衍生中性粒–淋巴细胞比值与体重调整腰围 指数在肌肉减少性肥胖的相关性研究
Association of Derived Neutrophil-to-Lymphocyte Ratio and Weight-Adjusted Waist Index with Sarcopenic Obesity
摘要: 目的:本研究旨在衍生中性粒细胞与淋巴细胞比值(ln dNLR)与体重调整腰围指数(WWI)在肌肉减少性肥胖(SO)中的关联及潜在机制,为其风险评估与早期干预提供依据。方法:基于1999~2006年及2010~2018年美国国家健康与营养调查(NHANES)数据,共纳入24,264名成年人。采用多因素Logistic回归分析WWI及自然对数转换的dNLR (ln dNLR)与肌肉减少性肥胖的独立关联,限制性立方样条分析剂量–反应关系,交互作用及中介分析探讨二者协同效应及潜在路径。结果:共有肌肉减少性肥胖患者1020例,其WWI与ln dNLR水平均显著高于非患病者(均P < 0.001)。完全校正混杂因素后,WWI与ln dNLR均为SO的独立危险因素。限制性立方样条分析提示二者与SO均存在非线性阈值效应。相加交互分析显示,ln dNLR与WWI存在显著协同作用(RERI = 6.84, 95%CI: 2.31~11.37; AP = 0.26, 95%CI: 0.15~0.38; SI = 1.38, 95%CI: 1.17~1.63, 均P < 0.001),双高暴露组患病风险最高(OR = 25.85, 95%CI: 15.35~43.54, P < 0.001)。中介分析表明,WWI在ln dNLR与SO的关联中发挥部分中介作用。结论:ln dNLR与WWI升高均会增加肌肉减少性肥胖的发病风险,二者存在显著协同作用,且WWI可部分介导ln dNLR与肌肉减少性肥胖之间的关联。
Abstract: Background: To investigate the associations and potential mechanisms linking the natural log-transformed derived neutrophil-to-lymphocyte ratio (ln dNLR) and weight-adjusted waist index (WWI) with sarcopenic obesity (SO). Methods: Based on data from the National Health and Nutrition Examination Survey (NHANES) 1999~2006 and 2010~2018, a total of 24,264 adults were included. Multivariable logistic regression was performed to examine the independent associations of weight-adjusted waist index (WWI) and natural log-transformed derived neutrophil-to-lymphocyte ratio (ln dNLR) with sarcopenic obesity (SO). Restricted cubic spline analysis was used to evaluate dose-response relationships, while interaction and mediation analyses were conducted to explore synergistic effects and potential pathways. Results: A total of 1020 participants with SO were identified. Both WWI and ln dNLR levels were significantly higher in individuals with SO than in those without (both (P < 0.001)). After full adjustment for confounders, WWI and ln dNLR remained independent risk factors for SO. Restricted cubic spline analysis revealed nonlinear threshold effects of both indicators on SO risk. Additive interaction analysis demonstrated a significant synergistic effect between ln dNLR and WWI (RERI = 6.84, 95% CI: 2.31~11.37; AP = 0.26, 95% CI: 0.15~0.38; SI = 1.38, 95% CI: 1.17~1.63; all (P < 0.001)), with the highest risk observed in the group with both indicators at high levels (OR = 25.85, 95% CI: 15.35~43.54, (P < 0.001)). Mediation analysis showed that WWI partially mediated the association between ln dNLR and SO. Conclusion: Elevated ln dNLR and WWI are independently associated with increased risk of sarcopenic obesity, with a significant synergistic effect between them. Furthermore, WWI partially mediates the association between ln dNLR and SO.
文章引用:张成祥, 邓辉胜. 衍生中性粒–淋巴细胞比值与体重调整腰围 指数在肌肉减少性肥胖的相关性研究[J]. 临床医学进展, 2026, 16(3): 3405-3419. https://doi.org/10.12677/acm.2026.1631146

参考文献

[1] Chen, L., Woo, J., Assantachai, P., Auyeung, T., Chou, M., Iijima, K., et al. (2020) Asian Working Group for Sarcopenia: 2019 Consensus Update on Sarcopenia Diagnosis and Treatment. Journal of the American Medical Directors Association, 21, 300-307.e2. [Google Scholar] [CrossRef] [PubMed]
[2] Donini, L.M., Busetto, L., Bischoff, S.C., Cederholm, T., Ballesteros-Pomar, M.D., Batsis, J.A., et al. (2022) Definition and Diagnostic Criteria for Sarcopenic Obesity: ESPEN and EASO Consensus Statement. Clinical Nutrition, 41, 990-1000. [Google Scholar] [CrossRef] [PubMed]
[3] Xu, Y. and Yilmazer, T. (2021) Childhood Socioeconomic Status, Adulthood Obesity and Health: The Role of Parental Permanent and Transitory Income. Social Science & Medicine, 283, Article ID: 114178. [Google Scholar] [CrossRef] [PubMed]
[4] Batsis, J.A. and Villareal, D.T. (2018) Sarcopenic Obesity in Older Adults: Aetiology, Epidemiology and Treatment Strategies. Nature Reviews Endocrinology, 14, 513-537. [Google Scholar] [CrossRef] [PubMed]
[5] Franceschi, C., Garagnani, P., Parini, P., Giuliani, C. and Santoro, A. (2018) Inflammaging: A New Immune-Metabolic Viewpoint for Age-Related Diseases. Nature Reviews Endocrinology, 14, 576-590. [Google Scholar] [CrossRef] [PubMed]
[6] Ferrucci, L. and Fabbri, E. (2018) Inflammageing: Chronic Inflammation in Ageing, Cardiovascular Disease, and Frailty. Nature Reviews Cardiology, 15, 505-522. [Google Scholar] [CrossRef] [PubMed]
[7] Lee, G., Espirito Santo, A.I., Zwingenberger, S., Cai, L., Vogl, T., Feldmann, M., et al. (2018) Fully Reduced HMGB1 Accelerates the Regeneration of Multiple Tissues by Transitioning Stem Cells to GAlert. Proceedings of the National Academy of Sciences of the United States of America, 115, E4463-E4472. [Google Scholar] [CrossRef] [PubMed]
[8] Proctor, M.J., Morrison, D.S., Talwar, D., Balmer, S.M., Fletcher, C.D., O’Reilly, D.S.J., et al. (2011) A Comparison of Inflammation-Based Prognostic Scores in Patients with Cancer. A Glasgow Inflammation Outcome Study. European Journal of Cancer, 47, 2633-2641. [Google Scholar] [CrossRef] [PubMed]
[9] Templeton, A.J., McNamara, M.G., Šeruga, B., Vera-Badillo, F.E., Aneja, P., Ocaña, A., et al. (2014) Prognostic Role of Neutrophil-To-Lymphocyte Ratio in Solid Tumors: A Systematic Review and Meta-Analysis. JNCI: Journal of the National Cancer Institute, 106, dju124. [Google Scholar] [CrossRef] [PubMed]
[10] Park, Y., Kim, N.H., Kwon, T.Y. and Kim, S.G. (2018) A Novel Adiposity Index as an Integrated Predictor of Cardiometabolic Disease Morbidity and Mortality. Scientific Reports, 8, Article No. 16753. [Google Scholar] [CrossRef] [PubMed]
[11] Addison, O., Marcus, R.L., LaStayo, P.C. and Ryan, A.S. (2014) Intermuscular Fat: A Review of the Consequences and Causes. International Journal of Endocrinology, 2014, Article ID: 309570. [Google Scholar] [CrossRef] [PubMed]
[12] Batsis, J.A., Barre, L.K., Mackenzie, T.A., Pratt, S.I., Lopez‐Jimenez, F. and Bartels, S.J. (2013) Variation in the Prevalence of Sarcopenia and Sarcopenic Obesity in Older Adults Associated with Different Research Definitions: Dual‐energy X‐Ray Absorptiometry Data from the National Health and Nutrition Examination Survey 1999-2004. Journal of the American Geriatrics Society, 61, 974-980. [Google Scholar] [CrossRef] [PubMed]
[13] Schmidt, S.L., Bryman, D., Greenway, F.L. and Hendricks, E.J. (2014) How Physician Obesity Medicine Specialists Treated Obesity before 2012 New Drug Approvals. Obesity Surgery, 25, 186-190. [Google Scholar] [CrossRef] [PubMed]
[14] Zhang, X., Lu, X., Pan, X., Shen, S. and Tong, N. (2024) Role of Waist Circumference-To-Height Ratio in Assessing Adiposity, Predicting Type 2 Diabetes Mellitus and Other Cardiometabolic Diseases. Journal of Central South University. Medical Sciences Journal, 49, 1062-1072.
[15] Thomas, D.M., Bredlau, C., Bosy-Westphal, A., Mueller, M., Shen, W., Gallagher, D., et al. (2013) Relationships between Body Roundness with Body Fat and Visceral Adipose Tissue Emerging from a New Geometrical Model. Obesity, 21, 2264-2271. [Google Scholar] [CrossRef] [PubMed]
[16] Krakauer, N.Y. and Krakauer, J.C. (2012) A New Body Shape Index Predicts Mortality Hazard Independently of Body Mass Index. PLOS ONE, 7, e39504. [Google Scholar] [CrossRef] [PubMed]
[17] Ashwell, M. and Hsieh, S.D. (2005) Six Reasons Why the Waist-To-Height Ratio Is a Rapid and Effective Global Indicator for Health Risks of Obesity and How Its Use Could Simplify the International Public Health Message on Obesity. International Journal of Food Sciences and Nutrition, 56, 303-307. [Google Scholar] [CrossRef] [PubMed]
[18] Hu, B., Yang, X., Xu, Y., Sun, Y., Sun, C., Guo, W., et al. (2014) Systemic Immune-Inflammation Index Predicts Prognosis of Patients after Curative Resection for Hepatocellular Carcinoma. Clinical Cancer Research, 20, 6212-6222. [Google Scholar] [CrossRef] [PubMed]
[19] Liu, H., Tang, G., Yu, D., Gu, P., Zhu, X., Wang, A., et al. (2025) The Aggregate Index of Systemic Inflammation (AISI) Is a Novel Iga Nephropathy Prognosis Predictor. Journal of Inflammation Research, 18, 5031-5046. [Google Scholar] [CrossRef] [PubMed]
[20] Gkantzios, A., Tsiptsios, D., Karapepera, V., Karatzetzou, S., Kiamelidis, S., Vlotinou, P., et al. (2023) Monocyte to HDL and Neutrophil to HDL Ratios as Potential Ischemic Stroke Prognostic Biomarkers. Neurology International, 15, 301-317. [Google Scholar] [CrossRef] [PubMed]
[21] Arabi, A., Abdelhamid, A., Nasrallah, D., Al-Haneedi, Y., Assami, D., Alsheikh, R., et al. (2025) Monocyte-To-HDL Ratio (MHR) as a Novel Biomarker: Reference Ranges and Associations with Inflammatory Diseases and Disease-Specific Mortality. Lipids in Health and Disease, 24, Article No. 343. [Google Scholar] [CrossRef
[22] Li, X., Du, H., Zhang, G., Song, Z., Qi, M. and Wang, H. (2025) Threshold Effect of the Lymphocyte to HDL-C Ratio on the Risk of Stroke-Associated Pneumonia after Acute Ischemic Stroke: A Retrospective Cohort Study. Journal of Inflammation Research, 18, 15847-15858. [Google Scholar] [CrossRef
[23] Zahorec, R. (2021) Neutrophil-To-Lymphocyte Ratio, Past, Present and Future Perspectives. Bratislava Medical Journal, 122, 474-488. [Google Scholar] [CrossRef] [PubMed]
[24] Duan, J., Pan, L. and Yang, M. (2018) Preoperative Elevated Neutrophil-To-Lymphocyte Ratio (NLR) and Derived NLR Are Associated with Poor Prognosis in Patients with Breast Cancer. Medicine, 97, e13340. [Google Scholar] [CrossRef] [PubMed]
[25] Gambichler, T., Mansour, R., Scheel, C.H., Said, S., Abu Rached, N. and Susok, L. (2022) Prognostic Performance of the Derived Neutrophil-To-Lymphocyte Ratio in Stage IV Melanoma Patients Treated with Immune Checkpoint Inhibitors. Dermato, 2, 14-20. [Google Scholar] [CrossRef
[26] Naganuma, A., Kakizaki, S., Hiraoka, A., Tada, T., Hatanaka, T., Kariyama, K., et al. (2025) Evaluation of Treatment Outcomes Using dNLR and GNRI in Combination Therapy with Atezolizumab and Bevacizumab for Hepatocellular Carcinoma. Cancer Medicine, 14, e70618. [Google Scholar] [CrossRef] [PubMed]
[27] Proctor, M.J., McMillan, D.C., Morrison, D.S., Fletcher, C.D., Horgan, P.G. and Clarke, S.J. (2012) A Derived Neutrophil to Lymphocyte Ratio Predicts Survival in Patients with Cancer. British Journal of Cancer, 107, 695-699. [Google Scholar] [CrossRef] [PubMed]
[28] Obeagu, E.I. (2025) Monocyte-to-lymphocyte Ratio as a Subtype-Specific Biomarker in Breast Cancer Prognosis: A Narrative Review. Annals of Medicine & Surgery, 87, 8617-8623. [Google Scholar] [CrossRef
[29] Pang, Y., Shao, H., Yang, Z., Fan, L., Liu, W., Shi, J., et al. (2020) The (Neutrophils + Monocyte)/Lymphocyte Ratio Is an Independent Prognostic Factor for Progression-Free Survival in Newly Diagnosed Multiple Myeloma Patients Treated with BCD Regimen. Frontiers in Oncology, 10, Article 1617. [Google Scholar] [CrossRef] [PubMed]
[30] Barnhill, M.S. and Carey, E.J. (2023) Compartmentalizing Risk with Sarcopenic Obesity. Liver Transplantation, 29, 463-464. [Google Scholar] [CrossRef] [PubMed]
[31] Ma, Y., Li, X., Lin, X., Zhang, K. and Leng, J. (2025) Role of Immunity and Inflammation in Sarcopenic Obesity. The Journal of Nutritional Biochemistry, 146, Article ID: 110077. [Google Scholar] [CrossRef] [PubMed]
[32] Londhe, P. and Guttridge, D.C. (2015) Inflammation Induced Loss of Skeletal Muscle. Bone, 80, 131-142. [Google Scholar] [CrossRef] [PubMed]
[33] Kalinkovich, A. and Livshits, G. (2017) Sarcopenic Obesity or Obese Sarcopenia: A Cross Talk between Age-Associated Adipose Tissue and Skeletal Muscle Inflammation as a Main Mechanism of the Pathogenesis. Ageing Research Reviews, 35, 200-221. [Google Scholar] [CrossRef] [PubMed]
[34] Zembron-Lacny, A., Dziubek, W., Wolny-Rokicka, E., Dabrowska, G. and Wozniewski, M. (2019) The Relation of Inflammaging with Skeletal Muscle Properties in Elderly Men. American Journal of Mens Health, 13, 1-8. [Google Scholar] [CrossRef] [PubMed]
[35] Choi, K.M. (2013) Sarcopenia and Sarcopenic Obesity. Endocrinology and Metabolism, 28, 86-89. [Google Scholar] [CrossRef] [PubMed]
[36] Tao, Z., Zuo, P. and Ma, G. (2024) Association of Weight-Adjusted Waist Index with Cardiovascular Disease and Mortality among Metabolic Syndrome Population. Scientific Reports, 14, Article No. 18684. [Google Scholar] [CrossRef] [PubMed]
[37] Tidball, J.G. (2017) Regulation of Muscle Growth and Regeneration by the Immune System. Nature Reviews Immunology, 17, 165-178. [Google Scholar] [CrossRef] [PubMed]
[38] Cani, P.D., Bibiloni, R., Knauf, C., Waget, A., Neyrinck, A.M., Delzenne, N.M., et al. (2008) Changes in Gut Microbiota Control Metabolic Endotoxemia-Induced Inflammation in High-Fat Diet-Induced Obesity and Diabetes in Mice. Diabetes, 57, 1470-1481. [Google Scholar] [CrossRef] [PubMed]