SEARCHCROSS-SECTIONALepidemiology, public health

cross-sectional·epidemiology, public health, internal medicine, cardiology, endocrinology·PMC10000634

Investigating the relationship between haematological parameters and metabolic syndrome: A population‐based study

Endocrinology, Diabetes & Metabolism · 6 authors, 6 centres

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TL;DR

Metabolic syndrome (MetS) was defined using ATP III criteria.

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Metabolic syndrome (MetS) was defined using ATP III criteria. The study investigated correlations between various haematological parameters and MetS components, and evaluated the predictive value of WBC and its subtypes for MetS using ROC curves. Key results showed that WBC, neutrophil, lymphocyte, monocyte, red cell distribution width (RDW), monocyte-to-HDL ratio (MHR), and neutrophil-to-HDL ratio (NHR) were significantly positively correlated with the number of MetS components.

STUDY TYPE

cross-sectional

SPECIALTY

epidemiology

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ORIGINAL PAPER

PMC10000634

Investigating the relationship between haematological parameters and metabolic syndrome: A population‐based study

Endocrinology, Diabetes & Metabolism

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ABSTRACT

Abstract Background Metabolic syndrome (MetS) is a global public health concern. Chronic inflammation plays a role in MetS; haematological inflammatory parameters can be used as MetS predicting factors. Objective Hereditary and environmental factors play an important role in the development of MetS. This study aimed to determine the relationship between haematological parameters and MetS in the adult population of southeastern Iran, Kerman. Methods This cross‐sectional study was a sub‐analysis of 1033 subjects who participated in the second phase of the Kerman Coronary Artery Disease Risk Factor Study (KERCADRS). Metabolic syndrome was diagnosed according to Adult Treatment Panel III (ATP III) definition. Pearson correlation coefficient was used to investigate the relationship between haematological parameters with age and components of metabolic syndrome. The role of WBC, neutrophil, lymphocyte and monocyte in predicting metabolic syndrome was evaluated using the receiver operating characteristic (ROC) curve. Results White blood cell (WBC) and its subcomponent cells count, red cell distribution width (RDW), monocyte to HDL ratio (MHR) and Neutrophil to HDL ratio (NHR) had a significant positive correlation with the severity of MetS. The cut‐off value of WBC was 6.1 (×10 3 /μL), the sensitivity was 70%, the specificity was 52.9% for females, the cut‐off value of WBC was 6.3 (×10 3 /μL), the sensitivity was 68.2% and the specificity was 46.7%, for males. Conclusion WBC and its subcomponent count, RDW, MHR and NHR parameters are valuable biomarkers for further risk appraisal of MetS in adults. These markers are helpful in early diagnoses of individuals with MetS.

CITATION EXPORT

Mohammad Javad Najafzadeh, Amir Baniasad, Reza Shahabinejad et al.. Investigating the relationship between haematological parameters and metabolic syndrome: A population‐based study. Endocrinology, Diabetes & Metabolism. (2023). https://doi.org/10.1002/edm2.407

AUTHORS

6 · 6 CENTRES

Mohammad Javad Najafzadeh, Amir Baniasad, Reza Shahabinejad, Mahdieh Mashrooteh, Hamid Najafipour, Mohammad Hossein Gozashti

1 Gastroenterology and Hepatology Research Center Institute of Basic and Clinical Physiology Sciences, Kerman University of Medical Sciences Kerman Iran
2 Endocrinology and Metabolism Research Center Institute of Basic and Clinical Physiology Science, Kerman University of Medical Sciences Kerman Iran
3 Physiology Research Center Institute of Basic and Clinical Physiology Sciences, Kerman University of Medical Sciences Kerman Iran
4 Modeling in Health Research Center Institute for Futures Studies in Health, Kerman University of Medical Sciences Kerman Iran
5 Cardiovascular Research Center Institute of Basic and Clinical Physiology Sciences, Kerman University of Medical Sciences Kerman Iran
6 Endocrinologist, Endocrinology and Metabolism Research Center Institute of Basic and Clinical Physiology Sciences, Kerman University of Medical Sciences Kerman Iran