Anthropometric characterization and statistical modeling for optimizing the construction parameters of girls’ trousers
Source abstract
Abstract
Abstract The aim of this study is the development of a regression-based model for improving the construction of girls’ trouser patterns, with a focus on enhancing garment comfort and functionality. Anthropometric data were collected from a sample of 4,002 girls aged 6–12 years in the Republic of Croatia. Statistical analysis was conducted using Statistica and SPSS to establish relationships between key body dimensions and garment construction parameters. The regression model for trouser length demonstrated high predictive applicability, with coefficients of determination (R 2 ) increasing from 0.39 in younger age groups to approximately 0.60 in older groups, confirming body height as a reliable predictor. In contrast, seat depth showed substantially higher variability (CV = 17.3–22.0 %) and weak regression performance (R 2 ≈ 0.05–0.15), primarily due to the complexity and lower reliability of direct anthropometric measurement. Multiple regression prediction of inside leg length based on body height and knee height achieved moderate to high explanatory power (R 2 ≈ 0.50–0.70), with predictive accuracy improving with age. The study extends existing sizing methodologies by integrating statistical modelling into garment pattern development, thereby contributing to improved fit optimisation and more reliable use of anthropometric data in contemporary children’s clothing design.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: 3D Shape Modeling and Analysis · Textile materials and evaluations · Ergonomics and Musculoskeletal Disorders
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
University of Zagreb, Faculty of Textile Technology, Department of Clothing Technology , Zagreb , Croatia
References (31)
Show source-provided references
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