Determinants of Quality of Life in Older Adults: The Role of Sarcopenia, Physical Fitness, and Lifestyle Factors

Abstract

To examine the relationship between the applicability of the Sarcopenia & Quality of Life (SarQoL) questionnaire and physical fitness factors including living environment, body composition, and exercise function of individuals aged over 60 years were analyzed. The study included 551 older adults (129 men, 422 women) aged 60–100 years, residing in South Korea, and without serious diseases, disabilities, or physical activity limitations. Demographics, health indicators, living conditions, SarQoL survey results, and physical fitness were assessed. Group differences were evaluated using one-way ANOVA with Tukey’s post hoc test. Hierarchical regression analysis explored the relationship between SarQoL scores and various factors, and multiple logistic regression analyzed the association between SarQoL and exercise variables. Statistical significance was set at p < 0.05. Sex (B, 0.200; t, 2.233; p < 0.001), age (B, −0.031; t, −6.574; p < 0.001), education level (B, −0.110; t, 3.067; p = 0.002), and regular physical activity influenced SarQoL scores. Physical fitness measures were significantly correlated with SarQoL scores. Additionally, conditions such as diabetes, sleep disorders, and sarcopenia affected SarQoL outcomes. High SarQoL in older adults is associated with higher educational attainment, presence of medical conditions, and improved physical fitness. This underscores the complex interplay of physical and mental health in the aging process and highlights the importance of preventing and managing sarcopenia to improve the quality of life for older adults.

1. Introduction

As the global population ages, the prevalence of sarcopenia has increased, imposing substantial burdens on healthcare and social security systems [1]. Sarcopenia arises from interacting biological aging processes together with socio-demographic and lifestyle determinants [2]. Since 2016, sarcopenia has been listed in the International Statistical Classification of Diseases and Related Health Problems (ICD-10-CM, code M62) [3]. Clinically, sarcopenia is associated with higher risks of morbidity, mortality, falls, physical disability, and poorer health-related quality of life (HRQoL) [4]. For disease-specific evaluation of HRQoL in sarcopenia, the Sarcopenia & Quality of Life (SarQoL) questionnaire is recommended [5]. Prior studies show that HRQoL decrements among individuals with sarcopenia are most evident in domains linked to physical function and mobility [6,7].

The SarQoL questionnaire—developed in 2015—remains the only validated sarcopenia-specific HRQoL tool applicable to older adults across diverse settings [5,8]. Cross-cultural versions have demonstrated acceptable structural validity and psychometric performance in older populations with sarcopenia [9], and SarQoL has been adopted in both epidemiological and interventional studies worldwide. Nonetheless, proposed SarQoL cut-points for screening vary (≈52.4–60 points) with only moderate agreement across studies [10,11]. Moreover, while HRQoL differences by sarcopenia status are well documented, fewer studies have quantified how performance-based physical function (e.g., timed up-and-go, chair sit-and-reach, ankle plantarflexion/dorsiflexion strength), together with living-environment factors and body composition, relates to SarQoL after adjustment for socio-demographic characteristics and comorbidities. This evidence gap is particularly relevant in Asian community-dwelling cohorts where AWGS-based criteria are commonly used [12].

Therefore, this study examined community-dwelling older adults (≥60 years) and evaluated associations between SarQoL scores and (i) socio-demographic characteristics and comorbidities, (ii) body composition, and (iii) performance-based physical fitness. We applied hierarchical (blockwise) modeling to isolate the independent contribution of physical-function measures beyond demographics, comorbidities, and body composition, and explored SarQoL both as a continuous score and by quartiles to facilitate clinical interpretability.

The following hypotheses are proposed accordingly. Performance-based physical fitness measures (timed up-and-go, chair sit-and-reach, and isometric ankle plantarflexion/dorsiflexion) are independently associated with SarQoL after adjustment for demographics, comorbidities, and body composition. A high level of education and regular physical activity are likely to be associated with SarQoL. Additionally, Diabetes and sleep disorders are likely to be associated with SarQoL.

2. Materials and Methods

2.1. Participants

This cross-sectional, community-based study recruited older adults aged 60–100 years who were independently ambulant and attended senior community centers, welfare centers, day-care centers in Incheon, Republic of Korea. All candidates received a standardized explanation of the study procedures and provided written informed consent before completing questionnaires and undergoing testing. We initially assessed 559 individuals; of these, excluded due to an acute illness or hospitalization within the previous 3 months (n = 2), due to moderate-to-severe cognitive impairment that precluded informed consent or reliable self-completion of questionnaires (n = 2), and cardiovascular, respiratory, or neuromuscular conditions that rendered physical testing unsafe (n = 1). An additional three candidates were excluded because the assessments were incomplete. Ultimately, 551 participants with complete data were included in the final analysis. Sarcopenia was classified using the Asian sarcopenia diagnostic criteria, as illustrated in Figure 1 [13]. Participants were assessed for sarcopenia according to the 2019 Asian Working Group for Sarcopenia (AWGS) diagnostic criteria. This included low muscle strength (less than 28 kg for men, less than 18 kg for women), low physical performance (5-repetition sit-to-stand [5RST] in 12 s or more, or Stable Performance and Posture Balance [SPPB] score of 9 or less), and low muscle mass (less than 7.0 kg/m² for men, less than 5.7 kg/m² for women, calculated as arm and leg skeletal muscle [ASM]/height²). Participants were classified as normal, possible sarcopenia, and sarcopenia (including severe sarcopenia). The definitions for sarcopenia were as follows: The possible sarcopenia group was defined by low muscle strength or physical performance; the sarcopenia group by low skeletal muscle mass, muscle strength, or physical performance; and severe sarcopenia by low skeletal muscle mass, muscle strength, and physical performance. Prior to the study’s initiation, all participants received a comprehensive explanation of the study’s objectives, method, and potential risks, and they were informed of their right to withdraw from the study at any time. Written informed consent was obtained from all participants, and the study was approved by the Institutional Bioethics Committee of Gachon University (approval date: 26 October 2024; approval number: 1044396-202301-HR-020-01). The research adhered to the principles outlined in the Declaration of Helsinki.

2.2. Measures

2.2.1. Demographic Characteristics

Participants’ demographic characteristics were obtained using the questionnaire from the Korea National Health and Nutrition Examination Survey (KNHANES), a type of sample survey conducted annually by the Ministry of Health and Welfare of the Republic of Korea. The variables studied were age, sex, family composition, family life, income, physical activity, and chronic diseases (hypertension, diabetes, sleep disorders, and dyslipidemia). Field assessments were conducted at three institutions. Each session consisted of two assessors (administrator/safety) and one recorder. Standard operating procedures training and pilot sessions prior to testing ensured inter-rater reliability. Examiners were responsible for posture correction, safety checks, and providing standard motivational prompts, while recorders handled raw data documentation and missing data checks. Any abnormal findings or situations requiring termination were immediately reported to the principal investigator.

2.2.2. Quality of Life (SarQoL)

The Korean-translated version [14] of the SarQoL questionnaire was employed to evaluate the quality of life of patients with sarcopenia. This instrument comprises questions designed to measure frequency or intensity on a Likert scale, with the exception of items 7, 14, and 22. The questionnaire is structured into seven domains: D1 (physical and mental health), D2 (exercise), D3 (body composition), D4 (functionality), D5 (daily life activities), D6 (leisure activities), and D7 (fear). Scores for each domain, as well as the overall questionnaire, are recorded on a scale from 0 to 100, where higher scores reflect a superior quality of life. Based on the scores, participants are divided into quartiles (0–24, 25–49, 50–74, and 75–100). The survey was conducted face-to-face by trained interviewers reading standardized instructions. Understanding was confirmed with 1–2 demonstration questions before responses, supplemented with large-print cards and repeated readings as needed. No formal cognitive assessment was performed, but responses with caregiver assistance were permitted if comprehension was insufficient. Investigators standardized procedures through pre-training and pilot studies, and immediately corrected omissions or contradictory responses on-site using a checklist.

2.2.3. Measurement of Body Composition and Physical Fitness Factors

Physical fitness assessments were conducted in the same location following the completion of the questionnaire. The measurements included body composition parameters such as height, weight, body fat mass, body mass index (BMI), appendicular skeletal muscle (ASM), calf circumference (CC), and blood pressure. The physical fitness tests were conducted using the following procedure (Figure 2).

• Hand grip strength (HG): A hand dynamometer (Takei Scientific Instruments Co. Ltd., Tokyo, Japan) was used for HG measurement. Participants received a brief demonstration and verbal instructions for the test. Adjustments were made as needed based on participants’ hand size. Measurements were taken with the participant standing with arms at their sides and elbows fully extended. Measurements were taken twice alternately without an intermediate rest period. Participants were instructed to exert maximum force for 3 s during each measurement. The maximum value was utilized for data analysis [15,16].
• Plantar and Dorsi flexion: Isometric muscle strength measurement of the ankle was performed using a modified method reported by Li et al. [17]. The microFET^®2 (Hoggan Scientific, LLC, Salt Lake City, UT, USA) was placed in close contact with the sole or top of the foot. Participants then applied force in the sole or top direction for approximately 5 s upon the start signal. Resistance was applied by the examiner to prevent knee flexion or rebound.
• Stand and sit: Participants sit on a chair without armrests (approximately 43 cm/17 inches high) and secure themselves against the wall for stability. Arms were crossed and held in front of the chest, maintaining a straight back. Using the arms to stand up was counted as “0 times.” The number of times the movement was performed correctly was counted. The participant repeated the action of sitting in the chair for 30 s and then standing up completely, and the number of times they stood up completely was measured. Additionally, even if the participant was only partially standing by the end of the 30 s, it was counted as one attempt [15].
• Chair sit and reach: Sit at the edge of the chair, extend one leg, and reach towards the toes with both hands while keeping the other foot flat. Maintain a 90° ankle angle, hold for 1–2 s, and measure the fingertip-to-toe distance twice, recording the best result (+ or −) [18,19].
• Timed up and go (TUG): Participants were instructed to stand up from an armless chair (height 46 cm), walk 3 m, turn direction at a cone-shaped marker, then walk back and sit down. They were told to walk at their normal pace, regardless of whether they wore shoes. Time was measured from when the participant’s buttocks left the chair upon standing until they returned to a seated position and their buttocks touched the seat. The test was performed consecutively twice, and the average of the millisecond scores was used for further analysis [20].
• Short Physical Performance Battery (SPPB): The SPPB consists of three tests: the standing balance test, the 4 m walk test, and the 5-time chair stand test. In the standing balance test, participants received 4 points if they could maintain each of the following positions for 10 s: feet together (1 point), semi-tandem (1 point), and tandem (2 points). For the 4 m walk test, participants were allowed two attempts to walk 4 m at their normal pace, with the shorter time recorded as their score. The use of assistive devices was permitted during the walking test. The five-time chair rise test scored the time taken to rise five times as quickly as possible with arms crossed over the chest. The total SPPB score ranged from 0 to 12 points [21,22].

2.3. Statistical Analysis

All statistical analyses were performed using SPSS version 26.0 (SPSS Corp., Armonk, NY, USA). Differences between groups were evaluated using a one-way analysis of variance, and Tukey’s test was used for post hoc analysis. To analyze the relationship between SarQoL and variables, hierarchical regression analysis was used with a priori block entry based on theory and clinical priority. Model 1 included demographic and disease variables, Model 2 included body composition, and Model 3 included functional fitness components. Multicollinearity was checked using VIF < 5 as the criterion. Finally, multiple logistic regression analysis was performed to analyze the association between SarQoL and exercise factors. All results are expressed as mean ± standard deviation and statistical significance was set at p < 0.05.

3. Results

3.1. SarQoL Quatiles and Participant Characteristics

Table 1. Demographic characteristics of the study participants.

Variables			1 (n = 44)		2 (n = 193)		3 (n = 211)		4 (n = 103)		Total (n = 551)		F	p
			Mean	±or %	Mean	±or %	Mean	±or %	Mean	±or %	Mean	±or %
Age (years)			82.27	5.78	78.85	7.78	74.55	7.26	72.76	7.77	76.35	7.98	28.574	<0.001 ***
Sex	Male		7	15.9	32	16.6	56	26.5	34	33.0	129	23.4	4.036	0.001 ***
	Female		37	84.1	161	83.4	155	73.5	69	67.0	422	76.6
Height (cm)			150.28	8.30	152.68	7.46	156.29	8.07	158.39	7.74	154.94	8.20	19.198	<0.001 ***
Weight (kg)			56.26	9.30	58.23	9.69	58.91	9.13	60.39	9.80	58.74	9.50	2.224	0.008 **
Appendicular Skeletal Muscle (kg)			6.09	1.43	6.34	1.34	6.66	1.38	6.89	1.49	6.54	1.41	5.410	<0.001 ***
Body fat mass (%)			20.66	7.01	21.66	7.26	19.43	6.06	19.01	6.02	20.21	6.64	5.140	<0.001 ***
Body Mass Index (kg/m2)			25.16	4.26	25.15	4.16	24.12	3.13	23.98	3.16	24.54	3.65	4.003	0.001 ***
Diabetes		Yes	16	36.4	60	31.1	51	24.2	18	17.5	145	26.3	3.246	0.002 **
		No	28	63.6	133	68.9	160	75.8	85	82.5	406	73.7
Hyperlipidemia		Yes	11	25.0	66	34.2	76	36.0	32	31.1	185	33.5	0.695	0.056
		No	33	75.0	127	65.8	135	64.0	71	68.9	366	66.5
Hypertension		Yes	25	56.8	104	53.9	108	51.2	40	38.8	277	50.2	2.481	0.006 **
		No	19	43.2	89	46.1	103	48.8	63	61.2	274	49.8
Sleep disorder		Yes	19	43.2	81	42.0	75	35.5	19	18.4	194	35.2	6.070	<0.001 ***
		No	25	56.8	112	58.0	136	64.5	84	81.6	357	64.8
Sarcopenia		Yes	40	90.9	138	71.5	93	43.1	30	29.1	344	60.6	38.838	<0.001 ***
		No	4	9.1	55	28.5	118	55.9	73	70.9	207	39.4
SarQoL		S Total	31.33	4.15	48.99	6.40	69.08	5.80	86.97	4.84	62.37	17.42	1501.662	<0.001 ***

mean ± SD. S Total, SarQoL score total. ** p < 0.01, *** p < 0.001.

illustrates the participants’ demographic characteristics. The ANOVA results of demographic characteristics showed that statistically significant differences by SarQoL score quartiles occurred for all variables except hyperlipidemia.

3.2. Determinants of SarQoL

The results of the hierarchical regression analysis of lifestyle factors affecting HRQoL and SarQoL are shown in

Table 2. Results for participant characteristics associated with SarQoL.

	Independent Variable	Model 1				Model 2
		B	β	t	p	B	β	t	p
A	(Constant)	5.111		12.896	<0.001 ***	4.536		10.953	<0.001 ***
	Sex	0.200	0.098	2.233	0.026 *	0.098	0.048	1.090	0.276
	Age	−0.031	−0.296	−6.574	<0.001 ***	−0.020	−0.185	−3.746	<0.001 ***
	Education level	0.110	0.144	3.067	0.002 **	0.095	0.125	2.729	0.007 **
	RPA	−0.258	−0.146	−3.532	<0.001 ***	−0.220	−0.125	−3.110	0.002 **
	Diabetes					−0.208	−0.110	−2.717	0.007 **
	Hyperlipidemia					0.034	0.019	0.451	0.652
	Hypertension					−0.027	−0.016	−0.380	0.704
	Sleep disorder					−0.235	−0.133	−3.327	0.001 ***
	Sarcopenia					−0.179	−0.216	−4.519	<0.001 ***
	F (p)	29.245 (<0.001 ***)				19.061 (<0.001 ***)
	R2	0.194				0.263
	adjR2	0.188				0.249

Significant difference, * p < 0.05, ** p < 0.01, *** p < 0.001; tested by Hierarchical regression analysis. A (dependent variable); Model 1, basic characteristics; Model 2, Model 1 + disease; RPA, Regular physical activity.

. In the analysis of Model 1 (basic characteristics), statistically significant results were obtained for sex (B = 0.200; t = 2.233; p < 0.001), age (B, −0.031; t, −6.574; p < 0.001), education level (B, −0.110; t, 3.067; p = 0.002), and periodic physical activity (B, −0.258; t, −3.532; p < 0.001). The analysis of Model 2 (Model 1 + disease) showed statistically significant results for age (B, −0.020; t, −3.746; p < 0.001), education level (B, 0.095; t, 2.729; p = 0.007), periodic physical activity (B, −0.220; t, −3.110; p = 0.002), diabetes (B, −0.208; t, −20717; p = 0.007), sleep disorders (B, −0.235; t, −3.327; p = 0.001), and sarcopenia (B, −0.179; t, −4.519; p < 0.001). The Durbin–Watson value of the model was found to be 0.557, and all values were found to be VIF 5 or less (Table 2).

3.3. Physical Fitness and SarQoL

Table 3. Results of hierarchical regression analysis for SarQoL and associated factors.

	Independent Variable	Model 1				Model 2				Model 3
		B	β	t	p	B	β	t	p	B	β	t	p
A	(Constant)	4.762		11.508	<0.001 ***	6.485		3.109	0.002 **	4.114		2.011	0.045 *
	Sex	0.147	0.074	1.647	0.100	−0.059	−0.03	−0.458	0.647	0.131	0.065	1.004	0.316
	Age	−0.022	−0.216	−4.269	<0.001 ***	−0.018	−0.175	−3.283	0.001 ***	−0.011	−0.104	−1.973	0.049 *
	Education level	0.076	0.102	2.211	0.028 *	0.048	0.065	1.373	0.170	0.009	0.012	0.260	0.795
	RPA	−0.191	−0.109	−2.658	0.008 **	−0.162	−0.092	−2.263	0.024 *	−0.122	−0.070	−1.758	0.079
	Diabetes	−0.219	−0.118	−2.936	0.003 **	−0.208	−0.112	−2.76	0.006 **	−0.182	−0.099	−2.509	0.012 *
	Sleep disorder	−0.245	−0.141	−3.473	0.001 ***	−0.218	−0.125	−3.084	0.002 **	−0.196	−0.113	−2.891	0.004 **
	Sarcopenia	−0.168	−0.204	−4.210	<0.001 ***	−0.175	−0.213	−4.071	<0.001 ***	−0.086	−0.105	−1.983	0.048 *
	Height					−0.016	−0.152	−1.196	0.232	−0.005	−0.049	−0.392	0.695
	Weight					0.033	0.381	2.020	0.044 *	0.014	0.163	0.879	0.380
	Body Fat Mass					−0.023	−0.177	−1.788	0.074	−0.010	−0.082	−0.844	0.399
	Body Mass Index					−0.064	−0.278	−1.654	0.099	−0.034	−0.147	−0.899	0.369
	Calf Circumference					0.015	0.056	0.787	0.431	0.018	0.067	0.976	0.330
	Timed up and go									−0.022	−0.155	−3.214	0.001 ***
	Chair sit and reach									0.009	0.136	2.888	0.004 **
	Plantar flexion									0.019	0.118	2.307	0.022 *
	F (p)	23.591 (<0.001 ***)				15.235 (<0.001 ***)				15.890 (<0.001 ***)
	R2	0.264				0.287				0.345
	adjR2	0.253				0.268				0.324

Significant difference, * p < 0.05, ** p < 0.01, *** p < 0.001; tested by Hierarchical regression analysis. A (dependent variable), Sarcopenia; Model 1, basic characteristics; Model 2, Model 1 + body composition; Model 3, Model 2 + fitness factors; RPA, Regular physical activity.

presents the SarQoL group classification and hierarchical regression analysis results for each variable. As a result of Model 1 (basic characteristics) analysis, statistically significant results were found for age (B, −0.22; t, −4.269; p < 0.001), educational level (B, 0.076; t, 2.211; p = 0.028), periodic physical activity (B, −0.191; t, −2.658; p = 0.008), diabetes (B, −0.219; t, −2.936; p = 0.003), sleep disorders (B, −0.245; t, −4.210; p = 0.001), and sarcopenia (B, −0.168; t, −4.210; p < 0.001). Model 2 (Model 1 + body position) analysis revealed statistically significant results for age (B, −0.018; t, −3.283; p < 0.001), periodic physical activity (B, −0.162 t, −2.263; p = 0.024), diabetes (B, −0.208; t, −3.084; p = 0.006), sleep disorders (B, −0.218; t, −3.084; p = 0.002), sarcopenia (B, −0.175; t, −4.071; p < 0.001), and weight (B, 0.033; t, 2.020; p = 0.044). Model 3 (Model 2 + physical fitness factors) analysis revealed statistically significant results for age (−0.018–1; t, −1.973; p = 0.049), diabetes (−0.182; t, −2.509; p = 0.012), sleep disorders (−0.196; t, −2.891; p = 0.004), sarcopenia (B, −0.086; t, −1.983; p = 0.048), TUG (B, −0.022; t, −3.214; p = 0.001), chair sit and reach (B, 0.009; t, 2.888; p = 0.004), and plantar flexion (B, 0.019; t, 2.307; p = 0.022). The Durbin-Watson value of the model was 0.673, and all values were below VIF 5 (Table 3).

3.4. SarQoL Stages and Physical Fitness

Table 4. Odd ratios (95% confidence interval) for physical fitness factors across SarQoL quartiles.

Variables Category		Exp(B)	OR (95% CI)		p
Hand grip	1	Reference
	2	0.996	0.923	1.075	0.918
	3	1.046	0.964	1.134	0.279
	4	1.093	1.002	1.193	0.045 *
Dorsal flexion	1	Reference
	2	1.06	0.936	1.201	0.359
	3	1.154	1.012	1.316	0.032 *
	4	1.212	1.053	1.396	0.007 **
Stand and sit	1	Reference
	2	0.992	0.917	1.073	0.843
	3	1.051	0.956	1.155	0.305
	4	1.034	0.916	1.166	0.591
Chair sit and reach	1	Reference
	2	1.004	0.972	1.037	0.808
	3	1.014	0.979	1.05	0.444
	4	1.041	1.001	1.083	0.045 *
Timed up and go	1	Reference
	2	1.006	0.949	1.066	0.844
	3	0.943	0.865	1.029	0.444
	4	0.873	0.757	1.007	0.062
SPPB	1	Reference
	2	1.330	1.143	1.549	<0.001 ***
	3	1.609	1.32	1.961	<0.001 ***
	4	1.671	1.259	2.217	<0.001 ***

Significant difference, * p < 0.05, ** p < 0.01, *** p < 0.001; tested by performing multiple logistic regression analysis. OR, odds ratio; CI, confidence interval; SPPB, SPPB score 1, SarQoL 0–25%; 2, SarQoL 26–50%; 3, SarQoL 51–75%; 4, SarQoL 76–100%.

illustrates the results of SarQoL and variables related to exercise function through multiple logistic regression analysis; significant results were found for the following variables: hand grip (4: B, 1.093; p = 0.045), dorsal flexion (3: B, 1.154; p = 0.032; 4: B, 1.212; p = 0.007), chair sit and reach (4: B, 1.041; p = 0.045), and SPPB (2: B, 1.330; p < 0.001; 3: B, 1.609; p < 0.001; 4: B, 1.671; p < 0.001).

4. Discussion

This study explored the association between SarQoL scores and various demographic and clinical factors among older adults aged 60–100 years in South Korea. The SarQoL score, which evaluates the impact of sarcopenia on quality of life, encompasses dimensions such as physical and mental health (D1), locomotion (D2), body composition (D3), functionality (D4), activities of daily living (D5), and leisure activities (D6). The results revealed significant differences in SarQoL scores across quartiles. Additionally, variations in height and weight were noted, with younger age groups generally exhibiting higher average height and weight. Conversely, BMI and muscle mass tended to decrease with age. These results contrast with those of Liao et al., who found that higher BMI was associated with greater muscle mass [19] but align with Lee et al.’s findings that grip strength decreased with increasing BMI [20]. Furthermore, SarQoL showed strong associations with education, regular physical activity, diabetes, and sleep disorders, while body composition and functional fitness (TUG/chair sit and reach/plantar flexion/dorsiflexion) were independently related. Weight loss in older adults can adversely affect their health, leading to conditions such as reduced appetite, muscle loss, dehydration, and cachexia. Consequently, further research is essential to identify key predictors for the health care of older adults.

We systematized comprehension assistance and quality control for QoL assessments in elderly samples (face-to-face administration, demonstration items, large-font cards, repeated reading, caregiver assistance when needed). While these procedures mitigate measurement errors and expand the range of possible responses, caregiver-assisted responses carry the potential bias of under- or overestimating an individual’s perceived quality of life. To minimize this, we performed indicator variable adjustment and sensitivity analysis (excluding caregiver-assisted/low-cognitive participants), and core associations remained robust overall. However, residual misclassification cannot be ruled out, and future studies require standardized cognitive screening and mode effect evaluation (self-report vs. face-to-face comparison, retest reliability).

In addition, Geerinck et al. [10] identified a SarQoL threshold value of 52.4 points (ROC curve, sensitivity 64.7%, specificity 80.5%) in 309 older adults aged 65 years and older. Guillamón-Escudero et al. [11] found that the mean score of SarQoL was 75.5 in men and 72.6 in women among 202 participants aged 65 years and older, with a high prevalence of sarcopenia in the domains of locomotion (D2), functionality (D4), and activities of daily living (D5). The risk of sarcopenia was particularly high when D2 scores were below 60. Therefore, subjects in the second quartile of this study should be considered high risk, and the association between physical activity and sarcopenia may be further emphasized.

In this study, hierarchical regression showed that education, regular physical activity, body composition, and performance-based fitness (timed up-and-go, chair sit-and-reach, and isometric ankle plantarflexion) were each independently associated with SarQoL after blockwise adjustment. Beyond statistical associations, several biological pathways plausibly link skeletal muscle health to health-related quality of life. First, sarcopenia is accompanied by chronic low-grade inflammation (elevated IL-6, CRP, TNF-α), which accelerates muscle protein breakdown and impairs repair, thereby worsening mobility and daily function [23]. Second, mitochondrial dysfunction and oxidative stress in aging skeletal muscle reduce aerobic capacity and fatigue resistance, contributing to poorer performance on TUG/SPPB-related tasks [23,24]. Third, insulin resistance and anabolic resistance blunt muscle protein synthesis are frequently intertwined with metabolic comorbidities (e.g., diabetes), further degrading strength and function [25,26]. Finally, neuromuscular and proprioceptive declines adversely affect balance and gait stability, which are closely tied to perceived limitations and lower SarQoL [24,27]. Therefore, clinically combining SarQoL with primary screening tests such as SPPB ≤ 9 or low grip strength can efficiently identify older adults at high risk for poor health-related quality of life. In addition, when diabetes or sleep disorders are present, exercise and lifestyle modifications combining aerobic and resistance training targeting anti-inflammatory and metabolic pathways may provide an indirect pathway for improving SarQoL.

Model 2 highlighted that chronic conditions such as diabetes, sleep disorders, and sarcopenia significantly impacted SarQoL scores. Sarcopenia, in particular, is known to adversely affect HRQoL [4] and is a critical factor influencing physical activity levels and independence in older adults. Supporting this, Go et al. found that individuals with sarcopenia experienced approximately half the odds ratio of HRQoL issues compared to those without [28]. This underscores the importance of maintaining or improving the quality of life in older adults through effective health management. Therefore, this study verified the relationship between sarcopenia-related risk factors and quality of life using the SarQoL HRQoL questionnaire. Additionally, multiple logistic regression analyses were conducted to examine three physical factors—hand grip strength, the sit-to-stand test, and the SPPB—in relation to SarQoL scores. The analysis indicated that the odds ratio for improving quality of life increased with higher SarQoL scores across all variables, suggesting that better physical function is associated with enhanced quality of life. Notably, the SPPB demonstrated a statistically significant correlation with all stages of SarQoL, indicating its substantial impact on both muscle loss and quality of life in older adults. Grip strength, a key indicator of overall muscle strength [29], is associated with long-term resistance exercise [27].

Furthermore, inflammation activates macrophages that produce reactive oxygen species (ROS), leading to mitochondrial dysfunction and impaired ATP production and insulin secretion from pancreatic beta cells [30]. This chain of events contributes to sarcopenia and reduced muscle strength, including grip strength. Consequently, regular physical activity, encompassing both aerobic and resistance exercises, is essential in older adults to maintain or improve antioxidant capacity, mitochondrial function, and insulin sensitivity.

In summary, this study’s strength lies in its examination of the relationship between SarQoL scores, exercise function, and physical fitness factors among older adults in Korea. Unlike many previous studies that rely on national statistical data, this research involved a detailed, direct investigation of participants over several months. However, the study has notable limitations. This study employs a cross-sectional design, precluding causal inference. The sample is a convenience sample based on a single region, with a high proportion of women, limiting generalizability. Chronic diseases and physical activity were measured via self-report, introducing potential reporting bias. Furthermore, potential confounders such as nutritional intake, depression, and medication use were not sufficiently controlled, and the FET2-based foot flexion/dorsiflexion index may have limited external validity. Future cross-sectional and intervention studies, parallel use of standardized measures (6 m walk test, 5-reps chair stand test, etc.), and inclusion of nutritional and mental health variables are necessary.

5. Conclusions

The results of this study indicate that higher SarQoL scores among older adults in Korea are positively associated with higher levels of education, favorable living environment factors, and better performance on performance-based tests of physical fitness. These findings highlight the complex and significant role that physical and mental health play in the aging process. They also suggest that effective prevention and management of sarcopenia can directly contribute to improved quality of life in older adults.