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ORIGINAL RESEARCH article

Front. Nutr.
Sec. Clinical Nutrition
Volume 11 - 2024 | doi: 10.3389/fnut.2024.1505655
This article is part of the Research Topic Nutritional Indicators and Implications for Human Health View all 10 articles

Development and validation of a predicative Model for Identifying Sarcopenia in Chinese Adults Using Nutrition Indicators (AHLC)

Provisionally accepted
Xin Zhao Xin Zhao 1Pengdong Yan Pengdong Yan 2Ningxin Chen Ningxin Chen 1Tingting Han Tingting Han 1Bin Wang Bin Wang 2Yaomin Hu Yaomin Hu 1,3*
  • 1 Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
  • 2 Guangdong Institute of Intelligence Science and Technology, Zhuhai, China
  • 3 Department of Geriatrics, Renji Hospital, School of Medine, Shanghai Jiaotong University, Shanghai, China

The final, formatted version of the article will be published soon.

    Background Sarcopenia, a condition characterized by low muscle mass, plays a critical role in the health of older adults. Early identification of individuals at risk is essential to prevent sarcopenia-related complications. This study aimed to develop a predictive model using readily available clinical nutrition indicators to facilitate early detection Methods A total of 1002 participants were categorized into two groups: 819 with normal skeletal muscle mass (SMM) and 183 with low muscle mass (sarcopenia). A predictive model was developed for sarcopenia risk via multivariate logistic regression, and its performance was assessed using four analyses: receiver operating characteristic (ROC) curve analysis, decision curve analysis (DCA), a nomogram chart, and external validation. These methods were used to evaluate the model's discriminative ability and clinical applicability.In the low-SMM group, more females (55.73% vs. 40.42%) and older individuals (median 61 vs. 55 years) were observed. These patients had lower albumin (41.00 vs. 42.50 g/L) and lymphocyte levels (1.60 vs. 2.02 × 10 9 /L) but higher HDL (1.45 vs. 1.16 mmol/L) and calcium levels (2.24 vs. 2.20 mmol/L) (all P < 0.001). Using LASSO regression, we developed a nutritional AHLC (albumin + HDL cholesterol + lymphocytes + calcium) model for sarcopenia risk prediction. AUROC and DCA analyses, as well as nomogram charts and external validation, confirmed the robustness and clinical relevance of the AHLC model for predicting sarcopenia.3 Conclusions Our study employs serum nutrition indicators to aid clinicians in promoting healthier aging. The AHLC model stands out for weight-independent evaluations. This novel approach could assess sarcopenia risk in the Chinese population, thereby enhancing aging and quality of life.

    Keywords: Sarcopenia, nutrition indicators, AHLC, Predicative Model, sarcopenia risk 4

    Received: 03 Oct 2024; Accepted: 21 Nov 2024.

    Copyright: © 2024 Zhao, Yan, Chen, Han, Wang and Hu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Yaomin Hu, Department of Geriatrics, Renji Hospital, School of Medine, Shanghai Jiaotong University, Shanghai, China

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.