Evidence map›Paper›PMID 41455931›Full record

ArticleBMC neurology2025

Association between inflammatory markers and Parkinson's disease risk: a cross-sectional, propensity score-matched analysis of NHANES data.

Yue Sun, Shuang Li, Shengming Shi, Yan Liu

Abstract read
In one paragraph

Article in BMC neurology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Yue SunDepartment of Geriatric Medicine, The First Affiliated Hospital of Huzhou Normal University, Huzhou First People's Hospital, Huzhou City, Zhejiang Province, China.
Shuang LiDepartment of General Practice, The First Affiliated Hospital of Huzhou Normal University, Huzhou First People's Hospital, Huzhou City, Zhejiang Province, China.
Shengming ShiDepartment of General Practice, The First Affiliated Hospital of Huzhou Normal University, Huzhou First People's Hospital, Huzhou City, Zhejiang Province, China.
Yan LiuDepartment of General Practice, The First Affiliated Hospital of Huzhou Normal University, Huzhou First People's Hospital, Huzhou City, Zhejiang Province, China. ly260147545@163.com.

Funding

Huzhou Science and Technology Bureau 2024GZB01
6 · The paper itself

Abstract

backgroundParkinson's disease (PD) is a chronic neurodegenerative disorder characterized by motor and non-motor symptoms, with neuroinflammation hypothesized to contribute to its pathogenesis. Systemic inflammation, as indicated by elevated peripheral inflammatory markers, has been implicated in PD; however, the relationship between complete blood count (CBC)-derived inflammatory markers and the presence of PD remains unclear.

methodsWe analyzed data from the National Health and Nutrition Examination Survey (NHANES) spanning 1999 to 2018, including 15,349 participants. Propensity score matching was employed to balance baseline characteristics between PD and non-PD groups. Multivariate logistic regression models were used to evaluate the association between CBC-derived inflammatory markers, particularly the neutrophil-to-lymphocyte ratio (NLR), and the presence of PD.

resultsAfter multivariable adjustment, elevated NLR was significantly associated with higher odds of PD. Individuals in the highest NLR quartile had higher odds of PD compared to those in the lowest quartile (OR: 2.18, 95% CI: 1.04-4.68; P for trend < 0.0001). This association was consistent across subgroups, including gender, diabetes status, hypertension, obesity, smoking, and alcohol consumption. Other CBC-derived markers, such as the monocyte-to-lymphocyte ratio (MLR), platelet-to-lymphocyte ratio (PLR), systemic immune-inflammation index (SII), and systemic inflammation response index (SIRI), did not show consistent associations with the presence of PD.

conclusionsElevated NLR is significantly associated with the presence of PD among U.S. adults, independent of key confounders. However, due to the cross-sectional study design and reliance on self-reported PD status, causality cannot be inferred, and misclassification bias cannot be excluded. Further longitudinal studies are warranted to validate these findings and clarify the temporal relationship between systemic inflammation and PD.

Indexed as

InflammationParkinson DiseaseAdultAgedBiomarkersCross-Sectional StudiesFemaleHumansMaleMiddle AgedNeutrophilsNutrition SurveysPropensity ScoreRisk FactorsUnited StatesBiomarkersCBC-derived markersInflammationNeutrophil-to-lymphocyte ratioNHANESParkinson's diseaseSystemic inflammation

Identifiers

PMID41455931
PMCPMC12853715

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.