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The Human Interference Scoring System (HISS): A New Tool for Quantifying Food Quality Based on Its Level of Processing

Nutrients 2024 4 citations ? Citation count from OpenAlex, updated daily. May differ slightly from the publisher's own count. Score: 55 ? 0–100 AI score estimating relevance to the microplastics field. Papers below 30 are filtered from public browse.
Olivia Malamatenios, Olivia Malamatenios, Jessica L. Campbell, Grant Schofield, Caryn Zinn

Summary

Researchers developed a new food classification tool called the Human Interference Scoring System that categorizes foods by their level of processing using photographs. They found high reliability among trained raters, especially for distinguishing unprocessed from ultra-processed foods. Ultra-processed items consistently had more calories, carbohydrates, and sugar, while unprocessed foods had notably higher fiber content.

The Human Interference Scoring System (HISS) is a novel food-based diet-quality-classification system based on the existing NOVA method. HISS involves food and fluid allocation into categories from digital imagery based on food processing levels, followed by meal plan analysis using food-servings quantification. The primary purpose of this work was to evaluate the reliability of HISS. Trained nutrition professionals analyzed digital photographs from five hypothetical 24 h food recalls and categorized foods into one of four HISS categories. A secondary purpose was to assess the nutrient composition of the food recalls and other selected foods from the HISS categories. Participants effectively categorized foods into HISS categories, with only minor discrepancies noted. High inter-rater reliability was observed in the outer HISS categories: unprocessed and ultra-processed foods. Ultra-processed items consistently displayed elevated energy, carbohydrates, and sugar compared to unprocessed foods, while unprocessed foods exhibited notably higher dietary fiber. This study introduces the HISS as a potentially useful tool for quantifying a food-quality-based system using digital-photography-based assessments. Its high inter-rater reliability and ability to capture relationships between food processing levels and nutrient composition make it a promising method for assessing dietary habits and food quality.

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