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ORIGINAL RESEARCH article

Front. Nutr.
Sec. Nutritional Epidemiology
Volume 11 - 2024 | doi: 10.3389/fnut.2024.1439803
This article is part of the Research Topic Functional Foods for Metabolic Health View all 5 articles

Association of inflammation/nutrition-based indicators with Parkinson's disease and Mortality

Provisionally accepted
Huafang Jia Huafang Jia 1Kaixiang Yin Kaixiang Yin 2Jihu Zhao Jihu Zhao 2Fengyuan Che Fengyuan Che 3,4,5,6*
  • 1 Qingdao University, Qingdao, Shandong Province, China
  • 2 The Affiliated Hospital of Qingdao University, Qingdao, Shandong Province, China
  • 3 Independent researcher, Linyi, China
  • 4 Linyi People's Hospital, Linyi, China
  • 5 Shandong Provincial Health Commission, Linyi, China
  • 6 Key Laboratory for Translational Oncology, Xuzhou Medical University, linyi, China

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

    Objective: The study explores the association between inflammation/nutrition-based indicators, Parkinson's disease (PD), and all-cause mortality among adult participants. Methods: The analysis included 38,091 participants from National Health and Nutrition Examination Survey (NHANES) 1999-2018. Inflammation/nutrition-based indicators were derived from a comprehensive set of parameters, including neutrophil-albumin ratio (NAR), prognostic nutritional index (PNI), monocyte-albumin ratio (MAR), red cell distribution width-albumin ratio (RAR), hemoglobin, albumin, lymphocyte, and platelet (HALP) score, advanced lung cancer inflammation index (ALI), geriatric nutrition risk index (GNRI), and controlling nutritional status (CONUT) score. PD status was determined based on self-reported anti-parkinsonian medication use. Mortality data were obtained from the National Death Index, linked up to December 30, 2019. Results: After multivariate adjustment, all inflammation/nutrition-based indicators showed significant associations with all-cause mortality among adult participants. The random survival forest emphasized the importance of inflammation/nutrition-based indicators and their components in predicting mortality, with PNI and RAR being the most important indicators for predicting all-cause mortality. Individuals with PD have a significantly higher risk of all-cause mortality compared to those without PD (HR = 1.747 [1.363-2.238], P < 0.001) among adults. Additionally, elevated levels of inflammation/nutrition-based indicators are associated with a higher risk of all-cause mortality among individuals with PD compared to those without PD. This suggested a synergistic effect of PD and elevated levels of inflammatory/nutritional indicators on mortality risk. Specifically, individuals with PD and elevated NAR (HR=2.066 [1.398-3.052], P<0.001), MAR (HR=2.249 [1.612-3.138], P <0.001), RAR (HR=1.617 [1.179-2.218], P=0.003), ALI (HR=1.763 [1.225-2.537], P=0.002) and CONUT (HR=2.221 [1.434-3.440], P <0.001), and not elevated PNI (HR=1.771 [1.295-2.423], P <0.001), HALP (HR=1.738 [1.242-2.432], P=0.001), and GNRI (HR=2.689 [1.898-3.811], P <0.001) have a substantially higher risk of mortality compared to those without PD. Conclusion: Inflammation and nutrition status play crucial roles in predicting all-cause mortality among adults, particularly in the context of PD. The study underscores the importance of considering both factors in mortality risk assessment and provides valuable insights for future research and clinical practice.

    Keywords: Inflammation, nutrition, Parkinson's disease, Mortality, NHANES

    Received: 30 May 2024; Accepted: 04 Sep 2024.

    Copyright: © 2024 Jia, Yin, Zhao and Che. 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: Fengyuan Che, Independent researcher, Linyi, China

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