Association Between High-Sensitivity C-Reactive Protein Trajectories and the Incidence of Metabolic Syndrome:A Retrospective Cohort Study
JianJiang Pan,1,* XiXuan Cai,1,* JieRu Chen,1 MingYing Xu,1 JingYu Hu,1 YueChun Mao,1 Tao Chen,2 LuSha Li,1 MengQi Jin,1 LiYing Chen1 1Department of General Practice, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, 310020, People’s Republic of...
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Dove Medical Press
2024-11-01
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| Series: | Journal of Inflammation Research |
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| author | Pan J Cai X Chen J Xu M Hu J Mao Y Chen T Li L Jin M Chen L |
| author_facet | Pan J Cai X Chen J Xu M Hu J Mao Y Chen T Li L Jin M Chen L |
| author_sort | Pan J |
| collection | DOAJ |
| description | JianJiang Pan,1,* XiXuan Cai,1,* JieRu Chen,1 MingYing Xu,1 JingYu Hu,1 YueChun Mao,1 Tao Chen,2 LuSha Li,1 MengQi Jin,1 LiYing Chen1 1Department of General Practice, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, 310020, People’s Republic of China; 2Department of General Practice, Jianqiao Community Health Service Center, Hangzhou, Zhejiang, 310021, People’s Republic of China*These authors contributed equally to this workCorrespondence: LiYing Chen, Department of General Practice, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, People’s Republic of China, Email 3197020@zju.edu.cnPurpose: Understanding the role of systemic inflammation in the development of Metabolic Syndrome (MetS) is crucial for identifying individuals at a higher risk of this cluster of conditions that increase the risk of heart disease, stroke, and diabetes.Patients and Methods: A retrospective cohort study was conducted with 4,312 participants who were free from MetS at the study’s onset and had high-sensitivity C-reactive protein (hsCRP) levels measured. Latent class trajectory modeling was utilized to identify distinct hsCRP trajectory patterns. Multivariable regression and proportional hazards analyses were employed to evaluate the predictive value of hsCRP trajectories for the development of MetS.Results: During the 1.63-year follow-up period, 1,308 participants developed metabolic syndrome (MetS). Individuals with high hsCRP levels exhibited a significantly increased risk of developing MetS compared to those with low hsCRP levels (HR = 1.062, 95% CI 1.103– 1.113). The hsCRP trajectory analysis identified three distinct groups: low-stable, increasing, and decreasing. The decreasing and increasing hsCRP trajectory groups demonstrated a 1.408-fold (95% CI 1.115– 1.779) and a 1.618-fold (95% CI 1.288– 2.033) increased risk of MetS, respectively.Conclusion: This study suggests that participants with higher baseline hsCRP levels and increasing hsCRP trajectories are associated with a progression toward MetS. Long-term hsCRP trajectories may serve as useful tools for identifying individuals at higher risk of MetS who could benefit from targeted preventive and therapeutic interventions.Keywords: high-sensitivity C-reactive protein, metabolic syndrome, trajectory analysis, retrospective cohort study, risk prediction |
| format | Article |
| id | doaj-art-279579f5b3eb46b59a1f5f98f1700f13 |
| institution | OA Journals |
| issn | 1178-7031 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | Dove Medical Press |
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| series | Journal of Inflammation Research |
| spelling | doaj-art-279579f5b3eb46b59a1f5f98f1700f132025-08-20T02:13:55ZengDove Medical PressJournal of Inflammation Research1178-70312024-11-01Volume 178501851197122Association Between High-Sensitivity C-Reactive Protein Trajectories and the Incidence of Metabolic Syndrome:A Retrospective Cohort StudyPan JCai XChen JXu MHu JMao YChen TLi LJin MChen LJianJiang Pan,1,* XiXuan Cai,1,* JieRu Chen,1 MingYing Xu,1 JingYu Hu,1 YueChun Mao,1 Tao Chen,2 LuSha Li,1 MengQi Jin,1 LiYing Chen1 1Department of General Practice, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, 310020, People’s Republic of China; 2Department of General Practice, Jianqiao Community Health Service Center, Hangzhou, Zhejiang, 310021, People’s Republic of China*These authors contributed equally to this workCorrespondence: LiYing Chen, Department of General Practice, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, People’s Republic of China, Email 3197020@zju.edu.cnPurpose: Understanding the role of systemic inflammation in the development of Metabolic Syndrome (MetS) is crucial for identifying individuals at a higher risk of this cluster of conditions that increase the risk of heart disease, stroke, and diabetes.Patients and Methods: A retrospective cohort study was conducted with 4,312 participants who were free from MetS at the study’s onset and had high-sensitivity C-reactive protein (hsCRP) levels measured. Latent class trajectory modeling was utilized to identify distinct hsCRP trajectory patterns. Multivariable regression and proportional hazards analyses were employed to evaluate the predictive value of hsCRP trajectories for the development of MetS.Results: During the 1.63-year follow-up period, 1,308 participants developed metabolic syndrome (MetS). Individuals with high hsCRP levels exhibited a significantly increased risk of developing MetS compared to those with low hsCRP levels (HR = 1.062, 95% CI 1.103– 1.113). The hsCRP trajectory analysis identified three distinct groups: low-stable, increasing, and decreasing. The decreasing and increasing hsCRP trajectory groups demonstrated a 1.408-fold (95% CI 1.115– 1.779) and a 1.618-fold (95% CI 1.288– 2.033) increased risk of MetS, respectively.Conclusion: This study suggests that participants with higher baseline hsCRP levels and increasing hsCRP trajectories are associated with a progression toward MetS. Long-term hsCRP trajectories may serve as useful tools for identifying individuals at higher risk of MetS who could benefit from targeted preventive and therapeutic interventions.Keywords: high-sensitivity C-reactive protein, metabolic syndrome, trajectory analysis, retrospective cohort study, risk predictionhttps://www.dovepress.com/association-between-high-sensitivity-c-reactive-protein-trajectories-a-peer-reviewed-fulltext-article-JIRhigh-sensitivity c-reactive proteinmetabolic syndrometrajectory analysisretrospective cohort studyrisk prediction |
| spellingShingle | Pan J Cai X Chen J Xu M Hu J Mao Y Chen T Li L Jin M Chen L Association Between High-Sensitivity C-Reactive Protein Trajectories and the Incidence of Metabolic Syndrome:A Retrospective Cohort Study Journal of Inflammation Research high-sensitivity c-reactive protein metabolic syndrome trajectory analysis retrospective cohort study risk prediction |
| title | Association Between High-Sensitivity C-Reactive Protein Trajectories and the Incidence of Metabolic Syndrome:A Retrospective Cohort Study |
| title_full | Association Between High-Sensitivity C-Reactive Protein Trajectories and the Incidence of Metabolic Syndrome:A Retrospective Cohort Study |
| title_fullStr | Association Between High-Sensitivity C-Reactive Protein Trajectories and the Incidence of Metabolic Syndrome:A Retrospective Cohort Study |
| title_full_unstemmed | Association Between High-Sensitivity C-Reactive Protein Trajectories and the Incidence of Metabolic Syndrome:A Retrospective Cohort Study |
| title_short | Association Between High-Sensitivity C-Reactive Protein Trajectories and the Incidence of Metabolic Syndrome:A Retrospective Cohort Study |
| title_sort | association between high sensitivity c reactive protein trajectories and the incidence of metabolic syndrome a retrospective cohort study |
| topic | high-sensitivity c-reactive protein metabolic syndrome trajectory analysis retrospective cohort study risk prediction |
| url | https://www.dovepress.com/association-between-high-sensitivity-c-reactive-protein-trajectories-a-peer-reviewed-fulltext-article-JIR |
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