Correlation between skeletal muscle mass and Chinese healthy eating index in older adults

doi:10.12307/2026.851

Abstract

Abstract: BACKGROUND: With the deepening of China’s aging population, low skeletal muscle mass has become a serious public health problem. Diet is closely linked to muscle mass; however, existing research has mostly focused on the effects of a single nutrient, and there is still a lack of systematic exploration of the relationship between China’s overall dietary pattern and skeletal muscle quality.
OBJECTIVE: To analyze the correlation between the Chinese healthy eating index and skeletal muscle mass in older adults, thereby providing scientific evidence for optimizing diets for the elderly and preventing low skeletal muscle mass.
METHODS: Based on the data from the 2018 China Longitudinal Healthy Longevity Survey (CLHLS), 8 114 study subjects were included. The Chinese healthy eating index was used to evaluate the dietary quality of older adults, and skeletal muscle mass index was used to calculate the skeletal muscle mass of older adults. Low skeletal muscle mass was diagnosed according to the 2019 Asian Musculosis Working Group criteria. Multiple Logistic regression analysis was used to explore the association between China’s Healthy Diet Index and low skeletal muscle mass.
RESULTS AND CONCLUSION: (1) Univariate analysis showed that the highest quartile (Q4) group of the overall Chinese healthy eating index [odds ratio (OR)=0.52, 95% confidence interval (CI): 0.46-0.59], animal-based Chinese healthy eating index (OR=0.85, 95% CI: 0.75-0.97), and plant-based Chinese healthy eating index (OR=0.43, 95% CI: 0.38-0.49) was significantly associated with low skeletal muscle mass (P < 0.001). (2) Multivariate logistic regression showed that compared with the lowest quartile (Q1) group, the highest quartile (Q4) group of overall Chinese healthy eating index, animal-based Chinese healthy eating index, and plant-based Chinese healthy eating index had a 30% (OR=0.70, 95% CI: 0.60-0.83, P < 0.05), 20% (OR=0.80, 95% CI: 0.68-0.94, P < 0.05), and 20% (OR=0.80, 95% CI: 0.69-0.94, P < 0.05) reduction in low skeletal muscle mass risk, respectively. Trend testing further indicated that higher dietary quality was significantly associated with lower risk of low skeletal muscle mass (P_trend < 0.001). (3) Subgroup analysis showed that in female study subjects, compared with the lowest quartile (Q1), the highest quartile (Q4) group had a 43% (OR=0.57, 95% CI: 0.45-0.72, P < 0.05), 29% (OR=0.71, 95% CI: 0.56-0.88, P < 0.001), and 33% (OR=0.67, 95% CI: 0.54-0.83, P < 0.001) reduction in the risk of low skeletal muscle mass for the overall Chinese healthy eating index, animal-based Chinese healthy eating index, and plant-based Chinese healthy eating index, respectively. No correlation was found among males. These findings indicate that a higher Chinese healthy eating index is significantly associated with a reduced risk of low skeletal muscle mass in older adults. Adopting a healthy diet is an economically effective intervention to prevent a decrease in skeletal muscle mass.

Key words: China Longitudinal Healthy Longevity Survey (CLHLS), Chinese healthy eating index, skeletal muscle mass, older adults

CLC Number:

Chen Simin, Song Rui, Peng Xing, Wang Jie, Jing Zhaohang, Parhati Nasr, Abdunabi Wupu, He Qi, Yang Lei. Correlation between skeletal muscle mass and Chinese healthy eating index in older adults[J]. Chinese Journal of Tissue Engineering Research, 2026, 30(34): 9075-9080.

Figures/Tables 4

2.1 正常骨骼肌质量与低骨骼肌质量研究对象的基本情况对比分析共纳入目标人群8 114人：42.3%为男性(n=3 430)，57.7%为女性(n=4 684)；64.8%为低骨骼肌质量(n=5 254)，35.2%为正常骨骼肌质量(n=2 860)。与正常骨骼肌质量组相比，低骨骼肌质量组具有以下特征：女性比例更高(63.9% vs. 46.5%，P < 0.001)、年龄更大(80岁以上人群占比75.7% vs. 44.1%，P < 0.001)、未婚、离异或丧偶者占比更高(69.1% vs. 42.8%，P < 0.001)、教育水平在0年者占比更高(60.9% vs. 35.2%，P < 0.001)、退休前职业为农民者占比更高(70.6% vs. 57.2%，P < 0.001)。在生活方式方面，低骨骼肌质量组从不吸烟(70.7% vs. 65.8%，P < 0.001)和从不饮酒(76.7% vs. 71.0%，P < 0.001)的比例更高，而总体中国健康膳食指数评分处于最低四分位数(Q1)的比例更高(27.9% vs. 20.1%，P < 0.001)，见表2。 2.2 13种食物摄入与低骨骼肌质量风险的关联性分析单因素分析显示，所有13种被调查食物的摄入频率在低骨骼肌质量组与正常骨骼肌质量组之间的分布均存在显著差异(P均< 0.001)。多因素分析结果显示，有11种食物的较高摄入频率与低骨骼肌质量风险降低显著相关(P < 0.001)，保护效应(OR < 1)由强至弱依次为：新鲜水果(OR=0.74，95% CI：0.68-0.80)、蘑菇(OR=0.81，95% CI：0.79-0.83)、牛奶/奶制品(OR=0.91，95% CI：0.88-0.95)、坚果(OR=0.85，95% CI：0.81-0.88)、鱼类(OR=0.87，95% CI：0.84-0.91)、蛋类(OR=0.87，95% CI：0.83-0.92)、腌制蔬菜(OR=0.87，95% CI：0.84-0.91)、豆制品(OR=0.86，95% CI：0.83-0.90)、红肉(OR=0.91，95% CI：0.88-0.95)、食糖(OR=0.91，95% CI：0.89-0.95)和茶(OR=0.92，95% CI：0.87-0.94)。新鲜蔬菜的摄入虽在单因素分析中差异显著，但在Logistic回归模型中未显示出统计学意义(OR=0.95，P=0.171)。大蒜的摄入与低骨骼肌质量风险之间未发现任何显著关联(OR=0.99，P=0.707)，见表3。 2.3 中国健康膳食指数四分位数与低骨骼肌质量风险的多变量Logistic回归分析总体中国健康膳食指数的模型4中，与最低四分位数Q1相比，最高四分位数Q4低骨骼肌质量风险显著减少30%(OR=0.70，95%CI：0.60-0.83，P < 0.05)。在动物性中国健康膳食指数模型4中，与最低四分位数Q1相比，最高四分位数Q4低骨骼肌质量风险显著减少20%(OR=0.80，95%CI："

0.68-0.94，P < 0.05)。对于植物性中国健康膳食指数模型4中，与最低四分位数Q1相比，最高四分位数Q4低骨骼肌质量风险同样减少20%(OR=0.80，95%CI：0.69-0.94，P < 0.05)。趋势检验显示，较高的膳食质量与较低的低骨骼肌质量发生风险显著相关，且这种关联在统计上是显著的(P_trend < 0.001)，见表4。 2.4 不同性别研究对象中国健康膳食指数四分位数与低骨骼肌质量风险的关联分析男性总体中国健康膳食指数、动物性中国健康膳食指数与植物性中国健康膳食指数的P_trend值均无统计学差异，表明男性群体中膳食质量变化与低骨骼肌质量发生风险没有明显关联。相反女性群体中总体中国健康膳食指数、动物性和植物性中国健康膳食指数均显示较高的膳食质量与较低的低骨骼肌质量发生风险显著相关(P_trend < 0.001)。具体而言，与最低四分位数Q1相比，最高四分位数Q4总体中国健康膳食指数的低骨骼肌质量发生风险降低43% (OR=0.57，95%CI：0.45-0.72，P < 0.05)，见表5。 2.5 不同收入水平研究对象中国膳食质量指数四分位数与低骨骼肌质量发生风险的关联分析在年收入低于10万元和年收入≥10万元的两个群体中，总体中国膳食质量指数、动物性中国膳食质量指数和植物性中国膳食质量指数的P_trend均具有统计学意义(P < 0.05)，表明膳食质量越高，低骨骼肌质量发生风险越低。具体而言，在收入低于10万元的群体中，与最低四分位数Q1相比，总体中国膳食质量指数的最高四分位数Q4组低骨骼肌质量发生风险降低38%(OR=0.62，95%CI：0.50–0.77)；动物性中国膳食质量指数的最高四分位数Q4组低骨骼肌质量发生风险降低28%(OR=0.72，95%CI：0.58–0.89)；植物性中国膳食质量指数的最高四分位数Q4组低骨骼肌质量发生风险降低32%(OR=0.68，95%CI：0.55–0.85)。在收入≥10万元的群体中，同样观察到显著的保护效应，见表6。结果表明，在不同收入水平群体中，更高的膳食质量均与更低的低骨骼肌质量发生风险显著相关。"

References

[1] 古恒宇,肖江曼,林育豪,等.2000-2020年中国人口老龄化的空间格局及影响因素研究[J].华南地理学报,2025,3(1):54-66.
[2] NONAKA K, MURATA S, SHIRAIWA K, et al. Effect of Skeletal Muscle and Fat Mass on Muscle Strength in the Elderly. Healthcare (Basel). 2018;6(3):72.
[3] 宋雪红.老年病的预防与管理：健康老龄化的智慧[J].家庭生活指南,2024,40(12):64-65.
[4] 肖亮满,朱娴琼,何念财,等.1990-2023年全球老年人心血管疾病领域专利的发展态势及研究热点[J].实用心脑肺血管病杂志,2024,32(8):1-7.
[5] 许丽娴,崔丽萍,陈诗琪,等.老年糖尿病患者老化期望现状及影响因素研究[J].护理管理杂志,2025,25(1):39-43.
[6] 季小琳,徐海燕,苏建华.肌少症信号通路在老化中的角色[J].中国疗养医学,2025,34(4):67-72.
[7] LOW S, GOH KS, NG TP, et al. Decline in skeletal muscle mass is associated with cognitive decline in type 2 diabetes mellitus. J Diabetes Complications. 2022;36(9):108258.
[8] ARAI H, NOZOE M, KAMIYA K, et al. Association Between Skeletal Muscle Mass Index and Falls in Patients With Functional Impairment. Am J Phys Med Rehabil. 2023;102(10):913-918.
[9] OGAWA T, ONAGA A, OSHIRO N, et al. Older patients with less skeletal muscle mass gain more skeletal muscle in rehabilitation wards after fractures. Eur Geriatr Med. 2022;13(3):615-622.
[10] 刘力源.我国老龄人口死因死亡率的动态演变研究[D].天津:天津财经大学,2024.
[11] VAN VUGT JLA, GASPERSZ MP, VUGTS J, et al. Low Skeletal Muscle Density Is Associated with Early Death in Patients with Perihilar Cholangiocarcinoma Regardless of Subsequent Treatment. Dig Surg. 2019;36(2):144-152.
[12] HAMAGUCHI Y, KAIDO T, OKUMURA S, et al. Proposal for new diagnostic criteria for low skeletal muscle mass based on computed tomography imaging in Asian adults. Nutrition. 2016;32(11-12): 1200-1205.
[13] KIM KM, JANG HC, LIM S. Differences among skeletal muscle mass indices derived from height-, weight-, and body mass index-adjusted models in assessing sarcopenia. Korean J Intern Med. 2016;31(4):643-650.
[14] PAPADOPOULOU SK. Sarcopenia: A Contemporary Health Problem among Older Adult Populations. Nutrients. 2020;12(5):1293.
[15] BOOTH FW, ROBERTS CK, THYFAULT JP, et al. Role of Inactivity in Chronic Diseases: Evolutionary Insight and Pathophysiological Mechanisms. Physiol Rev. 2017;97(4):1351-1402.
[16] YOON MS. mTOR as a Key Regulator in Maintaining Skeletal Muscle Mass. Front Physiol. 2017;8:788.
[17] REMELLI F, VITALI A, ZURLO A, et al. Vitamin D Deficiency and Sarcopenia in Older Persons. Nutrients. 2019;11(12):2861.
[18] LOPEZ-PEDROSA JM, CAMPRUBI-ROBLES M, GUZMAN-ROLO G, et al. The Vicious Cycle of Type 2 Diabetes Mellitus and Skeletal Muscle Atrophy: Clinical, Biochemical, and Nutritional Bases. Nutrients. 2024;16(1):172.
[19] DONINI LM, BUSETTO L, BISCHOFF SC, et al. Definition and Diagnostic Criteria for Sarcopenic Obesity: ESPEN and EASO Consensus Statement. Obes Facts. 2022;15(3):321-335.
[20] DAMLUJI AA, ALFARAIDHY M, ALHAJRI N, et al. Sarcopenia and Cardiovascular Diseases. Circulation. 2023;147(20):1534-1553.
[21] TUTTLE CSL, THANG LAN, MAIER AB. Markers of inflammation and their association with muscle strength and mass: A systematic review and meta-analysis. Ageing Res Rev. 2020;64:101185.
[22] YIN L, LI N, JIA W, et al. Skeletal muscle atrophy: From mechanisms to treatments. Pharmacol Res. 2021;172:105807.
[23] IZQUIERDO M, DE SOUTO BARRETO P, ARAI H, et al. Global consensus on optimal exercise recommendations for enhancing healthy longevity in older adults (ICFSR). J Nutr Health Aging. 2025; 29(1):100401.
[24] HEYMSFIELD SB, GONZALEZ MC, LU J, et al. Skeletal muscle mass and quality: evolution of modern measurement concepts in the context of sarcopenia. Proc Nutr Soc. 2015;74(4):355-366.
[25] MASSON SWC, DISSANAYAKE WC, BROOME SC, et al. A role for β-catenin in diet-induced skeletal muscle insulin resistance. Physiol Rep. 2023; 11(4):e15536.
[26] ZHANG Y, GUO H, LIANG J, et al. Relationship Between Dietary Omega-3 and Omega-6 Polyunsaturated Fatty Acids Level and Sarcopenia. A Meta-Analysis of Observational Studies. Front Nutr. 2022;8:738083.
[27] WESSELINK E, BOSHUIZEN HC, VAN LANEN AS, et al. Dietary and lifestyle inflammation scores in relation to colorectal cancer recurrence and all-cause mortality: A longitudinal analysis. Clin Nutr. 2024;43(9):2092-2101.
[28] 吕璐.不同糖耐量人群中衰老与炎症、氧化应激及饮食模式关联的研究[D].北京:北京协和医学院,2022.
[29] 杨柳青,田红梅,石汉平.三种饮食模式与慢性疾病研究进展[J].首都医科大学学报,2022, 43(2):311-320.
[30] 易鑫枚,张飞,王佳贺.老年人炎症与肌少症相关性的研究进展[J].实用老年医学,2025, 39(7):654-658.
[31] 彭苏柳,刘玲中,孙镌,等.营养干预对老年肌少症患者的影响[J].广东医学,2025,46(8): 1276-1280.
[32] PÉREZ PALMER N, TREJO ORTEGA B, JOSHI P. Cognitive Impairment in Older Adults: Epidemiology, Diagnosis, and Treatment. Psychiatr Clin North Am. 2022;45(4):639-661.
[33] XING X, YANG X, CHEN J, et al. Multimorbidity, healthy lifestyle, and the risk of cognitive impairment in Chinese older adults: a longitudinal cohort study. BMC Public Health. 2024;24(1):46.
[34] ZHONG BL, CHEN SL, TU X, et al. Loneliness and Cognitive Function in Older Adults: Findings From the Chinese Longitudinal Healthy Longevity Survey. J Gerontol B Psychol Sci Soc Sci. 2017;72(1):120-128.
[35] MA YH, CHEN HS, LIU C, et al. Association of Long-term Exposure to Ambient Air Pollution With Cognitive Decline and Alzheimer’s Disease-Related Amyloidosis. Biol Psychiatry. 2023;93(9):780-789.
[36] GANAPATHY A, NIEVES JW. Nutrition and Sarcopenia-What Do We Know? Nutrients. 2020; 12(6):1755.
[37] LU W, WU D, WANG L, et al. Insoluble dietary fibers from Lentinus edodes stipes improve the gel properties of pork myofibrillar protein: A water distribution, microstructure and intermolecular interactions study. Food Chem. 2023;411:135386.
[38] BOYD CE, MCNEVIN AA, DAVIS RP. The contribution of fisheries and aquaculture to the global protein supply. Food Secur. 2022;14(3):805-827.
[39] MATSUMOTO A, PASUT A, MATSUMOTO M, et al. mTORC1 and muscle regeneration are regulated by the LINC00961-encoded SPAR polypeptide. Nature. 2017;541(7636):228-232.
[40] ROBERTS MD, MCCARTHY JJ, HORNBERGER TA, et al. Mechanisms of mechanical overload-induced skeletal muscle hypertrophy: current understanding and future directions. Physiol Rev. 2023;103(4):2679-2757.
[41] WIDJAJA AA, LIM WW, VISWANATHAN S, et al. Inhibition of IL-11 signalling extends mammalian healthspan and lifespan. Nature. 2024;632(8023):157-165.
[42] JUUL F, VAIDEAN G, PAREKH N. Ultra-processed Foods and Cardiovascular Diseases: Potential Mechanisms of Action. Adv Nutr. 2021;12(5): 1673-1680.
[43] YADAV D, NEGI PS. Bioactive components of mushrooms: Processing effects and health benefits. Food Res Int. 2021;148:110599.
[44] SANS MD, CROZIER SJ, VOGEL NL, et al. Dietary Protein and Amino Acid Deficiency Inhibit Pancreatic Digestive Enzyme mRNA Translation by Multiple Mechanisms. Cell Mol Gastroenterol Hepatol. 2021;11(1):99-115.
[45] MOHAJERI M, CICERO AFG. Dietary inflammation index association with serum levels of nitric oxide, prostacyclin, and thromboxane B2 among prinzmetal angina patients and healthy persons. Nutr Metab Cardiovasc Dis. 2024;34(4):1054-1060.
[46] OH S, LEE SY, KIM DY, et al. Association of Dietary Patterns with Weight Status and Metabolic Risk Factors among Children and Adolescents. Nutrients. 2021;13(4):1153.
[47] PAPADOPOULOU SK, DETOPOULOU P, VOULGARIDOU G, et al. Mediterranean Diet and Sarcopenia Features in Apparently Healthy Adults over 65 Years: A Systematic Review. Nutrients. 2023;15(5):1104.
[48] FOURNIER C, KARAGOUNIS LG, SACCO SM, et al. Impact of moderate dietary protein restriction on glucose homeostasis in a model of estrogen deficiency. J Nutr Biochem. 2022;102:108952.
[49] BIDDLE M, KNOX D. The role of estrogen receptor manipulation during traumatic stress on changes in emotional memory induced by traumatic stress. Psychopharmacology (Berl). 2023;240(5):1049-1061.
[50] CHEN QH, MUNOZ E, ASHONG D. Insight into Recent Advances in Degrading Androgen Receptor for Castration-Resistant Prostate Cancer. Cancers (Basel). 2024;16(3):663.
[51] YAO M, ROSARIO ER, SOPER JC, et al. Androgens Regulate Tau Phosphorylation Through Phosphatidylinositol 3-Kinase-Protein Kinase B-Glycogen Synthase Kinase 3β Signaling. Neuroscience. 2025;568:503-518.