Predictive Ability of the Estimate of Fat Mass to Detect Early-Onset Metabolic Syndrome in Prepubertal Children with Obesity

Abstract

Body mass index (BMI), usually used as a body fatness marker, does not accurately discriminate between amounts of lean and fat mass, crucial factors in determining metabolic syndrome (MS) risk. We assessed the predictive ability of the estimate of FM (eFM) calculated using the following formula: FM = weight − exp(0.3073 × height2 − 10.0155 ×d-growth-standards/standards/body-mass-index-for-age-bmi-for-age weight− 1 + 0.004571 × weight − 0.9180 × ln(age) + 0.6488 × age0.5 + 0.04723×male + 2.8055) (exp = exponential function, score 1 if child was of black (BA), south Asian (SA), other Asian (AO), or other (other) ethnic origin and score 0 if not, ln = natural logarithmic transformation, male = 1, female = 0), to detect MS in 185 prepubertal obese children compared to other adiposity parameters. The eFM, BMI, waist circumference (WC), body shape index (ABSI), tri-ponderal mass index, and conicity index (C-Index) were calculated. Patients were classified as having MS if they met ≥ 3/5 of the following criteria: WC ≥ 95th percentile; triglycerides ≥ 95th percentile; HDL-cholesterol ≤ 5th percentile; blood pressure ≥ 95th percentile; fasting blood glucose ≥ 100 mg/dL; and/or HOMA-IR ≥ 97.5th percentile. MS occurred in 18.9% of obese subjects (p < 0.001), with a higher prevalence in females vs. males (p = 0.005). The eFM was correlated with BMI, WC, ABSI, and Con-I (p < 0.001). Higher eFM values were present in the MS vs. non-MS group (p < 0.001); the eFM was higher in patients with hypertension and insulin resistance (p < 0.01). The eFM shows a good predictive ability for MS. Additional to BMI, the identification of new parameters determinable with simple anthropometric measures and with a good ability for the early detection of MS, such as the eFM, may be useful in clinical practice, particularly when instrumentation to estimate the body composition is not available.

A height-weight formula to measure body fat in childhood obesity

“…In a retrospective study performed in a Danish cohort, FM estimated by this height-weight equation at 10 or 13 years was associated with adult risk of type 2 diabetes between 30 and 70 years better than childhood weight [ 20 ]. Furthermore, FM estimated by this equation was independently associated with subclinical atherosclerosis [ 13 ] and showed a good ability for detection of metabolic syndrome in Italian children and adolescents [ 21 ].…”

“…As secondary outcome, we found a greater relationship between BMI Z-score and FM or BF% as estimated by the height–weight equation than the BIA prediction model, after adjusting for gender, age and prepubertal stage. As far as we know, only Calcaterra et al have assessed the correlation between the height-weight equation with other indices of obesity, such as BMI ( r = 0.69, p < 0.001), waist circumference ( r = 0.32, p < 0.01) [ 21 ].…”

A Multivariate Analysis of “Metabolic Phenotype” Patterns in Children and Adolescents with Obesity for the Early Stratification of Patients at Risk of Metabolic Syndrome

“…As previously reported [ 31 ], a pathological level of fasting blood glucose (FBG) and/or IR was used as a marker of gluco-metabolic derangement, because impaired fasting glucose is rare in childhood and IR precedes glucose abnormalities [ 45 ]. The euglycemic–hyperinsulinemic clamp is the gold standard for measuring IR; however, this method is invasive, time-consuming, and is difficult to apply with pediatric patients.…”

“…Multivariate analysis (MVA) is used in medical research due to its ability to explore the structure of correlations and retrieve relevant associations within the data [ 29 , 30 ]. Studies on the inter-relationship of new adiposity indices with different metabolic phenotypes and cardiometabolic risk markers, according to sex, are limited in pediatrics [ 31 ].…”

The Relationship between Fat Mass Percentage and Glucose Metabolism in Children and Adolescents: A Systematic Review and Meta-Analysis

“…Meanwhile, the prevalence of prediabetes and diabetes was high among overweight and obese children [ 8 ]. Recently, it has been considered that the evaluation of body fat mass has a certain value in predicting abnormal glucose metabolism and metabolic syndrome in children [ 9 , 10 ]. Fat mass percentage (FMP) was positively associated with homeostasis model assessment insulin resistance (HOMA-IR) and glycosylated hemoglobin A1c (HbA1c), and South Asian children are more metabolically sensitive to adiposity [ 4 ].…”