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An interactive web-based tool for computing BMI standard deviation scores in Italian children and adolescents using
Livio Tarchi1,2,3, Elena Mattesini4, Cristiano Dani5,4
1Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Viale Pieraccini, 6, Florence, FI, Italy. livio.tarchi@unifi.it.
Background:
Body mass index (BMI) standard deviation scores (SDS) are essential for age- and sex-adjusted assessments in pediatric populations, including growth trajectories. Their accuracy depends on the use of population-specific reference data, as BMI distributions vary substantially across countries. Despite the availability of internationally recognized growth standards, no accessible computational tool tailored to Italian normative data has been previously described.
Objectives:
This paper describes the development and validation of an interactive, freely accessible web-based calculator for deriving BMI-SDS in Italian children and adolescents, based on the nationally representative Cacciari et al. (2006) growth reference dataset.
Methods:
BMI-SDS computation is based on the LMS parameterization of Italian reference curves, which provide sex-specific L (skewness), M (median), and S (coefficient of variation) values at half-year age intervals from 2 to 20 years for a nationally representative Italian sample of approximately 70,000 children and adolescents.
Results:
The tool was implemented in R using the Shiny web application framework and is hosted at https://turius.shinyapps.io/BMI_SDS_IT/. Given user-entered weight, height, age, and sex, the tool computes BMI (kg/m2), derives the corresponding BMI-SDS and returns i) age- and sex-adjusted BMI-SDS; ii) the corresponding percentile; iii) a graphical representation of the individual's position on the reference distribution.
Conclusions:
The tool offers a straightforward, clinician- and researcher-friendly interface for computing age- and sex-standardized BMI scores using Italian-specific references, supporting more accurate weight-status classification in both clinical practice and epidemiological research.
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