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Updated: Sep 19, 2025

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Published on: April 19, 2024
A Developmental Texture Framework for Food Texture Progression: Implications for Feeding Development, Oral Motor
Amy L Delaney1, Sarah Staskiewicz2, Suzanne Evans Morris3
1Department of Speech Pathology and Audiology, Marquette University, Milwaukee, Wisconsin, USA.
Abstract:
The introduction of food textures in a child's first 2 years of life plays a vital role in growth, nutrition, and feeding development. However, the absence of a standardized texture framework for studying texture progression limits both pediatric feeding research and the ability to diagnose pediatric feeding disorder (PFD) based on age-appropriate expectations. To address this gap, authors Delaney and Goday proposed data sharing from the Nestlé Feeding Infant-Toddler Study (FITS) to explore texture progression and define age-appropriate texture expectations. In response, Nestlé assembled a multidisciplinary panel of feeding experts to create standardized textures but did not provide financial or nonfinancial assistance for this study. This panel integrated literature on global guidelines, texture classification systems, the International Dysphagia Diet Standardization Initiative, food properties, and developmental research. Through an iterative process, they developed a framework with standardized definitions based on food properties. The framework categorizes food textures into five main groups: liquids, purees, mashed solids, chewable solids, and combination foods. These categories are based on food properties (flow rate/cohesiveness, moisture content, firmness, particle size, and particle distribution) and oral motor skills (biting, chewing, tongue force, and tongue control). Each category is further divided into three subcategories. The texture category is determined by how the food is prepared and presented, rather than its original form. This property-based framework offers flexibility in classifying foods based on preparation and presentation, making it ideal for coding existing data and supporting at-home data collection. By establishing a standardized language for food textures, the framework will help fill gaps in normative data, assist in PFD diagnostics, and support future research and clinical applications.
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