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Association between Leukocyte and Metabolic Syndrome in Urban Han Chinese: A Longitudinal Cohort Study

Public Library of Science
Publication Date
DOI: 10.1371/journal.pone.0049875
  • Research Article
  • Medicine
  • Clinical Research Design
  • Longitudinal Studies
  • Metabolic Disorders
  • Economics
  • Medicine


Background Although cross-sectional studies have shown that leukocyte is linked with metabolic syndrome (MetS), few longitudinal or cohort studies have been used to confirm this relationship. We therefore conducted a large-scale health check-up longitudinal cohort in urban Chinese population from middle to upper socioeconomic strata to investigate and prove the association between the total leukocyte/its subtypes and MetS/its components (obesity, hyperglycemia, dyslipidemia, and hypertension). Methods A longitudinal cohort study was established in 2005 on individuals who were middle-to-upper class urban Chinese. Data used in this investigation was based on 6,513 participants who had at least three routine health check-ups over a period of six-year follow-up. Data analysis was conducted through generalized estimating equation (GEE) model. Results A total of 255 cases of MetS occurred over the six-year follow-up, leading to a total incidence density of 11.45 per 1,000 person-years (255/22279 person-years). The total leukocyte was markedly associated with MetS (RR = 2.66, 95%CI = 1.81–3.90], p<0.0001) and a dose-response existed. Similar trends can be found in monocytes, lymphocytes, and neutrophils compared with the total leukocyte. The total leukocyte, neutrophil, monocyte and eosinophil levels were strong and independent risk factors to obesity, total leukocyte and neutrophil to dyslipidemia and hyperglycemia, while neither total leukocyte nor its subtypes to hypertension. Conclusion Total leukocyte/its subtype were associated with MetS/its components (obesity, dyslipidemia and hyperglycemia), they might provide convenient and useful markers for further risk appraisal of MetS, and be the earlier biomarkers for predicting cardiovascular disease than the components of MetS.

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