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JNFS 2024, 9(1): 1-6 |
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Sharifi A. ShaFA, a New Microsoft Windows-Based Software for Food Intake Analysis. JNFS 2024; 9 (1) :1-6
URL: http://jnfs.ssu.ac.ir/article-1-628-en.html
URL: http://jnfs.ssu.ac.ir/article-1-628-en.html
Department of Nutrition and Food Hygiene, Nutrition Health Research Center, Hamadan University of Medical Sciences, Hamadan, Iran.
Abstract: (2481 Views)
In food intake studies, converting eaten foods into calories and nutrients and other food components using books and tables of food ingredients is a very time-consuming and error-prone task. ShaFA is new Microsoft Windows-based software for food component derivation of individual and group food intake data. This software is developed using C sharp programming language. Microsoft Access has been used to put the information of 8790 food types and their 85 food components based on the USDA-SR28 in the database of software. The user is capable to search in the database for desired food by the name or special code of the food and select them for each person. Each person’s food intake data can be stored via allocating an exclusive ID. Finally, the user can get a report of the imported data in a new window, and also can get a Microsoft Excel export which can be imported into statistical software such as SPSS and STATA. Each research project data can be stored in a file with the unique extension (ShaFA) which can be opened and edited in any system that its operating system is Microsoft Windows, and has ShaFA software installed on it. This software can provide researchers with valuable information in a short time, especially nutritional epidemiology studies. It can also be used in food industry to extract the information needed to label and complete food information table for a variety of food industry products.
Type of article: orginal article |
Subject:
public specific
Received: 2022/05/8 | Published: 2024/02/21 | ePublished: 2024/02/21
Received: 2022/05/8 | Published: 2024/02/21 | ePublished: 2024/02/21
References
1. Haytowitz DB, Lemar LE & Pehrsson PR 2009. USDA's Nutrient Databank System – A tool for handling data from diverse sources. Journal of food composition and analysis. 22 (5): 433-441.
2. Hedrick VE, et al. 2012. Dietary biomarkers: advances, limitations and future directions. Nutrition journal. 11 (1): 1-14.
3. Ibsen DB, et al. 2021. Food substitution models for nutritional epidemiology. American journal of clinical nutrition. 113 (2): 294-303.
4. Illner A, et al. 2012. Review and evaluation of innovative technologies for measuring diet in nutritional epidemiology. International journal of epidemiology. 41 (4): 1187-1203.
5. Kaaks R, Ferrari P, Ciampi A, Plummer M & Riboli E 2002. Uses and limitations of statistical accounting for random error correlations, in the validation of dietary questionnaire assessments. Public health nutrition. 5 (6a): 969-976.
6. Kim Y-J, et al. 2012. Plasma phospholipid fatty acid composition in ischemic stroke: importance of docosahexaenoic acid in the risk for intracranial atherosclerotic stenosis. Atherosclerosis. 225 (2): 418-424.
7. Kuhnle GG 2012. Nutritional biomarkers for objective dietary assessment. Journal of the science of food agriculture. 92 (6): 1145-1149.
8. Neuhouser ML 2019. The importance of healthy dietary patterns in chronic disease prevention. Nutrition research. 70: 3-6.
9. Raw P 2015. Composition of Foods Raw, Processed, Prepared USDA National Nutrient Database for Standard Reference, Release 28 (2015) Documentation and User Guide. United States Ritchie P 2016. Practical Microsoft Visual Studio 2015. Springer.
10. Ritchie P 2016. Practical Microsoft Visual Studio 2015. Springer
11. Shim J-S, Oh K & Kim HC 2014. Dietary assessment methods in epidemiologic studies. Epidemiol Health. 36: e2014009-e2014009.
12. US Department of Agriculture, Agricultural Research Service & Laboratory ND 2016. USDA National Nutrient Database for Standard Reference, Release 28 (Slightly revised). Version Current: May 2016.
13. Willett W 2012. Nutritional epidemiology. Oxford university press.
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