Using hematogram model to predict future metabolic syndrome in elderly: A 4-year longitudinal study

Yu Hsiang Fu, Chun Hsien Hsu, Jiunn Diann Lin, Chang Hsun Hsieh, Chung Ze Wu, Ting Ting Chao, Dee Pei, Yao Jen Liang, Kun Wang, Yen Lin Chen

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)


Objectives: The metabolic syndrome (MetS) is proposed to predict future occurrence of cardiovascular diseases and diabetes. There are some other "non-traditional" risk factors such as hematogram components that are also related to the same endpoints as MetS. In this four-year longitudinal study, we used hematogram components to build models for predicting future occurrence of MetS in older men and women separately. Methods: Subjects above 65 years without MetS and related diseases were enrolled. All subjects were followed up until they developed MetS or until up to four years from the day of entry, whichever was earlier. Results: Among the 4539 study participants, 1327 developed MetS. Models were built for men and women separately and the areas under the receiver operation curves were significant. The Kaplan-Meier plot showed that the models could predict future MetS. Finally, Cox regression analysis showed that the hematogram model was correlated to future MetS with hazard ratios of 1.567 and 1.738 in men and women, respectively. Conclusion: Our hematogram models could significantly predict future MetS in elderly and might be more practical and convenient for daily clinical practice.

Original languageEnglish
Pages (from-to)38-43
Number of pages6
JournalAging Male
Issue number1
Publication statusPublished - Mar 1 2015


  • Hematogram
  • Hemoglobin
  • Metabolic syndrome
  • Platelets
  • White blood cell count

ASJC Scopus subject areas

  • Geriatrics and Gerontology


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