Association of cardiovascular risk factors in different anthropometric parameters in overweight or obese adults.

Authors

Motahareh Hasani, Leila Sheikhi, Soodeh Razeghi Jahromi, Maryam Khazdouz, Saleheh Ahmadzadeh, Zahra Rahimi, Saeed Alinejad, Sahar Mohammadipoornami, Mastaneh Rajabian Tabesh, Maryam Abolhasani

Published in

American heart journal plus : cardiology research and practice. Volume 68. Pages 100823. Epub Jul 01, 2026.

Abstract

Since overweight and obesity stands as a factor to the development of cardiovascular risk factors and the importance of targeted interventions to address their intertwined impact on public health, this investigation aimed to discover the association between cardiovascular risk factors and anthropometric parameters in adults with overweight or obesity.
This cross-sectional study evaluated 909 overweight or obese participants from Obesity Clinic and Minimally Invasive Surgery Research Center at Sinai Hospital. The participants were examined for lipid profile, glycemic index, and inflammatory indices. Anthropometric parameters were measured according to the World Health Organization (WHO) protocols. Linear and logistic regression methods were used to examine the relationship between various variables.
In the adjusted model, a significant negative association was observed between the LDL/HDL ratio and BMI (p = 0.05), whereas HDL showed a positive association with all anthropometric measures. No significant association was found between WC and the variables in the adjusted model. In the unadjusted model, QUICKI demonstrated significant associations with all anthropometric indices, similar to FBS and ESR. Despite, SBP demonstrated a significant association with WHtR (p = 0.04). Furthermore, LDL, insulin and HbA1c showed no significant associations with any of the anthropometric measures in either model (p > 0.05).
In conclusion, anthropometric indices may provide useful, though variable, insights into cardiovascular risk factors among overweight and obese individuals. Further research with larger samples and longitudinal design is needed to clarify these associations.

PMID:
42437180
Bibliographic data and abstract were imported from PubMed on 12 Jul 2026.

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