Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2024 May 11;12(5):1066.
doi: 10.3390/biomedicines12051066.

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  1 , Alexander Kalinkovich  2 , Shai Ashkenazi  1 , Stacey S Cherny  2 , Adel Shalata  3 , Gregory Livshits  1   2
Affiliations

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 et al. Biomedicines. .

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.

Keywords: GDF-15; adipokines; body composition; hyperlipidemia; hypertension; inflammation; multivariable statistical analyses; type 2 diabetes mellitus.

PubMed Disclaimer

Conflict of interest statement

The authors declare no conflicts of interest.

Figures

Figure 1
Figure 1
Directed acyclic graph among study measures, generated by additive Bayesian network modeling. Continuous variables are represented by ovals, and the squares represent binary variables. All quantitative variables were standardized before analysis. The coefficients on the arcs (paths) are the modes (beta) obtained from the posterior distributions of the coefficients, with the corresponding 95% credible intervals presented below in parentheses. The red arrows denote direct influences on CVD, and the black arrows indicate direct influences of CVD on other variables. Abbreviations: HTN, hypertension; HLD, hyperlipidemia; T2DM, type 2 diabetes mellitus; CVD, cardiovascular disease; ECW, extracellular water; L/A ratio, leptin/adiponectin ratio; GDF-15, growth differentiation factor-15; SIRI, systemic inflammation response index.
See this image and copyright information in PMC

Similar articles

See all similar articles

Cited by

References

    1. Bays H.E., Kulkarni A., German C., Satish P., Iluyomade A., Dudum R., Thakkar A., Rifai M., Al Mehta A., Thobani A., et al. Ten Things to Know about Ten Cardiovascular Disease Risk Factors—2022. Am. J. Prev. Cardiol. 2022;10:100342. doi: 10.1016/J.AJPC.2022.100342. - DOI - PMC - PubMed
    1. Laranjo L., Lanas F., Sun M.C., Chen D.A., Hynes L., Imran T.F., Kazi D.S., Kengne A.P., Komiyama M., Kuwabara M., et al. World Heart Federation Roadmap for Secondary Prevention of Cardiovascular Disease: 2023 Update. Glob. Heart. 2024;19:8. doi: 10.5334/GH.1278. - DOI - PMC - PubMed
    1. Cardiovascular Diseases (CVDs) [(accessed on 17 March 2024)]. Available online: https://www.who.int/news-room/fact-sheets/detail/cardiovascular-diseases...
    1. Zhao D., Liu J., Wang M., Zhang X., Zhou M. Epidemiology of Cardiovascular Disease in China: Current Features and Implications. Nat. Rev. Cardiol. 2019;16:203–212. doi: 10.1038/S41569-018-0119-4. - DOI - PubMed
    1. Vesa C.M., Popa L., Popa A.R., Rus M., Zaha A.A., Bungau S., Tit D.M., Aron R.A.C., Zaha D.C. Current Data Regarding the Relationship between Type 2 Diabetes Mellitus and Cardiovascular Risk Factors. Diagnostics. 2020;10:314. doi: 10.3390/DIAGNOSTICS10050314. - DOI - PMC - PubMed

LinkOut - more resources

  NODES
Association 8
COMMUNITY 3
Note 1
twitter 2