title: The associations between leukocyte, erythrocyte or platelet, and metabolic syndrome in different genders of Chinese.
abstract: Leukocyte, erythrocyte or platelet and metabolic syndrome (MS) are closely correlated, and there exist gender differences. We aimed to explore the associations between the hematological parameters and MS in different genders of Chinese. This cross-sectional study included 32,900 participants (20,733 males, 12,167 females) who were enrolled in a health examination. Clinical data including anthropometric measurements and serum parameters were collected. The associations between hematological parameters and MS of both genders were analyzed separately. Odds ratio (OR) of MS was calculated by binary logistic regression models. All hematological parameters were related to MS. With leukocyte and erythrocyte counts rising, the risks of developing MS increased in both genders, which was more obvious in women. For instance, in model 3, the ORs of MS in leukocyte quartiles in females were from 1.333 to 2.045 (P < 0.01), while in males, from 1.238 to 1.675 (P < 0.01). Platelet seemed as a protective factor in males. Model 1 and model 3 in quartile 2 demonstrated ORs of 0.922 (P < 0.05) and 0.912 (P < 0.05). However, platelet acted as risk factor in female. For instance, the ORs were 1.253 (P < 0.01), 1.461 (P < 0.01), and 1.322 (P < 0.01) in platelet quartile 4 of all 3 models in female. Gender has influences on the associations between leukocyte, erythrocyte or platelet, and MS. In both genders, higher levels of leukocyte and erythrocyte increased risks of MS. For men, platelet was a protective factor, but for women, platelet seemed as a risk factor.
authors.affiliation: Department of Nuclear Medicine Department of Endocrinology and Metabolism Department of Health Management, Tianjin Medical University General Hospital, Tianjin, Peoples Republic of China.
authors.forename: Pingping
authors.initials: P
authors.lastname: Zhou
authors.forename: Zhaowei
authors.initials: Z
authors.lastname: Meng
authors.forename: Ming
authors.initials: M
authors.lastname: Liu
authors.forename: Xiaojun
authors.initials: X
authors.lastname: Ren
authors.forename: Mei
authors.initials: M
authors.lastname: Zhu
authors.forename: Qing
authors.initials: Q
authors.lastname: He
authors.forename: Qing
authors.initials: Q
authors.lastname: Zhang
authors.forename: Li
authors.initials: L
authors.lastname: Liu
authors.forename: Kun
authors.initials: K
authors.lastname: Song
authors.forename: Qiang
authors.initials: Q
authors.lastname: Jia
authors.forename: Jian
authors.initials: J
authors.lastname: Tan
authors.forename: Xue
authors.initials: X
authors.lastname: Li
authors.forename: Na
authors.initials: N
authors.lastname: Liu
authors.forename: Tianpeng
authors.initials: T
authors.lastname: Hu
authors.forename: Arun
authors.initials: A
authors.lastname: Upadhyaya
mesh_terms: D044466:Asian People; D001792:Blood Platelets; D003430:Cross-Sectional Studies; D004912:Erythrocytes; D005260:Female; D006801:Humans; D007962:Leukocytes; D008297:Male; D024821:Metabolic Syndrome / Q000097:blood*; D008875:Middle Aged; D012737:Sex Factors