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Predicting insulin resistance in children: anthropometric and metabolic indicators
Sérgio R Moreira1, Aparecido P Ferreira, Ricardo M Lima
1Programa de Mestrado e Doutorado em Educação Física, Universidade Católica de Brasília (UCB), Brasília, DF, Brazil. sergior@pos.ucb.br
Insights
Anthropometric and metabolic indicators effectively predict insulin resistance in children aged 7-11. Key predictors include insulinemia, body fat percentage, and BMI, offering valuable insights for early detection and intervention.
Area of Science:
- Pediatric Endocrinology
- Metabolic Health
- Biostatistics
Background:
- Insulin resistance is a growing concern in pediatric populations, often linked to obesity.
- Early identification of insulin resistance is crucial for preventing long-term metabolic complications.
Purpose of the Study:
- To evaluate the predictive capability of various anthropometric and metabolic markers for insulin resistance in children.
- To determine optimal cutoff points for these indicators to maximize sensitivity and specificity.
Main Methods:
- A cross-sectional study involving 109 children (aged 7-11 years) with varying nutritional status (obese, overweight, well-nourished).
- Measurements included Body Mass Index (BMI), waist/hip circumferences, body fat percentage (DXA), fasting glucose, triglycerides, and insulin levels.
- Insulin resistance was assessed using the 90th percentile cutoff of the glycemic homeostasis method; Receiver Operating Characteristic (ROC) curves were analyzed.
Main Results:
- Insulinemia demonstrated the highest predictive power (AUC=0.99), followed by BMI (AUC=0.90) and body fat percentage (AUC=0.88) in the overall sample.
- Waist circumference also showed strong predictive value (AUC=0.88).
- Similar high predictive values were observed in the obese subgroup, particularly for insulinemia (AUC=0.99) and BMI (AUC=0.78).
Conclusions:
- Anthropometric and metabolic indicators possess significant predictive power for identifying insulin resistance in children aged 7-11.
- Optimized cutoff points for these indicators can enhance the accuracy of insulin resistance prediction in pediatric populations.
- These findings support the use of readily measurable indicators for early screening of insulin resistance.
Objective:
To predict insulin resistance in children based on anthropometric and metabolic indicators by analyzing the sensitivity and specificity of different cutoff points.
Methods:
A cross-sectional study was carried out of 109 children aged 7 to 11 years, 55 of whom were obese, 23 overweight and 31 well-nourished, classified by body mass index (BMI) for age. Measurements were taken to determine BMI, waist and hips circumferences, waist circumference/hip circumference ratio, conicity index and body fat percentage (dual emission X-ray absorptiometry). Fasting blood samples were taken to measure triglyceridemia, glycemia and insulinemia. Insulin resistance was evaluated by the glycemic homeostasis method, taking the 90th percentile as the cutoff point. Receiver operating characteristic curves were analyzed to a 95% confidence interval in order to identify predictors of glycemic homeostasis, and sensitivity and specificity were then calculated.
Results:
After analysis of the area under the receiver operating characteristic curve (confidence interval), indicators that demonstrated the power to predict insulin resistance were, in the following order: insulinemia = 0.99 (0.99-1.00), 18.7 microU mL(-1); body fat percentage = 0.88 (0.81-0.95), 41.3%; BMI = 0.90 (0.83-0.97), 23.69 kg m(2-(1)); waist circumference= 0.88 (0.79-0.96), 78.0 cm; glycemia = 0.71 (0.54-0.88), 88.0 mg dL(-1); triglyceridemia = 0.78 (0.66-0.90), 116.0 mg dL(-1) and conicity index = 0.69 (0.50-0.87), 1.23 for the whole sample; and were: insulinemia = 0.99 (0.98-1.00), 19.54 microU mL(-1); body fat percentage = 0.76 (0.64-0.89), 42.2%; BMI = 0.78 (0.64-0.92), 24.53 kg m(2-(1)); waist circumference = 0.77 (0.61-0.92), 79.0 cm and triglyceridemia = 0.72 (0.56-0.87), 127.0 mg dL(-1), for the obese subgroup.
Conclusions:
Anthropometric and metabolic indicators appear to offer good predictive power for insulin resistance in children between 7 and 11 years old, employing the cutoff points with the best balance between sensitivity and specificity of the predictive technique.
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