ESTIMATION OF PEDIATRIC HEIGHT FROM TIBIAL LENGTH IN MEDICAL CITY HOSPITALS

Background: Accurate estimation of stature in children is essential in clinical, emergency, and forensic settings where direct measurement may be impractical. This study aimed to evaluate the relationship between tibial length and pediatric height in Iraqi children and to establish regression equations for reliable stature estimation. Method: A cross-sectional study was conducted at the Medical City Complex in Baghdad from January to June 2025, including 300 children aged 1–15 years without musculoskeletal deformities or growth disorders. Standardized measurements of tibial length and height were obtained. Results: showed that 62.3% of participants were older than 5 years, with nearly equal gender distribution (50.7% females, 49.3% males). Children older than 5 years demonstrated significantly greater mean tibial length (29.48 ± 4.39 cm) and height (126.16 ± 13.54 cm) compared with younger children (21.04 ± 2.79 cm and 95.87 ± 8.27 cm, respectively; p = 0.0001). Regression equations derived from tibial length showed strong predictive accuracy for height estimation. Correlation was particularly strong among younger children (≤5 years; p = 0.0001) and females (p = 0.0001), while associations in males and older children were weaker. Conclusion: The study confirms tibial length as a robust predictor of pediatric stature in the Iraqi population, with stronger associations in early childhood. Establishing locally validated regression models enhances clinical decision-making in growth assessment, drug dosing, and emergency care, while also providing forensic value for stature reconstruction. Future multicenter research is recommended to refine predictive equations and broaden their applicability.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-10-01
DOI
https://doi.org/10.5281/zenodo.17224264
Primary Topic
Genomics and Phylogenetic Studies
Type
article
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article

ESTIMATION OF PEDIATRIC HEIGHT FROM TIBIAL LENGTH IN MEDICAL CITY HOSPITALS

Zenodo (CERN European Organization for Nuclear Research)
Genomics and Phylogenetic Studies
article

ESTIMATION OF PEDIATRIC HEIGHT FROM TIBIAL LENGTH IN MEDICAL CITY HOSPITALS

article en

Abstract

Background: Accurate estimation of stature in children is essential in clinical, emergency, and forensic settings where direct measurement may be impractical. This study aimed to evaluate the relationship between tibial length and pediatric height in Iraqi children and to establish regression equations for reliable stature estimation. Method: A cross-sectional study was conducted at the Medical City Complex in Baghdad from January to June 2025, including 300 children aged 1–15 years without musculoskeletal deformities or growth disorders. Standardized measurements of tibial length and height were obtained. Results: showed that 62.3% of participants were older than 5 years, with nearly equal gender distribution (50.7% females, 49.3% males). Children older than 5 years demonstrated significantly greater mean tibial length (29.48 ± 4.39 cm) and height (126.16 ± 13.54 cm) compared with younger children (21.04 ± 2.79 cm and 95.87 ± 8.27 cm, respectively; p = 0.0001). Regression equations derived from tibial length showed strong predictive accuracy for height estimation. Correlation was particularly strong among younger children (≤5 years; p = 0.0001) and females (p = 0.0001), while associations in males and older children were weaker. Conclusion: The study confirms tibial length as a robust predictor of pediatric stature in the Iraqi population, with stronger associations in early childhood. Establishing locally validated regression models enhances clinical decision-making in growth assessment, drug dosing, and emergency care, while also providing forensic value for stature reconstruction. Future multicenter research is recommended to refine predictive equations and broaden their applicability.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 49%
Genomics and Phylogenetic Studies
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