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Assessment of Child Anthropometry in a Large Epidemiologic Study
Published on: February 2, 2017
Cardiometabolic risk stratification in pediatric obesity: evaluating the clinical utility of fasting insulin and
Rasmus Stenlid1,2, Sami El Amrani3, Sara Y Cerenius1,2
1Department of Medical Cell Biology, Uppsala University, Uppsala, Sweden.
Insights
Fasting insulin, not just BMI-SDS, helps identify children with obesity at high cardiometabolic risk. Elevated insulin levels in children warrant further investigation for conditions like dyslipidemia and dysglycemia.
Area of Science:
- Pediatric Endocrinology
- Cardiovascular Health
- Metabolic Syndrome
Background:
- Childhood obesity increases adult cardiovascular disease risk.
- Body Mass Index (BMI) standard deviation score (BMI-SDS) may underestimate risk in some children.
- Fasting insulin is a potential marker for cardiometabolic risk.
Purpose of the Study:
- To compare cardiometabolic risk assessment using BMI-SDS versus fasting insulin in children and adolescents.
- To evaluate the predictive accuracy of each marker for key cardiometabolic risk factors.
Main Methods:
- International cohort study of 712 children with obesity and 99 lean controls (ages 3-18).
- Categorization by BMI-SDS and fasting insulin quartiles.
- Assessment of dyslipidemia, dysglycemia, and hypertension prevalence.
- Statistical analyses including ROC and logistic regression.
Main Results:
- Elevated cardiometabolic risk factors (dyslipidemia, dysglycemia, hypertension) correlated with higher BMI-SDS and fasting insulin levels.
- Fasting insulin showed higher predictive accuracy (AUC) for dyslipidemia, dysglycemia, and combined risk than BMI-SDS.
- BMI-SDS was more accurate for hypertension detection, but fasting insulin had a stronger overall association with risk factors.
Conclusions:
- Fasting insulin offers valuable complementary information to BMI-SDS for identifying at-risk children with obesity.
- Neither marker alone is fully predictive, but insulin can help prioritize evaluations.
- Elevated fasting insulin in pediatric obesity warrants further investigation, regardless of BMI-SDS classification.
Background:
Patients with obesity during childhood have an increased risk of fatal and non-fatal cardiovascular events during adulthood. The severity of obesity is commonly determined by BMI. However, children with relatively low BMI may have high cardiometabolic risk. Indeed, BMI-based obesity classifications might miss children at high cardiometabolic risk. Insulin has been suggested as a marker of cardiometabolic risk. In this study, we therefore estimated and compared cardiometabolic risk using either the BMI standard deviation score (BMI-SDS) or fasting insulin in an international cohort of children and adolescents with obesity and lean controls.
Methods:
Study participants (712 with obesity and 99 lean controls), aged 3 to 18 years, were categorized according to their BMI-SDS as lean or obesity class I, II, or III, or by their fasting insulin quartiles as quartile 1, 2, 3, or 4 with the lean subjects in a separate control group. Prevalence of cardiometabolic risk factors was assessed in each group. Sensitivity and specificity analyses for cardiometabolic risk were conducted for both BMI-SDS and fasting insulin. Multiple regression, logistic regression, and receiver operating characteristic (ROC) analyses were performed between fasting insulin, BMI-SDS and cardiometabolic risk factors.
Results:
An elevated prevalence of the cardiometabolic risk factors dyslipidemia, dysglycemia and hypertension was observed in both increasing BMI-SDS classes and increasing fasting insulin quartiles. Fasting insulin demonstrated higher areas under the curve (AUC) for detecting dyslipidemia, dysglycemia, and the combination of dyslipidemia, dysglycemia, and hypertension, compared to BMI-SDS. BMI-SDS demonstrated a higher AUC for detecting hypertension compared to fasting insulin. The same patterns were seen for the logistic regression. However, fasting insulin had an overall stronger association with the cardiometabolic risk factors studied compared to BMI-SDS.
Conclusions:
In children and adolescents with obesity, fasting insulin provides complementary information to BMI-SDS in identifying those with elevated cardiometabolic risk factors. While neither marker alone offers strong predictive accuracy, incorporating fasting insulin into clinical assessment may help prioritize individuals who require more detailed evaluation. An elevated fasting insulin value may warrant further investigation among children and adolescents with obesity, independent of obesity class based on BMI-SDS.
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