2022.¹⁵ This study followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines for cross-sectional studies.¹⁶

Study Sample

The KLoSA provides foundational data for understanding aging processes in Korea and informing relevant policies and academic research.¹⁵ Conducted biennially since 2006, the KLoSA publicly released data from its 9th wave conducted in 2022. The study population comprises Korean citizens aged 45 years and older residing in general households, excluding those living in institutions or on islands for convenience. The initial sampling frame utilized enumeration districts from the 2005 Population and Housing Census. The first survey in 2006 established a panel of 10 254 individuals, with 920 new panelists added from the 5th wave onward. For the present study, inclusion criteria were: (1) aged 65 years or older, (2) classified as frail according to the operational definition derived from KLoSA frailty-related variables, and (3) having complete data for all variables included in the analysis. Exclusion criteria were: (1) residing in long-term care facilities or other institutions, (2) missing data on any key study variables, and (3) being classified as non-frail or disabled.

Of the 6057 participants in the 9th wave dataset, 447 community-dwelling frail older adults met the selection criteria and were included in the final analysis.

Research Variables

Frailty

Frailty was defined based on criteria proposed by Kim and Sun,¹⁴ identifying participants as frail if they met at least 2 out of 3 indicators: weakness, exhaustion, and isolation. Weakness was measured by grip strength, with thresholds of ≤24 kg for men and ≤15 kg for women. Exhaustion was assessed through responses to 2 questions: (1) “In the past week, did you feel that everything required a lot of effort?” and (2) “In the past week, did you feel you could not get going?” Participants answering “3-4 days” or “5-7 days” to at least 1 question were classified as exhausted. Isolation was identified if participants reported no participation in any group or social activities. The validity of this frailty classification has been robustly supported by previous research¹⁴ demonstrating predictive validity, with frail individuals showing significantly higher risks for disability, institutionalization, and mortality. In validation studies, the classification yielded strong discriminative performance (AUC = .83), with a sensitivity of 70% and specificity of 83%. Longitudinal analyses further demonstrated that frail older adults had approximately 5.5 times greater odds of institutionalization and 3.2 times greater odds of mortality compared to non-frail counterparts.

Subjective Health Status

SHS was assessed through the question, “How would you rate your subjective health status?” (originally in Korean). Response options were: “Best,” “Very good,” “Good,” “Fair,” and “Poor.” Scores were coded on a 5-point scale, with higher scores indicating better perceived health.

Socioeconomic and Demographic Characteristics

Variables for socioeconomic and demographic characteristics included age, sex, education level, subjective socioeconomic status, spouse status, economic satisfaction, and life satisfaction. Age was categorized into 3 groups: 65 to 74, 75 to 84, and ≥85 years. Gender was classified into men and women. Educational level was categorized as ≤Elementary school, Middle school, High school, or ≥College. Subjective socioeconomic status was categorized into 3 levels: high, middle, and low. Spouse status was recategorized as “with spouse” for currently married individuals and “without spouse” for those in other statuses (separated, divorced, or widowed). Economic satisfaction and life satisfaction were each assessed using a single-item scale ranging from 0 to 100, with higher scores indicating greater perceived satisfaction.

Health and Lifestyle Characteristics

Variables related to health and lifestyle included physical activity at least once a week, current smoking and alcohol consumption, number of chronic diseases, cognitive function, depression scores, activities of daily living (ADL), and instrumental activities of daily living (IADL). Physical activity (at least once a week) was assessed using data directly from the Korean Longitudinal Study of Aging (KLoSA). Respondents answering “Yes” to the question, “Do you usually exercise at least once a week?” were classified as engaging in physical activity at least once weekly, while those answering “No” were classified as not engaging in weekly physical activity. Current smoking and alcohol consumption statuses were categorized as “yes” for those currently using tobacco or alcohol, and “no” otherwise.

Cognitive function was assessed using a categorized version of the Korean Mini-Mental State Examination (K-MMSE) scores provided by KLoSA. The K-MMSE consists of 19 items assessing orientation, memory, attention, and calculation, identifying object purposes, repetition, and command performance. Total scores range from 0 to 30, with higher scores indicating better cognitive function. Scores were categorized as follows: ≤17 indicated suspected dementia, 18 to 23 indicated cognitive impairment, and ≥24 indicated normal cognitive function. Original data coded cognitive function as 1 (suspected dementia), 2 (cognitive impairment), and 3 (normal). Depression scores utilized the Korean version of the Center for Epidemiologic Studies-Depression Scale (CES-D) Anderson form CES-D10, directly provided by KLoSA. This scale measures depressive symptoms experienced over the past week using 10 items scored as 0 (“rarely or none of the time,” “some of the time”) and 1 (“much of the time,” “most or all of the time”). Scores range from 0 to 10, with higher scores indicating more severe depressive symptoms. ADL and IADL scores were also directly adopted from the KLoSA data. ADL consists of 7 items assessing the need for assistance in changing clothes, washing face/brushing teeth/washing hair, bathing/showering, eating, leaving the room, using the toilet, and managing bowel and bladder control. ADL scores range from 0 to 7, with higher scores indicating greater dependency in daily activities. IADL comprises 10 items assessing the need for assistance in grooming, housework, meal preparation, laundry, short-distance travel, transportation use, shopping, managing finances, using the telephone, and medication management. IADL scores range from 0 to 10, with higher scores indicating greater dependency in instrumental daily activities.

Data Analysis

Data analysis was conducted using SPSS/WIN 26.0 (IBM Corp., Armonk, NY, USA). Complex sample analysis was employed after creating a complex sample design file with weights applied, using stratification and cluster variables from the 2022 KLoSA sample design. Descriptive statistics included unweighted frequencies, weighted percentages, weighted means, and standard errors. Unadjusted (univariate) associations between SHS and participant characteristics were examined using Complex Samples GLM (CSGLM). Variables with P < .05 were considered candidates for the multivariable model, and these were entered into a multivariable CSGLM to estimate adjusted associations with SHS.

Ethical Considerations

As a secondary data analysis, this study was exempted from review by the Institutional Review Board (IRB) of the researchers’ institution (IRB No. JBNU 2024-12-006). Approval for data use was obtained from the KLoSA website, and anonymized data were provided according to their data sharing procedures.

Results

Participant Characteristics

The age distribution of participants was as follows: 65 to 74 years (27.1%), 75 to 84 years (46.8%), and 85 years or older (26.1%), with a mean age of 79.1 years. Of the participants, 199 (43.3%) were men and 248 (56.7%) were women. Most participants had completed elementary education or lower (60.8%), followed by middle school graduates (15.9%), high school graduates (15.3%), and college graduates or higher (8.0%). Regarding subjective socioeconomic status, 254 (57.3%) identified as low, 185 (40.1%) as middle, and 8 (2.6%) as high. Participants with spouses numbered 267 (58.4%), regular exercisers were 134 (30.1%), current smokers were 31 (7.4%), and alcohol consumers were 74 (18.9%). The average number of chronic diseases was 1.83. Dementia was diagnosed in 17 participants (3.1%), and cognitive impairment in 6 (0.8%). Mean depression scores were 2.82 ± 0.15 (out of 10), mean ADL scores were 0.24 ± 0.04 (out of 7), mean IADL scores were 1.40 ± 0.14 (out of 10), economic satisfaction averaged 46.75 ± 1.54 (out of 100), life satisfaction averaged 54.95 ± 1.35 (out of 100), and subjective health status averaged 2.48 ± 0.04 (out of 5; Table 1).

Table 1.

Subjective Health Status Level and Participants’ Characteristics (N = 447).

Characteristics	Categories	%^†	M ± SE
Age (years)	65-74	27.1	79.1 ± 0.5
	75-84	46.8
	≥85	26.1
Gender	Men	43.3
	Women	56.7
Education level	≤Elementary school	60.8
	Middle school	15.9
	High school	15.3
	≥College	8.0
Subjective socioeconomic status	Low	57.3
	Middle	40.1
	High	2.6
Spouse status	With	58.4
	Without	41.6
Economic satisfaction score			46.75 ± 1.54
Life satisfaction score			54.95 ± 1.35
Physical activity at least once a week	Yes	30.1
	No	69.9
Current smoking	Yes	7.4
	No	92.6
Current alcohol consumption	Yes	18.9
	No	81.1
Number of chronic diseases			1.83 ± 0.59
Cognitive function	Normal	96.1
	Cognitive impairment	0.8
	Suspected dementia	3.1
Depression score			2.82 ± 0.15
ADL			0.24 ± 0.04
IADL			1.40 ± 0.14
Subjective health status score			2.48 ± 0.04

ADL = activities of daily living; IADL = instrumental activities of daily living; M = mean; SE = standard error.

†

Weighted %.

Differences in Subjective Health Status by Participant Characteristics

Significant differences in subjective health status scores were observed based on age, gender, educational level, subjective socioeconomic status, spouse status, physical activity at least once a week, alcohol consumption, number of chronic diseases, cognitive function, depression scores, ADL, IADL, economic satisfaction, and life satisfaction. SHS was higher among those aged 65 to 74 years (2.62 ± 0.10) than those aged 85 or older (2.32 ± 0.07; F = 3.45, P = .035). Men (2.60 ± 0.07) reported higher SHS than women (2.39 ± 0.04; F = 5.99, P = .014). SHS was lower among those with elementary education or lower (2.37 ± 0.05) compared to college graduates or higher (2.90 ± 0.18; F = 3.59, P = .013). Participants identifying as high socioeconomic status (3.22 ± 0.31) reported higher SHS than those identifying as middle (2.69 ± 0.06) or low (2.30 ± 0.05; F = 13.69, P < .001). Higher SHS was observed among participants with spouses (2.55 ± 0.06) compared to those without (2.38 ± 0.05; F = 4.56, P = .033), regular exercisers (physical activity at least once a week; 2.64 ± 0.08) compared to non-exercisers (2.41 ± 0.05; F = 5.76, P = .016), and current alcohol consumers (2.82 ± 0.10) compared to non-consumers (2.40 ± 0.04; F = 14.57, P < .001). Normal cognitive function was associated with higher SHS (2.50 ± 0.04) compared to cognitive impairment (1.73 ± 0.17) or dementia (1.84 ± 0.10; F = 28.51, P < .001). Negative correlations were found between SHS scores and the number of chronic diseases (r = −.23, P < .001), depression scores (r = −.21, P < .001), ADL scores (r = −.21, P < .001), and IADL scores (r = −.30, P < .001). Positive correlations existed between SHS scores and economic satisfaction (r = .29, P < .001) and life satisfaction (r = .32, P < .001; Table 2).

Table 2.

Unadjusted Associations Between Subjective Health Status and Participant Characteristics (N = 447).

Characteristics	Categories	M ± SE	F^† or r	P	Post-hoc^§
Age (years)	65-74^a	2.62 ± 0.10	3.45	.035	a > c
	75-84^b	2.48 ± 0.06
	≥85^c	2.32 ± 0.07
Gender	Men	2.60 ± 0.07	5.99	.014
	Women	2.39 ± 0.04
Education level	≤Elementary school^a	2.37 ± 0.05	3.59	.013	a < d
	Middle school^b	2.59 ± 0.10
	High school^c	2.58 ± 0.15
	≥College^d	2.90 ± 0.18
Subjective socioeconomic status	Low^a	2.30 ± 0.05	13.69	<.001	a,b < c
	Middle^b	2.69 ± 0.06
	High^c	3.22 ± 0.31
Spouse status	Yes	2.55 ± 0.06	4.56	.033
	No	2.38 ± 0.05
Economic satisfaction score			.29^‡	<.001
Life satisfaction score			.32^‡	<.001
Physical activity at least once a week	Yes	2.64 ± 0.08	5.76	.016
	No	2.41 ± 0.05
Current smoking	Yes	2.64 ± 0.19	.84	.361
	No	2.46 ± 0.04
Current alcohol consumption	Yes	2.82 ± 0.10	14.57	<.001
	No	2.40 ± 0.04
Number of chronic diseases			−.23^‡	<.001
Cognitive function	Normal	2.50 ± 0.04	28.51	<.001	a > b,c
	Cognitive impairment	1.73 ± 0.17
	Suspected dementia	1.84 ± 0.10
Depression score			−.21^‡	<.001
ADL			−.21^‡	<.001
IADL			−.30^‡	<.001

ADL = activities of daily living; IADL = instrumental activities of daily living.

a,b,c

Indicate subgroup categories used for post-hoc comparison.

†

Wald F-statistical value.

‡

r-statistical value.

Bonferroni correction.

Factors Influencing Subjective Health Status

A Complex Sample General Linear Model analysis was conducted using variables significantly associated with SHS from univariate analysis. Significant predictors included physical activity at least once a week (B = 0.17, P = .040), cognitive impairment (B = −0.63, P < .001), number of chronic diseases (B = −0.07, P = .032), depression scores (B = −0.03, P = .033), IADL scores (B = −0.06, P < .001), and life satisfaction scores (B = 0.01, P = .036; Table 3).

Table 3.

Adjusted Associations with Subjective Health Status (N = 447).

Characteristics categories		B	SE	t	P	95% CI
Characteristics categories		B	SE	t	P	Lower	Upper
Age (years)	≥85	0.07	0.11	0.66	.508	−0.14	0.28
	75-84	0.01	0.10	0.07	.940	−0.19	0.20
	65-74
Gender	Men	0.04	0.09	0.44	.663	−0.14	0.22
	Women
Education level	≥College	0.09	0.21	0.44	.659	−0.31	1.15
	High school	−0.02	0.14	−0.17	.868	−0.31	0.96
	Middle school	0.14	0.09	1.43	.155	−0.05	2.10
	≤Elementary school
Subjective socioeconomic status	High	0.57	0.35	1.63	.104	−0.12	1.25
	Middle	0.14	0.08	1.85	.065	−0.01	0.29
	Low
Spouse status	Yes	0.02	0.07	0.31	.754	−0.12	0.16
	No
Economic satisfaction score		0.01	0.01	1.04	.297	−0.01	0.01
Life satisfaction score		0.01	0.01	2.11	.036	0.01	0.01
Physical activity at least once a week	Yes	0.17	0.08	2.07	.040	0.01	0.32
Physical activity at least once a week	No
Alcohol	Yes	0.17	0.12	1.35	.178	−0.08	0.41
Consumption	No
Cognitive function	Suspected dementia	−0.16	0.12	−1.31	.190	−0.39	0.08
	Cognitive impairment	−0.63	0.07	−8.47	<.001	−0.78	−0.48
	Normal
Number of chronic diseases		−0.07	0.03	−2.16	.032	−0.14	−0.01
Depression score		−0.03	0.02	−2.14	.033	−0.06	−0.01
ADL		0.02	0.03	0.52	.602	−0.05	0.08
IADL		−0.06	0.02	−3.84	<.001	−0.09	−0.03

ADL = activities of daily living; IADL = instrumental activities of daily living.

Discussion

This study aimed to identify factors influencing subjective health status (SHS) among frail community-dwelling older adults, providing foundational data for intervention strategies to prevent frailty progression and promote health. The mean SHS score of frail older adults in this study was 2.48 (out of 5), similar to previous findings by Yim and No¹⁷ (2.0 out of 5) and Ryu¹⁸ (2.65 out of 5), but lower than that of non-frail older adults reported by Ha and Park¹⁹ (3.08 out of 5). This supports the notion that health status significantly affects SHS, emphasizing the importance of interventions that help frail older adults perceive their health positively, thus fostering healthier behaviors.^6,20

Our results showed that physical activity at least once a week, cognitive impairment, number of chronic diseases, depression scores, IADL, and life satisfaction significantly influenced SHS. These findings suggest that SHS among frail older adults is shaped by complex interactions among physical, cognitive, emotional, and functional factors rather than a single health determinant.^7,21 Specifically, regular exercisers perceived higher SHS, aligning with García Bengoechea et al,⁵ who found exercise participation enhances autonomy and reduces social isolation, positively impacting SHS. Physical activity thus serves as a key strategy to simultaneously enhance physical function and psychological well-being, highlighting its broader role in interventions for frail older adults.

Additionally, cognitive function partially influenced SHS. Participants with cognitive impairment had significantly lower SHS scores than cognitively normal participants; however, no significant difference was found compared to those diagnosed with dementia. This suggests that early cognitive decline distinctly affects SHS, whereas moderate to severe cognitive impairment might diminish self-awareness, affecting health self-assessment.^22,23 Prior studies note that mild cognitive impairment is associated with negative health perception due to preserved awareness of functional decline, whereas more severe impairment reduces the individual’s ability to accurately evaluate health status.^24,25 Thus, interpreting SHS among frail older adults requires careful consideration of cognitive functioning levels, potentially incorporating objective health measures or proxy reports alongside subjective assessments.

Increasing age is linked to a higher prevalence of chronic diseases; in South Korea, approximately 88.5% of adults aged 65 or older have chronic conditions, averaging 2.5 diseases per person, with many experiencing multimorbidity.²⁶ Consistent with Song et al,²⁷ this study found a negative association between chronic disease burden and SHS. Multimorbidity contributes to symptoms such as pain, fatigue, sleep disturbances, and medication side effects, negatively impacting overall health perception.^28,29 Hence, SHS among frail older adults reflects accumulated functional declines and self-management challenges, necessitating integrated health management approaches beyond single-disease care.

Declines in ADL and IADL commonly accompany aging and chronic disease.³⁰ The current study found that greater IADL impairment was associated with lower SHS scores, supporting findings by Lee et al²² that functional limitations affect frailty and perceived health. IADL limitations among frail older adults predict future health deterioration, including increased dependency and risk of falls, making IADL an important early indicator for SHS changes.³¹ Thus, community-based care should integrate emotional support and early rehabilitation strategies to maintain functional independence.

Older adults’ physical limitations and chronic diseases often result in reduced activity, social isolation, and depression, a major predictor of frailty.^32,33 This study revealed a significant negative relationship between depression scores and SHS, corroborating previous studies linking depression with decreased life satisfaction, pessimism, and reduced self-efficacy.³² SHS thus encompasses not only physical health but psychological stability and autonomy. Interventions for frail older adults should therefore address depressive symptoms through tailored mental health services and continuous monitoring.

Life satisfaction significantly influenced SHS, aligning with research suggesting that higher life satisfaction positively correlates with better perceived health.^2,8 Even with reduced physical functioning, maintaining high life satisfaction can buffer negative health perceptions, emphasizing SHS as a comprehensive psychosocial indicator.³⁴ Thus, interventions for frail older adults should integrate psychosocial factors such as emotional support, leisure activities, and social connectedness to enhance health perception and overall quality of life.

SHS, influenced by physical, cognitive, emotional, functional, and social factors, serves as a comprehensive indicator of frail older adults’ health experiences. It has practical utility as an early-warning tool for health risk identification in community settings. Current frailty management primarily focuses on physical functions through exercise and nutrition; however, findings from this study highlight the importance of integrated interventions addressing emotional, social, and cognitive dimensions. Due to its simplicity and non-invasive nature, SHS can be effectively incorporated into routine community assessments, enabling early, personalized intervention plans to prevent frailty progression. While this study focused exclusively on frail older adults, including non-frail counterparts as a comparison group could yield additional insights into the distinct determinants and trajectories of SHS. Such comparative analyses would require a different analytical framework and were beyond the scope of the present study; however, this has been noted in the research recommendations section as an important direction for future work.

Despite its comprehensive approach, this study has limitations. First, using cross-sectional data from the 2022 KLoSA restricts causal inference between SHS and patient factors, necessitating longitudinal studies for clearer causal analysis. Second, reliance on self-reported data could introduce response bias, especially with cognitive impairments. Future studies should integrate objective health metrics to enhance SHS validity.

Conclusion

This study identified significant factors influencing SHS among frail older adults, including regular exercise, cognitive impairment, chronic diseases, depression, IADL, and life satisfaction. Findings confirm SHS as a multidimensional health indicator encompassing physical, cognitive, emotional, and social components. Given its sensitivity to early functional decline and motivational role in health behaviors, SHS should be leveraged in community-based interventions. Future longitudinal research and interventions targeting SHS improvement are recommended for better frailty management and policy implementation.

Supplemental Material

sj-docx-1-inq-10.1177_00469580251384786 – Supplemental material for Multidimensional Factors Associated with Subjective Health among Community-Dwelling Frail Older Adults: A Population-Based Study

Supplemental material, sj-docx-1-inq-10.1177_00469580251384786 for Multidimensional Factors Associated with Subjective Health among Community-Dwelling Frail Older Adults: A Population-Based Study by Hyuk Joon Kim and Hye Young Kim in INQUIRY: The Journal of Health Care Organization, Provision, and Financing

Footnotes

ORCID iDs

Hyuk Joon Kim

Hye Young Kim

Consent to Participate

Written informed consent to participate in the study was obtained from all participants.

Author Contributions

Conceptualization, HJK, and HYK; methodology, HJK, and HYK; formal analysis, HJK; investigation, and data curation, HJK; writing-original draft, HJK, and HYK; writing—review and editing, HJK, and HYK; visualization, HJK. All authors read and approved the final manuscript.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Supplemental Material

Supplemental material for this article is available online.

References

Statistics Korea. Projected population by major age groups [Internet]. Daejeon: Statistics Korea; 2025 [cited 2025 Apr 11]. https://kosis.kr/statHtml/statHtml.do?sso=ok&returnurl=https%3A%2F%2Fkosis.kr%3A443%2FstatHtml%2FstatHtml.do%3FtblId%3DDT_1BPA003%26language%3Den%26orgId%3D101%26

Lee

Repkine

Determinants of health status and life satisfaction among older South Koreans. Healthcare. 2024;12(11):1124. doi:10.3390/healthcare12111124

Arai

Ouchi

Toba

, et al. Japan as the front-runner of super-aged societies: perspectives from medicine and medical care in Japan. Geriatr Gerontol Int. 2015;15(6):673-687. doi:10.1111/ggi.12450

Clegg

Young

Iliffe

Rikkert

Rockwood

Frailty in elderly people. Lancet. 2013;381(9868):752-762. doi:10.1016/S0140-6736(12)62167-9

García Bengoechea

Doyle

Forte

, et al. Psychosocial effects of a behavioural augmentation of existing public physical activity programs for middle-aged and older adults in Ireland. PLoS One. 2025;20(3):e0318911. doi:10.1371/journal.pone.0318911

Park

Chung

Self-rated health as a predictor of mortality according to cognitive impairment: findings from the Korean Longitudinal Study of Aging (2006-2016). Epidemiol Health. 2021;43:e2021021. doi:10.4178/epih.e2021021

Pilleron

Le Goff

Ajana

, et al. Self-rated health and frailty in older adults from the population-based three-city Bordeaux cohort. Gerontology. 2022;68(7):755-762. doi:10.1159/000518864

Salminen

Luther-Tontasse

Koskenniemi

, et al. Factors contributing to self-rated health in community-dwelling independent 75-year-old Finns: A population-based cross-sectional cohort study. BMC Geriatr. 2025;25(1):141. doi:10.1186/s12877-025-05794-z

Bae

Nam

, et al. The association between self-rated health, number of family members, and cognitive function in community-dwelling older adults: mediating role of depression. PLoS One. 2024;19(7):e0306907. doi:10.1371/journal.pone.0306907

10.

Kwon

Lee

HR.

The influence of depression and perceived health status on health promotion behavior of community dwelling frail elderly. J Korea Acad Ind Coop Soc. 2020;21(12):742-751. doi:10.5762/KAIS.2020.21.12.742

11.

Rogowska

Morouço

Editorial: motivations for physical activity. Front Psychol. 2024;15:1437220. doi:10.3389/fpsyg.2024.1437220

12.

Park

YJ.

Health promotion behavior, perceived health status, social participation and empowerment in frail elderly receiving home visiting services. J Korean Public Health Nurs. 2017;31(2):244-256. doi:10.5932/JKPHN.2017.31.2.244

13.

Han

Jang

Factors influencing the stages of frailty among Korean older adults focusing on objective and subjective social isolation. BMC Geriatr. 2022;22(1):488. doi:10.1186/s12877-022-03179-0

14.

Kim

Sun

WD.

A frailty instrument to predict disability, institutionalization, and mortality: findings from the living profiles of older people survey. J Korean Gerontol Soc. 2015;35(2):451-474.

15.

Korea Employment Information Service. Korean Longitudinal Study of Aging (KLoSA), 9th wave, 2022 [Internet]. Korea Employment Information Service; 2023. Accessed May 13, 2025. https://survey.keis.or.kr/klosa/klosadownload/List.jsp

16.

von Elm

Altman

Egger

Pocock

Gøtzsche

Vandenbroucke

JP.

The strengthening the reporting of observational studies in epidemiology (STROBE) statement: guidelines for reporting observational studies. Lancet. 2007;370(9596):1453-1457.

17.

Yim

KH.

The effects of related factors on health-related quality of life for the frail elderly. J Korean Acad Community Health Nurs. 2010;21(1):12-20. doi:10.12799/jkachn.2010.21.1.12

18.

Ryu

The impact of physical functionality and activity level on the self-rated health status of older adults living alone: an analysis of the mediating effect of social engagement. Geriatr Nurs. 2025;63:464-469. doi:10.1016/j.gerinurse.2025.03.035

19.

Park

YH.

Health status and factors related to health behaviors of older adults using a senior center. Korean J Adult Nurs. 2015;27(4):428-437. doi:10.7475/kjan.2015.27.4.428

20.

YH.

The relationships among the physical competence, subjective health status, and health promoting behavior of elderly participating in health activity program. J Digit Converg. 2016;14(12):571-581. doi:10.14400/jdc.2016.14.12.571

21.

Cheng

Yan

Sociodemographic, health-related, and social predictors of subjective well-being among Chinese oldest-old: a national community-based cohort study. BMC Geriatr. 2021;21(1):124. doi:10.1186/s12877-021-02071-7

22.

Lee

Chung

Song

Prevalence and associated factors of cognitive frailty in community-dwelling older adults: results from the Korean Longitudinal Study of aging. Int J Older People Nurs. 2023;18(6):e12576. doi:10.1111/opn.12576

23.

Guo

Luo

Gao

Social isolation and cognitive decline among older adults with depressive symptoms: prospective findings from the China Health and Retirement Longitudinal Study. Arch Gerontol Geriatr. 2021;95:104390. doi:10.1016/j.archger.2021.104390

24.

Scholz

Donders

Cognitive complaints in older adults: Relationships between self and informant report, objective test performance, and symptoms of depression. Aging Neuropsychol Cogn. 2024;31(2):263-278. doi:10.1080/13825585.2022.2144617

25.

De Wit

Goldstein

Saurman

Rodriguez

Vickers

KL.

Discrepancies between self- and informant-ratings of functional abilities and objective cognition: predictors of bias in mild cognitive impairment. J Int Neuropsychol Soc. 2024;30(5):448-453. doi:10.1017/S1355617723011463

26.

Ministry of Health and Welfare. National survey of older Koreans 2017. Sejong (KR): Korea Institute for Health and Social Affairs; 2017. Report No. 11-1352000-000672-12.

27.

Song

Liu

U-shaped association between sleep duration and frailty in Chinese older adults: a cross-sectional study. Front Public Health. 2025;12:1464734. doi:10.3389/fpubh.2024.1464734

28.

Nguyen

Giang

Bui

Nguyen

NT.

Prevalence of functional disability and associated factors among older people in Vietnam: a secondary data analysis. BMJ Open. 2025;15(3):e093566. doi:10.1136/bmjopen-2024-093566

29.

Williams

Egede

LE.

The association between multimorbidity and quality of life, health status and functional disability. Am J Med Sci. 2016;352(1):45-52. doi:10.1016/j.amjms.2016.03.004

30.

Arias

Mirza

Fischer

Preliminary efficacy of an OT intervention to prevent functional decline among older adults with chronic diseases. Innov Aging. 2024;8(Supplement_1):1266-1267. doi:10.1093/geroni/igae098.4050

31.

Kojima

Iliffe

Jivraj

Walters

Association between frailty and quality of life among community-dwelling older people: a systematic review and meta-analysis. J Epidemiol Community Health. 2016;70(7):716-721. doi:10.1136/jech-2015-206717

32.

Zhang

Wang

Sun

, et al. The effect of depressive symptoms on the risk of cancer in middle-aged and elderly Chinese—a cross-sectional survey. Lancet Reg Health West Pac. 2025;55:101404. doi:10.1016/j.lanwpc.2024.101404

33.

Makizako

Shimada

Doi

, et al. Physical frailty predicts incident depressive symptoms in elderly people: prospective findings from the obu study of health promotion for the elderly. J Am Med Dir Assoc. 2015;16(3):194-199. doi:10.1016/j.jamda.2014.08.017

34.

Martyr

Nelis

Quinn

Lamont

Henderson

, et al. Living well with dementia: a systematic review and correlational meta-analysis of factors associated with quality of life, well-being and life satisfaction in people with dementia. Psychol Med. 2018;48(13):2130-2139. doi:10.1017/S0033291718000405

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