Body Mass Index, Waist Circumference, and the Clustering of Cardiometabolic Risk Factors in Early Childhood. Issue 2 (8th December 2015)

• Record Type: Journal Article
• Authors: Anderson, Laura N.; Lebovic, Gerald; Hamilton, Jill; Hanley, Anthony J.; McCrindle, Brian W.; Maguire, Jonathon L.; Parkin, Patricia C.; Birken, Catherine S.
• Is Part Of: Paediatric and perinatal epidemiology. Volume 30:Issue 2(2016:Mar.)
• Page Start: 160
• Page End: 170
• Publication Date: 2015-12-08
• Subjects: Pediatric obesity -- cardiovascular -- metabolic -- preschool children; Pediatrics -- Periodicals; Perinatology -- Periodicals; Pediatric epidemiology -- Periodicals; Infants (Newborn) -- Diseases -- Periodicals; 618.92
• DOI: 10.1111/ppe.12268
• Languages: English
• ISSNs: 0269-5022

Abstract

Abstract: Background: Obesity has its origins in early childhood; however, there is limited evidence of the association between anthropometric indicators and cardiometabolic risk factors in young children. Our aim was to evaluate the associations between body mass index (BMI) and waist circumference (WC) in relation to cardiometabolic risk factors and to explore the clustering of these factors. Methods: A cross‐sectional study was conducted in children aged 1–5 years through TARG et K ids! ( n = 2917). Logistic regression was used to evaluate associations between BMI and WC z‐scores and individual traditional and possible non‐traditional cardiometabolic risk factors. The underlying clustering of these measures was evaluated using principal components analysis (PCA). Results: Child obesity (BMI z‐score >2) was associated with high (>90th percentile) leptin [odds ratio (OR) 8.15, 95% confidence interval (CI) 4.56, 14.58] and insulin (OR = 1.76; 95% CI 1.05, 2.94). WC z‐score >1 was associated with high insulin (OR 1.59, 95% CI 1.11, 2.28), leptin (OR 5.48, 95% CI 3.48, 8.63) and 25‐hydroxyvitamin D < 75 nmol/L (OR 1.39, 95% CI 1.08, 1.79). BMI and WC were not associated with other traditional cardiometabolic risk factors, including non‐High Density Lipoprotein (HDL) cholesterol, and glucose. Among children 3–5 years ( n = 1035) the PCA of traditional risk factors identified three components: adiposity/blood pressure, metabolic, and lipids. The inclusion of non‐traditional risk factors identified four additional components but contributed minimally to the total variation explained. Conclusions: Anthropometric indicators are associated with selected cardiometabolic risk factors in early childhood, although the clustering of risk factors suggests that adiposity is only one distinct component of cardiometabolic risk. The measurement of other risk factors beyond BMI and WC may be important in defining cardiometabolic risk in early childhood.