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Development of a prediction equation for insulin sensitivity from anthropometry and fasting insulin in prepubertal
Terry T-K Huang1, Maria S Johnson, Michael I Goran
1Institute for Health Promotion and Disease Prevention Research, Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California 90089, USA.
Insights
A new prediction equation using ethnicity, calf skinfold, and fasting insulin accurately predicts insulin sensitivity in children. This method is more precise than the Homeostasis Model Assessment (HOMA) or fasting insulin alone.
Area of Science:
- Pediatric Endocrinology
- Metabolic Research
- Biostatistics
Background:
- Insulin sensitivity is crucial for metabolic health in children.
- Accurate prediction of insulin sensitivity is important for early identification of metabolic dysfunction.
- Current methods like HOMA have limitations in pediatric populations.
Purpose of the Study:
- To evaluate the Homeostasis Model Assessment (HOMA) for predicting insulin sensitivity in children.
- To develop and compare novel prediction equations for insulin sensitivity using demographic and anthropometric data.
- To assess the role of fasting insulin in these prediction models.
Main Methods:
- A study involving 156 children (mean age 9.7 years) of White and African-American ethnicity.
- Random assignment of participants into development (two-thirds) and cross-validation (one-third) groups.
- Utilized demographic, anthropometric measures, and fasting insulin levels.
Main Results:
- A modified HOMA equation showed utility but was comparable to fasting insulin alone.
- Demographic and anthropometric measures, including body composition, did not accurately predict insulin sensitivity independently.
- Ethnicity, calf skinfold, and fasting insulin together explained 73% of the variance in insulin sensitivity (R² = 0.73).
Conclusions:
- Ethnicity, calf skinfold, and fasting insulin provide a more precise prediction of insulin sensitivity than HOMA or fasting insulin alone.
- The developed cross-validated prediction equation demonstrated good accuracy.
- Further research is needed to determine the feasibility of a universal prediction equation for pediatric insulin sensitivity.
Objective:
To test the utility of homeostasis model assessment (HOMA) in predicting insulin sensitivity [x10(- 4) min(-1)/(microIU/ml)] in children and to develop and compare two new prediction equations for insulin sensitivity in children using demographic and anthropometric measures in the presence or absence of fasting insulin.
Research Design And Methods:
We studied 156 white and African-American children with complete data (mean age 9.7 +/- 1.8 years, 87.8% Tanner Stage 1 or 2). For development of new equations, two-thirds of the children were randomly assigned to a development group, whereas the remaining children were assigned to a cross-validation group.
Results:
A modified HOMA equation accurately predicted insulin sensitivity, but its utility is similar to fasting insulin alone. Demographic and anthropometric measures alone did not predict insulin sensitivity accurately, even when precise measures of body composition were included in the prediction model. Ethnicity, calf skinfold, and fasting insulin together explained 73% of the variance in insulin sensitivity and accurately predicted insulin sensitivity. The regression of measured versus predicted insulin sensitivity in the cross-validation group was not significantly different from the line of identity (P > 0.05). Mean difference between measured and predicted insulin sensitivity was also not significant (P > 0.05). Some bias was apparent, particularly in white boys.
Conclusions:
Ethnicity, calf skinfold, and fasting insulin can accurately predict insulin sensitivity with greater precision than HOMA or fasting insulin alone (R(2) = 0.73). Future studies, however, are needed to examine whether a universal equation is possible. A cross-validated prediction equation may be useful in population-based studies when complex measures of insulin sensitivity are not available.
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