Literature DB >> 32140984

Leukocyte-related parameters in older adults with metabolic syndrome.

Xue-Jiao Yang1, Shun Tian1, Qing-Hua Ma2, Hong-Peng Sun1, Yong Xu1, Chen-Wei Pan3.   

Abstract

PURPOSE: We aimed to examine the association between leukocyte-related parameters and the risk of metabolic syndrome (MetS) in community-dwelling older Chinese adults, with a special focus on assessing the diagnostic ability of leukocyte-related parameters in detecting MetS and the potential interaction effect of sex in the leukocyte-MetS relationship.
METHODS: Study sample was from the Weitang Geriatric Diseases Study, which included 4579 individuals aged 60 years or above. MetS was diagnosed based on the Adult Treatment Panel III criteria. Leukocyte-related parameters were assessed using an automated hematology analyzer.
RESULTS: The adjusted odds ratio (95% confidence interval (CI)) of MetS for the highest quartile of leukocyte-related parameters (leukocyte, lymphocyte, neutrophil, monocyte, eosinophil, and basophil), when compared with the lowest quartile were 2.87 (2.30, 3.59), 2.69 (2.15, 3.36), 2.09 (1.67, 2.62), 2.12 (1.71, 2.64), 1.62 (1.31, 2.00), and 1.36 (1.11, 1.65), respectively. Adding leukocyte, lymphocyte, monocyte, and neutrophil to a model containing conventional risk factors improved risk prediction for MetS. Furthermore, significant interactions between leukocyte, monocyte, neutrophil, and sex on MetS were observed (all P value for interaction <0.01).
CONCLUSION: The numbers of total leukocytes, lymphocyte, monocyte, neutrophil, and eosinophil counts were elevated in older adults with MetS, suggesting that leukocyte-related parameters may be meaningful biomarkers for MetS. Adding leukocyte-related parameters to the conventional models increased the ability of predicting MetS among older adults. These parameters may be useful biomarkers for further risk appraisal of MetS in older adults.

Entities:  

Keywords:  Leukocyte-related parameter; Leukocytes; Metabolic syndrome; Older adults; Sex differences

Mesh:

Year:  2020        PMID: 32140984     DOI: 10.1007/s12020-020-02243-2

Source DB:  PubMed          Journal:  Endocrine        ISSN: 1355-008X            Impact factor:   3.633


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