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Development of the anti-cancer food scoring system 2.0: Validation and nutritional analyses of quantitative anti-cancer food scoring model

BACKGROUND/OBJECTIVES: We have previously designed the anti-cancer food scoring model (ACFS) 1.0, an evidence-based quantitative tool analyzing the anti-cancer or carcinogenic potential of diets. Analysis was performed using simple quantitative indexes divided into 6 categories (S, A, B, C, D, and E...

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Detalles Bibliográficos
Autores principales: Hong, Yeo-Jin, Kim, Jeongseon, Lee, Hye Yoon, Rim, Chai Hong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Korean Nutrition Society and the Korean Society of Community Nutrition 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6997147/
https://www.ncbi.nlm.nih.gov/pubmed/32042372
http://dx.doi.org/10.4162/nrp.2020.14.1.32
Descripción
Sumario:BACKGROUND/OBJECTIVES: We have previously designed the anti-cancer food scoring model (ACFS) 1.0, an evidence-based quantitative tool analyzing the anti-cancer or carcinogenic potential of diets. Analysis was performed using simple quantitative indexes divided into 6 categories (S, A, B, C, D, and E). In this study, we applied this scoring model to wider recipes and evaluated its nutritional relevance. MATERIALS/METHODS: National or known regional databases were searched for recipes from 6 categories: Korean out-dining, Korean home-dining, Western, Chinese, Mediterranean, and vegetarian. These recipes were scored using the ACFS formula and the nutrition profiles were analyzed. RESULTS: Eighty-eight international recipes were analyzed. All S-graded recipes were from vegetarian or Mediterranean categories. The median code values of each category were B (Korean home-dining), C (Korean out-dining), B (Chinese), A (Mediterranean), S (vegetarian), and D (Western). The following profiles were correlated (P < 0.05) with ACFS grades in the univariate trend analysis: total calories, total fat, animal fat, animal protein, total protein, vitamin D, riboflavin, niacin, vitamin B(12), pantothenic acid, sodium, animal iron, zinc, selenium, and cholesterol (negative trends), and carbohydrate rate, fiber, water-soluble fiber, vitamin K, vitamin C, and plant calcium (positive trends). Multivariate analysis revealed that animal fat, animal iron, and niacin (negative trends) and animal protein, fiber, and vitamin C (positive trends) were statistically significant. Pantothenic acid and sodium showed non-significant negative trends (P < 0.1), and vitamin B(12) showed a non-significant positive trend. CONCLUSION: This study provided a nutritional basis and extended the utility of ACFS, which is a bridgehead for future cancer-preventive clinical trials using ACFS.