Submitted:
21 October 2025
Posted:
22 October 2025
You are already at the latest version
Abstract
Background/Objectives: Sarcopenia, age-related muscle loss, has been found to be influenced by nutrition and lifestyle in studies in the western countries. Little is known, however, about their effect on sarcopenia in Asia. This study examined the association between diet, clinical status, and clinical setting with sarcopenia and physical performance in older adults in Taiwan. Methods: We conducted a cross-sectional study of 588 individuals aged ≥65 years recruited from three hospitals in southern Taiwan (2018–2020). Questionnaire, medical chart, and laboratory data were used to study the association between demographic, dietary, nutritional status, and biochemical data with sarcopenia, defined as low muscle mass plus reduced strength or poor physical performance. Logistic regression was used to identify associated factors and linear regression was used to assess the contributions of these factors to grip strength, gait speed, and chair stand time. Results: Sarcopenia was identified in 159 (27.0%) of the 588 participants. Those with sarcopenia had lower education levels, poorer nutritional status, weaker grip strength, and slower mobility. Daily intakes of sea vegetables (adjusted OR = 0.45, 95% CI: 0.22–0.90) and fresh fruits (adjusted OR = 0.41, 95% CI: 0.23–0.76) were independently associated with reduced risk of sarcopenia. Those with increased risk were older (adjusted OR = 1.03, 95% CI: 1.01–1.05) and recruited from Pingtung Veterans General Hospital Longquan Branch (adjusted OR = 6.48, 95% CI: 3.16–13.3), compared with those recruited from Pingtung Hospital. Sea vegetable intake was positively associated with grip strength, while fruit intake was inversely associated with chair stand time. Conclusions: Dietary factors, nutritional status, and recruitment setting were significantly associated with sarcopenia risk and physical performance. Prevention efforts might want to focus on increasing consumption sea vegetables and fruits and addressing institutional disparities.
Keywords:
1. Introduction
2. Materials and Methods
Data Source, Participants, and Study Design
Measurement
Outcome
Statistics
3. Results
4. Discussion
Study Limitations
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Abbreviations
| AWGS | Asian Working Group for Sarcopenia |
| BIA | bioelectrical impedance analysis |
| BMI | body mass index |
| CI | confidence interval |
| eGFR | estimated glomerular filtration rate |
| KVGH | Kaohsiung Veterans General Hospital |
| MNA | Mini Nutritional Assessment |
| OR | odds ratio |
| sd | standard deviation |
| SMI | skeletal muscle mass index |
| TSMH | Antai Tian-Sheng Memorial Hospital |
| TUG | timed up-and-go test |
References
- Yuan, S.; Larsson, S.C. Epidemiology of sarcopenia: Prevalence, risk factors, and consequences. Metabolism 2023, 144, 155533. [Google Scholar] [CrossRef] [PubMed]
- Gao, Q.; Hu, K.; Yan, C.; Zhao, B.; Mei, F.; Chen, F.; Zhao, L.; Shang, Y.; Ma, Y.; Ma, B. Associated Factors of Sarcopenia in Community-Dwelling Older Adults: A Systematic Review and Meta-Analysis. Nutrients 2021, 13. [Google Scholar] [CrossRef]
- Liu, J.; Zhu, Y.; Tan, J.K.; Ismail, A.H.; Ibrahim, R.; Hassan, N.H. Factors Associated with Sarcopenia among Elderly Individuals Residing in Community and Nursing Home Settings: A Systematic Review with a Meta-Analysis. Nutrients 2023, 15. [Google Scholar] [CrossRef]
- Chang, C.F.; Yeh, Y.L.; Chang, H.Y.; Tsai, S.H.; Wang, J.Y. Prevalence and Risk Factors of Sarcopenia among Older Adults Aged >/=65 Years Admitted to Daycare Centers of Taiwan: Using AWGS 2019 Guidelines. Int J Environ Res Public Health 2021, 18. [Google Scholar] [CrossRef]
- Chen, L.K.; Woo, J.; Assantachai, P.; Auyeung, T.W.; Chou, M.Y.; Iijima, K.; Jang, H.C.; Kang, L.; Kim, M.; Kim, S. , et al. Asian Working Group for Sarcopenia: 2019 Consensus Update on Sarcopenia Diagnosis and Treatment. J Am Med Dir Assoc 2020, 21, 300–307 e302. [Google Scholar] [CrossRef]
- Wu, J.Y.; Tso, R.; Teo, H.S.; Haldar, S. The utility of algae as sources of high value nutritional ingredients, particularly for alternative/complementary proteins to improve human health. Front Nutr 2023, 10, 1277343. [Google Scholar] [CrossRef]
- Hyun, J.; Lee, S.Y.; Ryu, B.; Jeon, Y.J. A Combination Study of Pre- and Clinical Trial: Seaweed Consumption Reduces Aging-Associated Muscle Loss! Aging Dis 2023, 15, 2813–2827. [Google Scholar] [CrossRef]
- Trigo, J.P.; Palmnas-Bedard, M.; Juanola, M.V.; Undeland, I. Effects of whole seaweed consumption on humans: current evidence from randomized-controlled intervention trials, knowledge gaps, and limitations. Front Nutr 2023, 10, 1226168. [Google Scholar] [CrossRef]
- Lee, M.K.; Choi, Y.H.; Nam, T.J. Pyropia yezoensis protein protects against TNF-alpha-induced myotube atrophy in C2C12 myotubes via the NF-kappaB signaling pathway. Mol Med Rep 2021, 24. [Google Scholar] [CrossRef] [PubMed]
- Gonzalez-Hedstrom, D.; Priego, T.; Lopez-Calderon, A.; Amor, S.; de la Fuente-Fernandez, M.; Inarejos-Garcia, A.M.; Garcia-Villalon, A.L.; Martin, A.I.; Granado, M. Beneficial Effects of a Mixture of Algae and Extra Virgin Olive Oils on the Age-Induced Alterations of Rodent Skeletal Muscle: Role of HDAC-4. Nutrients 2020, 13. [Google Scholar] [CrossRef] [PubMed]
- Hwang, J.; Kim, M.B.; Lee, S.; Hwang, J.K. Fucosterol, a Phytosterol of Marine Algae, Attenuates Immobilization-Induced Skeletal Muscle Atrophy in C57BL/6J Mice. Mar Drugs 2024, 22. [Google Scholar] [CrossRef]
- Healy, L.E.; Zhu, X.; Pojic, M.; Sullivan, C.; Tiwari, U.; Curtin, J.; Tiwari, B.K. Biomolecules from Macroalgae-Nutritional Profile and Bioactives for Novel Food Product Development. Biomolecules 2023, 13. [Google Scholar] [CrossRef]
- Hong, S.H.; Bae, Y.J. Association of Dietary Vegetable and Fruit Consumption with Sarcopenia: A Systematic Review and Meta-Analysis. Nutrients 2024, 16. [Google Scholar] [CrossRef]
- Koyanagi, A.; Veronese, N.; Solmi, M.; Oh, H.; Shin, J.I.; Jacob, L.; Yang, L.; Haro, J.M.; Smith, L. Fruit and Vegetable Consumption and Sarcopenia among Older Adults in Low- and Middle-Income Countries. Nutrients 2020, 12. [Google Scholar] [CrossRef]
- Zhao, N.; Lu, Y.; Liu, J. Associations between dietary intake and sarcopenia: a Mendelian randomization study. Nutr Hosp 2025, 42, 48–56. [Google Scholar] [CrossRef] [PubMed]
- Savini, I.; Catani, M.V.; Duranti, G.; Ceci, R.; Sabatini, S.; Avigliano, L. Vitamin C homeostasis in skeletal muscle cells. Free Radic Biol Med 2005, 38, 898–907. [Google Scholar] [CrossRef] [PubMed]
- Li, J.; Yang, Q.; Han, L.; Pan, C.; Lei, C.; Chen, H.; Lan, X. C2C12 Mouse Myoblasts Damage Induced by Oxidative Stress Is Alleviated by the Antioxidant Capacity of the Active Substance Phloretin. Front Cell Dev Biol 2020, 8, 541260. [Google Scholar] [CrossRef]
- Mohri, S.; Takahashi, H.; Sakai, M.; Waki, N.; Takahashi, S.; Aizawa, K.; Suganuma, H.; Ara, T.; Sugawara, T.; Shibata, D. , et al. Integration of bioassay and non-target metabolite analysis of tomato reveals that beta-carotene and lycopene activate the adiponectin signaling pathway, including AMPK phosphorylation. PLoS One 2022, 17, e0267248. [Google Scholar] [CrossRef] [PubMed]
- Hour, T.C.; Vo, T.C.T.; Chuu, C.P.; Chang, H.W.; Su, Y.F.; Chen, C.H.; Chen, Y.K. The Promotion of Migration and Myogenic Differentiation in Skeletal Muscle Cells by Quercetin and Underlying Mechanisms. Nutrients 2022, 14. [Google Scholar] [CrossRef]
- Hour, T.C.; Lan Nhi, N.T.; Lai, I.J.; Chuu, C.P.; Lin, P.C.; Chang, H.W.; Su, Y.F.; Chen, C.H.; Chen, Y.K. Kaempferol-Enhanced Migration and Differentiation of C2C12 Myoblasts via ITG1B/FAK/Paxillin and IGF1R/AKT/mTOR Signaling Pathways. Mol Nutr Food Res 2024, 68, e2300685. [Google Scholar] [CrossRef]
- Calcaterra, L.; Abellan van Kan, G.; Steinmeyer, Z.; Angioni, D.; Proietti, M.; Sourdet, S. Sarcopenia and poor nutritional status in older adults. Clin Nutr 2024, 43, 701–707. [Google Scholar] [CrossRef] [PubMed]
- Vidana-Espinoza, H.J.; Lopez-Teros, M.T.; Esparza-Romero, J.; Rosas-Carrasco, O.; Luna-Lopez, A.; Aleman Mateo, H. Association between the risk of malnutrition and sarcopenia at 4.2 years of follow-up in community-dwelling older adults. Front Med (Lausanne) 2024, 11, 1363977. [Google Scholar] [CrossRef] [PubMed]
- Liguori, I.; Curcio, F.; Russo, G.; Cellurale, M.; Aran, L.; Bulli, G.; Della-Morte, D.; Gargiulo, G.; Testa, G.; Cacciatore, F. , et al. Risk of Malnutrition Evaluated by Mini Nutritional Assessment and Sarcopenia in Noninstitutionalized Elderly People. Nutr Clin Pract 2018, 33, 879–886. [Google Scholar] [CrossRef]
- Papadopoulou, S.K.; Tsintavis, P.; Potsaki, P.; Papandreou, D. Differences in the Prevalence of Sarcopenia in Community-Dwelling, Nursing Home and Hospitalized Individuals. A Systematic Review and Meta-Analysis. J Nutr Health Aging 2020, 24, 83–90. [Google Scholar] [CrossRef]
- Smoliner, C.; Sieber, C.C.; Wirth, R. Prevalence of sarcopenia in geriatric hospitalized patients. J Am Med Dir Assoc 2014, 15, 267–272. [Google Scholar] [CrossRef]
- Rodriguez-Rejon, A.I.; Ruiz-Lopez, M.D.; Wanden-Berghe, C.; Artacho, R. Prevalence and Diagnosis of Sarcopenia in Residential Facilities: A Systematic Review. Adv Nutr 2019, 10, 51–58. [Google Scholar] [CrossRef] [PubMed]
| With sarcopenia | Without sarcopenia | ||
| N, | 159 | 429 | p-value |
| Age, Mean (sd), years old | 81.1 (14.6) | 81.8 (17.8) | 0.20 |
| Gender | 0.12 | ||
| male | 78 (49.1) | 206 (48.0) | |
| female | 81 (50.9) | 223 (52.0) | |
| Smoking | |||
| Never | 144 (90.6) | 334 (77.9) | 0.93 |
| Former | 7 (4.4) | 72 (16.8) | 0.39 |
| Current | 8 (5.0) | 23 (5.4) | 0.14 |
| Alcohol | |||
| Never | 156 (98.1) | 385 (89.7) | 0.54 |
| > 1 per week | 3 (1.9) | 36 (8.4) | 0.80 |
| > 2 per week | 0 (0.0) | 8 (1.9) | 0.37 |
| Betel chewing | |||
| Never | 157 (98.7) | 403 (93.9) | 0.75 |
| Former | 1 (0.6) | 22 (5.1) | 0.80 |
| Current | 1 (0.6) | 4 (0.9) | 0.83 |
| Education level | |||
| Higher school and more | 42 (26.4) | 178 (41.5) | < 0.001 |
| The skeletal muscle mass relative to total body weight, mean (sd) | 8.6 (10.1) | 9.3 (1.3) | 0.2 |
| Grip, mean (sd), kg | 17.9 (7.0) | 20.4 (7.6) | < 0.001 |
| 6-meter gait speed, mean (sd), meter/second | 0.6 (0.3) | 1.1 (4.8) | 0.28 |
| Chair stand test time, mean (sd), second | 15.8 (11.1) | 12.6 (11.7) | 0.0035 |
| Fish paste products (fish balls, fish soup) | |||
| 3 per month | 37 (23.3) | 73 (17.0) | 0.08 |
| Dried small fish with bones (Kissed larvae, dried small fish) | |||
| 3 per month | 65 (40.9) | 103 (24.0) | < 0.001 |
| Other non-fish seafood (shrimp, flower sticks, hairy crab) | |||
| 3 per month | 17 (10.7) | 82 (19.1) | 0.015 |
| Livestock and poultry offal (chicken liver, kidney) | |||
| used | 32 (20.1) | 128 (29.8) | 0.019 |
| Processed meat products (gong balls, hot dogs) | |||
| used | 74 (46.5) | 186 (43.4) | 0.49 |
| Light-colored vegetables (radish, Chinese cabbage) | |||
| 4-6 per Week | 18 (11.3) | 69 (16.1) | 0.15 |
| per day | 44 (27.7) | 174 (40.6) | 0.004 |
| Sea vegetables (algae) (sea vegetables, seaweed, hair vegetables) | |||
| used | 27 (17.0) | 185 (43.1) | < 0.001 |
| Canned and salted frozen vegetables | |||
| used | 13 (8.2) | 88 (20.5) | < 0.001 |
| Fresh fruits (grapes, bananas, lychees, longan) | |||
| used | 57 (35.8) | 293 (68.3) | < 0.001 |
| Mini Nutritional Assessment (MNA) | |||
| ≥ 24 | 111 (69.8) | 317 (73.9) | 0.32 |
| Biochemical | |||
| Albumin, mean(sd), mg/dL | 4.7 (3.7) | 5.1 (4.1) | 0.35 |
| Blood Urea Nitrogen, mean(sd), mg/dL | 20.1 (10.6) | 22.3 (13.0) | 0.06 |
| Serum creatinine, mean(sd), mg/dL | 2 (2.5) | 1.9 (3.0) | 0.88 |
| Glomerular filtration rate, mean(sd), min/ml/1.73 m2 | 65.5 (35.0) | 59.9 (34.0) | 0.08 |
| Uric acid, mean(sd), mg/dL | 5.7 (1.9) | 6 (1.9) | 0.039 |
| Ante Cibum sugar, mean(sd), mg/dL | 169.8 (613.9) | 121.7 (141.0) | 0.13 |
| hemoglobin A1c, mean(sd), % | 7.1 (1.4) | 7.2 (1.4) | 0.47 |
| Total cholesterol, mean(sd), gm/dL | 174.9 (37.4) | 167.9 (36.4) | 0.044 |
| Triglyceride, mean(sd), mg/dL | 115.1 (70.3) | 119.4 (64.9) | 0.49 |
| Systolic blood pressure, mean(sd), mmHg | 139 (22) | 138 (22) | 0.75 |
| Diastolic blood pressure, mean(sd), mmHg | 73 (10) | 73 (15) | 0.99 |
| Kaohsiung Veterans General Hospital | 36 (22.6) | 221 (51.5) | < 0.001 |
| Pingtung Veterans general hospital Longquan Branch | 12 (7.5) | 89 (20.7) | 0.002 |
| Pingtung Hospital | 111 (69.8) | 119 (27.7) | 0.11 |
| Crude model | Adjusted model | |||
| Crude OR (95% confidence interval) | p-value | Adjusted OR (95% confidence interval) | p-value | |
| Age | 1.00 (0.99-1.01) | 0.68 | 1.03 (1.01-1.05) | 0.003 |
| Male | 1.04 (0.72-1.50) | 0.82 | 1.61 (0.95-2.74) | 0.08 |
| Sea vegetables (algae) (sea vegetables, seaweed, hair vegetables) | ||||
| Used vs non-used | 0.27 (0.17-0.43) | < 0.001 | 0.45 (0.22-0.90) | 0.023 |
| Light-colored vegetables (radish, Chinese cabbage) | ||||
| 4-6 per Week | 0.50 (0.28-0.89) | 0.018 | 1.04 (0.47-2.28) | 0.93 |
| per day | 0.48 (0.32-0.73) | 0.001 | 0.87 (0.45-1.70) | 0.69 |
| Fresh fruits (grapes, bananas, lychees, longan) | ||||
| per day | 0.26 (0.18-0.38) | < 0.001 | 0.41 (0.23-0.76) | 0.004 |
| Mini Nutritional Assessment (MNA) | ||||
| ≥ 24 | 0.82 (0.55-1.22) | 0.32 | 0.62 (0.35-1.11) | 0.11 |
| Glomerular filtration rate, per 10 min/ml/1.73 m2 | 1.08 (1.01-1.15) | 0.029 | 0.98 (0.90-1.08) | 0.70 |
| recruitment site (vs. Pingtung Hospital) | ||||
| Kaohsiung Veterans General Hospital | 0.83 (0.41-1.66) | 0.60 | - | - |
| Pingtung Veterans general hospital Longquan Branch | 5.73 (3.70-8.86) | < 0.001 | 6.48 (3.16-13.3) | < 0.001 |
| grip (per kg) | 6-meter gait speed, mean(sd), m/s | chair stand test time, mean(sd) , s | ||||
| grip | Regression coefficients (95% confidence intervals)a | P value | Regression coefficients (95% confidence intervals) a | P value | Regression coefficients (95% confidence intervals) a | P value |
| Age | < 0.1 (-0.1 to <0.1) | 0.008 | <0.1 (< 0.0 to 0.1) | 0.53 | < 0.1 (< 0.1 to 0.1) | 0.12 |
| Male | 8.2 (7.1 to 9.2) | < 0.001 | -0.3 (0-1.3 to 0.7) | 0.56 | -1.3 (-2.5 to -0.1) | 0.037 |
| Sea vegetables (algae) (sea vegetables, seaweed, hair vegetables) | ||||||
| Used vs non-used | 1.9 (0.6 to 3.1) | 0.003 | 0.1 (-1.0 to 1.2) | 0.85 | 0.2 (-1.2 to 1.5) | 0.81 |
| Light-colored vegetables (radish, Chinese cabbage) | ||||||
| 4-6 per Week | -1.3 (-2.9 to 0.4) | 0.13 | 0.1 (-1.4 to 1.5) | 0.94 | 1.3 (-0.5 to 3.1) | 0.15 |
| per day | -0.5 (-1.8 to 0.8) | 0.44 | -0.1 (-1.2 to 1.1) | 0.91 | 1.7 (0.3 to 3.1) | 0.018 |
| Fresh fruits (grapes, bananas, lychees, longan) | ||||||
| per day | 0.8 (-0.5 to 2.1) | 0.22 | -0.4 (-1.6 to 0.8) | 0.54 | -1.6 (-3.1 to -0.2) | 0.025 |
| Mini Nutritional Assessment (MNA) | ||||||
| ≥ 24 | 2.8 (1.5 to 4.0) | < 0.001 | 0.3 (-0.8 to 1.4) | 0.61 | -3.0 (-4.3 to -1.6) | < 0.001 |
| Glomerular filtration rate, per 10 min/ml/1.73 m2 | 0.2 (0.0 to 0.4) | 0.018 | 0.1 (-0.1 to 0.3) | 0.44 | -0.1 (-0.4 to 0.1) | 0.21 |
| Vs. Pingtung Hospital | ||||||
| Kaohsiung Veterans General Hospital | -7.6 (-18.5 to 3.4) | 0.17 | 0.3 (-9.5 to 10.1) | 0.99 | 23.3 (11.3 to 35.2) | < 0.001 |
| Pingtung Veterans general hospital Longquan Branch | 0.3 (-1.1 to 1.7) | 0.71 | -0.6 (-1.9 to 0.7) | 0.35 | -11.0 (-12.5 to -9.4) | < 0.001 |
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
