Predicting metabolic syndrome by using hematogram models in elderly women

Haixia Liu, Chun Hsien Hsu, Jiunn Diann Lin, Chang Hsun Hsieh, Wei Cheng Lian, Chung Ze Wu, Dee Pei, Yen Lin Chen

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)


Background: Low-grade inflammatory status was thought to be a major underlying mechanism in MetS. White blood cell (WBC) count was one of the inflammatory markers identified to be associated with MetS. Moreover, not only WBC but also hemoglobin (Hb) and platelet (PLT) were all associated with MetS. Objective: In this study, we tried to build models by the hematogram components. In this way, we can not only predict the occurrence of MetS with a relatively low-cost and routine lab test, but also can understand more about the relationships between low grade inflammation and MetS. Methods: We randomly collected subjects over 65 years old from MJ Health Screening Center's database between 1999 and 2008. After excluding subjects with medications for hypertension, hyperlipidemia and/or diabetes, 13132 female were eligible for analysis. Results: All the MetS components, hematogram parameters and age were higher in group with MetS. In the correlation matrix, all these three hematogram parameters (WBC, Hb and PLT) were correlated with MetS components except for the correlation between Hb and HDL-C. The ROC curves showed that the model 3 (PLT+Hb+WBC) had greatest area under the curve of 0.631 with the sensitivity of 58.1% and specificity of 61.4%. Conclusions: Our findings have shown that all the three hematogram parameters are related to MetS. The results not only shed light on the complex relationships, but also demonstrate a common and easy model to aid clinicians to be more aware of the occurrence of MetS.

Original languageEnglish
Pages (from-to)97-101
Number of pages5
Issue number2
Publication statusPublished - 2014


  • Hematogram
  • Hemoglobin
  • Metabolic syndrome
  • Platelet
  • White blood cell

ASJC Scopus subject areas

  • Hematology


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