Evidence map›Paper›PMID 41803945›Full record

ArticleJournal of health, population, and nutrition2026

Residual inflammatory risk as a predictor of cardiometabolic multi-morbidity: results from three prospective cohorts.

Shihai Wang, Xiaobin Zeng, Jianjun Lan, Shiyang Li

Abstract read
In one paragraph

Article in Journal of health, population, and nutrition, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Shihai WangDivision of Cardiology, Panzhihua Central Hospital, Panzhihua, China.
Xiaobin ZengDivision of Cardiology, Panzhihua Central Hospital, Panzhihua, China.
Jianjun LanDivision of Cardiology, Panzhihua Central Hospital, Panzhihua, China.
Shiyang LiDepartment of Geriatrics, Panzhihua Central Hospital, Panzhihua 34# Yi Kang Ave, 617000, Panzhihua, China. LSYpanzhihua@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundInflammation and its dynamic changes are intricately linked to cardiovascular diseases. This research aimed to explore the predictive significance of residual inflammatory risk (RIR) in evaluating the likelihood of developing cardiometabolic multi-morbidity (CMM).

methodsData were sourced from the China Health and Retirement Longitudinal Study (CHARLS), the Health and Retirement Study (HRS) and panzhihua central hospital. Inflammation status was assessed using at least two high-sensitivity C-reactive protein (hsCRP) measurements taken at baseline and follow-up, with a minimum interval of four weeks. High RIR was characterized by an hsCRP level exceeding 2 mg/L. Participants were categorized into four groups: persistent high RIR, increased RIR (initially low, subsequently high hsCRP), attenuated RIR (initially high, subsequently low hsCRP), and persistent low RIR. Multivariable Cox proportional hazards regression and subgroup analyses were employed to examine the relationship between RIR and CMM.

resultsThe study included 5,572 participants from the CHARLS (56.26% female, mean age 57.87 years), 3,856 participants from the HRS (60.35% female, mean age 65.74 years), and 2,446 participants from the panzhihua central hospital (54.17% female, mean age 58.65 years). Utilizing Cox proportional hazards regression, participants with persistent high RIR exhibited a significant association with an increased risk of developing CMM compared to those with persistent low RIR (CHARLS: HR = 2.2, 95% CI = 1.79-2.69, P < 0.001; HRS: HR = 1.79, 95% CI = 1.47-2.18, P < 0.001; panzhihua cohort: HR = 3.97, 95% CI = 2.52-6.27, P < 0.001). This association persisted after comprehensive adjustment for potential confounders (CHARLS: HR = 1.81, 95% CI = 1.47-2.23, P < 0.001; HRS: HR = 1.69, 95% CI = 1.38-2.08, P < 0.001; panzhihua cohort: HR = 3.74, 95% CI = 2.34-5.99, P < 0.001). Subgroup analyses further confirmed the robustness of the association between persistent high RIR and CMM across all examined subgroups.

conclusionPersistent high RIR was correlated with an increased risk of CMM. Future research is needed to determine whether anti-inflammatory strategies targeting RIR reduction could mitigate CMM risk.

Indexed as

Cardiovascular DiseasesInflammationAgedCardiometabolic Risk FactorsChinaC-Reactive ProteinFemaleHumansLongitudinal StudiesMaleMiddle AgedProportional Hazards ModelsProspective StudiesRisk FactorsC-Reactive ProteinCardiometabolic multimorbidityCHARLSHigh-sensitive c-reactive proteinHRSResidual inflammatory riskRisk

Identifiers

PMID41803945
PMCPMC13085376

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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.