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Computerised Algorithms Showed Promise in Identifying Swedish Children With Atypical Growth Patterns.

Lars Gelander1, Aimon Niklasson1, Anton Holmgren1,2

  • 1Göteborg Pediatric Growth Research Centre, Department of Paediatrics, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Sweden.

Acta Paediatrica (Oslo, Norway : 1992)
|July 1, 2025
PubMed
Summary
This summary is machine-generated.

Finnish growth assessment algorithms effectively identified atypical growth patterns in Swedish children. These computerised methods offer a valuable tool for monitoring child development and identifying potential health concerns early.

Keywords:
BMIgrowth algorithmsheightmid parental heightprepubertal

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Area of Science:

  • Pediatrics
  • Public Health
  • Biostatistics

Background:

  • Accurate growth assessment is crucial for monitoring child development.
  • Comparing different growth assessment criteria is essential for optimizing screening protocols.
  • International Obesity Task Force (IOTF) provides global growth references.

Purpose of the Study:

  • To compare the performance of Finnish growth assessment algorithms with Swedish criteria and IOTF standards.
  • To evaluate the efficacy of Finnish algorithms in identifying atypical growth patterns in Swedish children.

Main Methods:

  • Utilized historical data from 3214 Swedish children aged 4, 6, and 8 years.
  • Compared five Finnish screening parameters including height-SDS and BMI-SDS against Swedish and IOTF references.
  • Analyzed BMI cut-offs across Swedish, Finnish, and IOTF growth references.

Main Results:

  • Finnish algorithms identified up to 1.8% of children with low or high height-SDS and noted changes over time.
  • Finnish algorithms detected 26.4% more children with underweight, overweight, or obesity compared to IOTF measures.
  • Swedish criteria identified a higher proportion of short (13.6-17.4%) and tall (15.5-18.6%) children, with most atypical cases identified by age 4.

Conclusions:

  • Computerised Finnish algorithms demonstrated capability in identifying Swedish children with atypical growth.
  • The study highlights the potential of Finnish screening parameters for international application in pediatric growth monitoring.