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Wrist circumference in obese children may predict CVD

Capizzi M. Circulation. 2011;123:1757-1762.

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A manual measure of wrist circumference was more closely linked to insulin parameters than BMI in a cohort of overweight or obese children and adolescents, according to new study results published in Circulation.

The trial involved 477 overweight or obese children and adolescents in Rome (mean age, 10 years). Each participant’s wrist was manually measured. The researchers also evaluated standard deviation score BMI, fasting biochemical parameters and homeostasis model assessment of insulin resistance in the study population.

A subcohort of 51 randomly selected participants underwent a wrist MRI to assess transversal wrist area at the Lister tubercle level.

Wrist circumference was significantly linked with the parameters of insulin levels (β=0.34) and homeostasis model assessment of insulin resistance (β=0.35), according to the results.

Standard deviation BMI score yielded a statistical association of β=0.12 with insulin levels and β=0.10 with homeostasis model assessment of insulin resistance (P≤.02 for both comparisons).

In the MRI cohort, the link between wrist circumference and insulin levels was further clarified. Wrist circumference was associated insulin levels or homeostasis model assessment of insulin levels in bone tissue-related areas (P≤.01 for both comparisons) but not in adipose tissue areas (P<.05). MRI explained 20% of the variances in insulin levels and 17% of the variances in homeostasis model assessment of insulin levels.

The researchers noted that excess fat is a key determinant of insulin resistance which representing the metabolic basis for developing future cardiovascular disease. The aim of the study, they said, was to find a clinical marker of insulin resistance to identify young individuals at increased risk for CVD.

“Our findings suggest a close relationship among wrist circumference, its bone component, and insulin resistance in overweight/obese children and adolescents, opening new perspectives in the prediction of CVD,” the researchers wrote.

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