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  • 11Department of Orthopaedics, Faculty of Medicine, University of British Columbia, Vancouver, British Columbia, CANADA; 2Centre for Hip Health and Mobility, Vancouver Coastal Health Research Institute, Vancouver, British Columbia, CANADA; 3Department of Family Medicine, Faculty of Medicine, University of British Columbia, Vancouver, British Columbia, CANADA; 4Child and Family Research Institute, BC Women's and Children's Hospital, Vancouver, British Columbia, CANADA; 5College of Kinesiology, University of Saskatchewan, Saskatoon, Saskatchewan, CANADA; 6Centre for Global Health and Human Development, Department of Sport, Exercise and Health Sciences, Loughborough University, Leicestershire, UNITED KINGDOM; 7Centre for Clinical Epidemiology and Evaluation, Vancouver Coastal Health Research Institute, Vancouver, British Columbia, CANADA; and 8Department of Statistics, Faculty of Science, University of British Columbia, Vancouver, British Columbia, CANADA.

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New equations accurately predict children's biological maturity using anthropometric data. These models were validated in external samples, offering a reliable alternative for somatic maturity assessment in pediatric studies.

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Area of Science:

  • Pediatric endocrinology
  • Human growth and development
  • Biometric analysis

Background:

  • Assessing biological maturity in children is crucial but challenging.
  • Existing sex-specific regression equations for somatic maturity prediction lack external validation.
  • Overfitting and calibration of these predictive models require thorough evaluation.

Purpose of the Study:

  • To evaluate the predictive accuracy of existing anthropometric equations for somatic maturity.
  • To assess and adjust for potential overfitting in these models.
  • To calibrate the equations using independent external datasets.

Main Methods:

  • Overfitting was assessed using the Pediatric Bone Mineral Accrual Study (PBMAS) data.
  • Forward-stepwise regression and cluster-robust variance were employed to determine predictor effects.
  • Calibration was performed using data from the Healthy Bones Study III (HBS-III) and Harpenden Growth Study (HGS).

Main Results:

  • Refitting original equations showed negligible changes in R and SEE, indicating overfitting.
  • Redeveloped models demonstrated strong predictive power: age × sitting height for boys (R=0.91) and age × height for girls (R=0.90).
  • These new models exhibited excellent calibration in external HBS-III and HGS samples, with low root mean squared errors (RMSE).

Conclusions:

  • Developed anthropometric equations provide accurate and well-calibrated predictions of somatic maturity in children.
  • These validated equations serve as a reliable alternative to existing models for pediatric growth studies.
  • Simplification of original prediction equations resulted in no significant loss of estimation accuracy.