Evidence map›Paper›PMID 40119384›Full record

ArticleBMC women's health2025

Association between triglyceride levels and rheumatoid arthritis prevalence in women: a cross-sectional study of NHANES (1999-2018).

Chang-Mei Zeng, Jun He, Deng-Chao Wang, Hong Xie

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Article in BMC women's health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

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3citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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3 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Chang-Mei ZengDepartment of Endocrinology and Metabolic Diseases (Diabetes Section, including Rheumatology Specialty), Suining Municipal Hospital Of Traditional Chinese Medicine, No. 73, Tianfeng Street, Chuanshan District, Suining, 629000, Sichuan, China. changmeizeng@163.com.
Jun HeDepartment of Endocrinology and Metabolic Diseases (Diabetes Section, including Rheumatology Specialty), Suining Municipal Hospital Of Traditional Chinese Medicine, No. 73, Tianfeng Street, Chuanshan District, Suining, 629000, Sichuan, China.
Deng-Chao WangDepartment of General Surgery, Zigong Fourth People's Hospital, Zigong, 643000, Sichuan, China.
Hong XieDepartment of General Medicine, Zigong Fourth People's Hospital, Zigong, 643000, Sichuan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundRheumatoid arthritis (RA) is a chronic autoimmune disease with a higher prevalence in women. Triglycerides, key indicators of lipid metabolism, are linked to inflammation and metabolic disorders, both contributing to RA pathogenesis. However, the association between triglyceride levels and RA prevalence in women remains unclear. This study analyzes this association using NHANES (1999-2018) data to provide evidence for prevention and personalized intervention strategies.

methodsThis study utilized data from the National Health and Nutrition Examination Survey (NHANES) spanning 1999 to 2018. It included 10,728 female participants, of whom 639 were diagnosed with RA. Triglyceride levels were categorized into four quartiles (Q1 to Q4), and multivariable logistic regression models were used to analyze the association between triglyceride levels and RA prevalence in women. Restricted cubic spline (RCS) analyses were performed to evaluate the potential nonlinear association between triglyceride levels and RA prevalence. Subgroup and interaction analyses were conducted to further investigate the association across different populations.

resultsAmong the 639 RA patients, higher triglyceride levels were significantly positively associated with RA prevalence in women. In the unadjusted model, elevated triglyceride levels were significantly associated with an increased RA prevalence (OR: 1.30, 95% CI: 1.04-1.61, P = 0.019). This association remained significant in the adjusted model, with the highest quartile showing a substantially higher risk compared to the lowest quartile (OR: 2.46, 95% CI: 1.22-4.95, P for trend = 0.04). RCS analyses indicated a linear association between triglyceride levels and RA prevalence (P for nonlinearity = 0.19). Subgroup analyses revealed consistent trends across various subgroups, with no significant interactions observed (all interaction P-values > 0.05).

conclusionThis study demonstrates a significant positive association between elevated triglyceride levels and RA prevalence in women, with a linear trend observed in this association. Future research should further investigate the role of triglyceride levels in the pathogenesis of RA and explore potential intervention pathways.

Indexed as

Arthritis, RheumatoidTriglyceridesAdultAgedCross-Sectional StudiesFemaleHumansMiddle AgedNutrition SurveysPrevalenceRisk FactorsUnited StatesTriglyceridesEepidemiologyLogistic regressionNHANESNonlinear associationRheumatoid arthritisTriglyceridesWomen

Identifiers

PMID40119384
PMCPMC11927311

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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.