查萨科佩尼亚的新型炎症相关指数:基于人口的研究的见解
Yuanhao Tong1, Huayu Li2, Yang Cheng3
1Department of Social Medicine of School of Public Health and Department of Pharmacy of the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China; Department of Orthopedics, Shanghai Sixth People's Hospital affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Nutrition (Burbank, Los Angeles County, Calif.)
|October 29, 2025
概括
像中性粒细胞百分比与白蛋白比率 (NPAR) 这样的炎症标志物与美国人更高的肉症风险有关. 在临床环境中,NPAR显示为预测萨科佩尼亚最有前途的方法.
科学领域:
- 老年学是一门学科.
- 炎症研究的研究.
- 营养科学 营养科学
背景情况:
- 肉症的进展与炎症有关,但关于特定炎症指数的数据有限.
- 中性粒细胞百分比与白蛋白比率 (NPAR) 尚未被系统地研究与肉类有关.
研究的目的:
- 调查炎症指数与肉症发病率之间的相关性.
- 为了评估萨科佩尼亚炎症指数的预测性能.
主要方法:
- 使用了国家健康和营养检查调查 (NHANES) 数据 (2011-2018).
- 采用多变量逻辑回归,受限立方线 (RCS) 和随机森林分析.
- 使用接收器操作特征 (ROC) 曲线和曲线下的面积 (AUC) 评估预测准确性.
主要成果:
- 增加的NPAR和全身免疫炎症指数 (SII) 与更高的肉症发病率相关,在调整了混因素后.
- 在NPAR (OR=1.70) 和SII (OR=1.62) 的最高四分位数中,肉症的风险显著增加.
- NPAR显示了对皮症的最高预测值 (AUC=0.784).
结论:
- 炎症指数,特别是NPAR,与美国人的肉症发病率有很强的相关性.
- 在临床实践中,NPAR显示了预测萨科佩尼亚的巨大潜力.
- 需要进一步的研究来验证NPAR的临床效率.
相关概念视频
Single Nucleotide Polymorphisms-SNPs
A single nucleotide polymorphism or SNP is a single nucleotide variation at a specific genomic position in a large population. It is the most prevalent type of sequence variation found in the human genome. Point mutations that occur in more than 1% of the population qualify as SNPs. These are present once every 1000 nucleotides on an average in the human genome. Replacement of a purine with another purine (A/G) or a pyrimidine with another pyrimidine (C/T) is known as a transition. In contrast,...
Bias in Epidemiological Studies
Biases can arise at various stages of research, from study design and data collection to analysis and interpretation. Recognizing and addressing these biases is essential to ensure the validity and reliability of epidemiological findings.Broadly speaking, biases in epidemiology fall into three main categories: selection bias, information bias, and confounding. A more detailed description of possible biases is:
Steps in Outbreak Investigation
In the ever-evolving field of public health, statistical analysis serves as a cornerstone for understanding and managing disease outbreaks. By leveraging various statistical tools, health professionals can predict potential outbreaks, analyze ongoing situations, and devise effective responses to mitigate impact. For that to happen, there are a few possible stages of the analysis:
Principles of Disease Surveillance
Disease surveillance is the systematic collection, analysis, and interpretation of health data essential to the planning, implementation, and evaluation of public health practice. This process integrates data dissemination to entities responsible for preventing and controlling disease, injury, and disability. Surveillance systems provide crucial information for action, helping public health authorities make informed decisions to manage and prevent outbreaks, ensure public safety, optimize...
Infectious Diseases and Their Occurrence
Infectious diseases appear in populations through various transmission patterns, influenced by pathogen characteristics, population immunity, environmental conditions, and social behavior. Understanding these patterns is essential for effective public health surveillance and intervention. These categories—sporadic, outbreak, epidemic, pandemic, and endemic—help frame the nature and scope of disease events.Sporadic diseases occur irregularly and infrequently, without a predictable temporal or...
Investigation of Disease Outbreaks
Multistate foodborne outbreaks pose significant public health risks and require meticulous investigation to identify sources and implement control measures. The Centers for Disease Control and Prevention (CDC) utilizes a dynamic seven-step process for these investigations, integrating data from laboratories, interviews, and environmental assessments to protect public health.Outbreak Detection: The detection of multistate outbreaks typically begins with PulseNet, the CDC's national laboratory...


