Analysis of the Associations of Measurements of Body Composition and Inflammatory Factors with Cardiovascular Disease and Its Comorbidities in a Community-Based Study

Nader Tarabeih, Alexander Kalinkovich, Shai Ashkenazi, Stacey S. Cherny, Adel Shalata, Gregory Livshits

Research output: Contribution to journalArticlepeer-review

Abstract

The associations of cardiovascular disease (CVD) with comorbidities and biochemical and body composition measurements are repeatedly described but have not been studied simultaneously. In the present cross-sectional study, information on CVD and comorbidities [type 2 diabetes mellitus (T2DM), hypertension (HTN), and hyperlipidemia (HDL)], body composition, levels of soluble markers, and other measures were collected from 1079 individuals. When we examined the association of each comorbidity and CVD, controlling for other comorbidities, we observed a clear pattern of the comorbidity-related specific associations with tested covariates. For example, T2DM was significantly associated with GDF-15 levels and the leptin/adiponectin (L/A) ratio independently of two other comorbidities; HTN, similarly, was independently associated with extracellular water (ECW) levels, L/A ratio, and age; and HDL was independently related to age only. CVD showed very strong independent associations with each of the comorbidities, being associated most strongly with HTN (OR = 10.89, 6.46–18.38) but also with HDL (2.49, 1.43–4.33) and T2DM (1.93, 1.12–3.33). An additive Bayesian network analysis suggests that all three comorbidities, particularly HTN, GDF-15 levels, and ECW content, likely have a main role in the risk of CVD development. Other factors, L/A ratio, lymphocyte count, and the systemic inflammation response index, are likely indirectly related to CVD, acting through the comorbidities and ECW.

Original languageEnglish
Article number1066
JournalBiomedicines
Volume12
Issue number5
DOIs
StatePublished - May 2024

Keywords

  • adipokines
  • body composition
  • GDF-15
  • hyperlipidemia
  • hypertension
  • inflammation
  • multivariable statistical analyses
  • type 2 diabetes mellitus

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