Published in:
01-06-2021 | Obesity | Research article
Association of a body shape index and hip index with cardiometabolic risk factors in children and adolescents: the CASPIAN-V study
Published in: Journal of Diabetes & Metabolic Disorders | Issue 1/2021
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Objective
This study designed to discover the link between a body shape index (ABSI) and hip index (HI) with cardiometabolic risk factors (CMRFs) in Iranian children and adolescents.
Subjects and methods
In a nationwide cross-sectional survey, 4200 students who were 7–18 years old were chosen via a multistage cluster sampling method in 30 provinces of Iran in 2015. Metabolic syndrome (MetS) was defined in line with the Adult Treatment Panel III criteria. ABSI and HI were defined as waist circumference (m)/ [body mass index 2/3 * height (m)1/2] and hip circumference (cm) *(height/ 166 cm)0.310 *(weight / 73 kg)−0.482 respectively. Association between ABSI and HI with CMRFs as categorical and continuous variables were evaluated using multivariable logistic and linear regression analysis respectively.
Results
Totally, information of 14,002 students and findings of blood samples of 3483 of them were involved in the current study. In the multivariable logistic regression, an association of HI with high triglyceride (TG) (OR: 0.99, 95 % CI: 0.98–0.99) and ABSI with MetS (OR: 11.41, 2.61–49.88) was statistically significant (P < 0.05). Also, both indices were significantly associated with overweight, generalized, and abdominal obesity. In the multivariable linear regression analysis, increasing HI (per one unit) was associated with body mass index z-score (z-BMI) (β: -0.01), waist circumference (WC) (β: 0.15), TG (β: -0.16), and systolic blood pressure (SBP) (β: -0.02). Moreover, in the multivariable linear models, ABSI was significantly associated with z-BMI, WC, SBP, and diastolic blood pressure (P < 0.001).
Conclusions
ABSI and HI as novel body shape indices were significantly associated with some CMRFs. Therefore, these indices can be used as some useful anthropometric risk indices for predicting MetS.