TY - JOUR
T1 - Nutrient dataset development via FAO/INFOODS approach for infant nutritional survey in rural Matiari, Pakistan
AU - Soomro, Sanam Iram
AU - Jamil, Zehra
AU - Memon, Najma
AU - Ahmed, Sheraz
AU - Umrani, Fayaz
AU - Choudhri, Imran Ahmed
AU - Mohammed, Sajid
AU - Qureshi, Khalique
AU - Raza, Ghulam
AU - Jakhro, Sadaf
AU - Ali, Asad
N1 - Publisher Copyright:
© 2024 The Authors
PY - 2024/9
Y1 - 2024/9
N2 - To accurately evaluate dietary intake, multiple resources are necessary, including serving-size modules, pictures, and questionnaires that are used to gather information during surveys. One critical component is the accessibility of food composition data at the national or regional level, which is required to determine dietary intake. Food Agriculture Organization/International Network of Food Data Systems (FAO/INFOODs) tools are useful for developing high-quality food composition data. We used these tools to create a nutrient dataset for a nutritional survey in Matiari, Sindh, and to collect dietary information through a 24-hour food recall questionnaire. The survey results indicated 540 distinct types of foods, including 291 ready-to-eat items, 84 foods used as ingredients in recipes, and 164 various composite and mixed recipes. Most food items corresponded to the national and regional Food Composition Tables (FCTs) and the Food and Nutrient Database for Dietary Studies (FNDDS) of the USDA, with the exception of recipe food data. We utilized Eurofir-recipe calculation methods to compute the recipe data. The data were homogenized and standardized utilizing EFSA and Langual™. Because of the obsolescence and inadequacy of Pakistan's food composition table in assessing essential nutrients, we had to source data from various other sources. Consequently, to establish the nutrient dataset, we incorporated approximately 25 % of user data from national sources, with recipe data comprising 46 % and less than 20 % extracted from regional, U.S database, and diverse online sources. This study is the first effort in which we gathered data from reliable sources representing local eating patterns, with some exceptions. Future studies will hugely benefit from this database, especially as we face a high prevalence of undernutrition in our part of the world.
AB - To accurately evaluate dietary intake, multiple resources are necessary, including serving-size modules, pictures, and questionnaires that are used to gather information during surveys. One critical component is the accessibility of food composition data at the national or regional level, which is required to determine dietary intake. Food Agriculture Organization/International Network of Food Data Systems (FAO/INFOODs) tools are useful for developing high-quality food composition data. We used these tools to create a nutrient dataset for a nutritional survey in Matiari, Sindh, and to collect dietary information through a 24-hour food recall questionnaire. The survey results indicated 540 distinct types of foods, including 291 ready-to-eat items, 84 foods used as ingredients in recipes, and 164 various composite and mixed recipes. Most food items corresponded to the national and regional Food Composition Tables (FCTs) and the Food and Nutrient Database for Dietary Studies (FNDDS) of the USDA, with the exception of recipe food data. We utilized Eurofir-recipe calculation methods to compute the recipe data. The data were homogenized and standardized utilizing EFSA and Langual™. Because of the obsolescence and inadequacy of Pakistan's food composition table in assessing essential nutrients, we had to source data from various other sources. Consequently, to establish the nutrient dataset, we incorporated approximately 25 % of user data from national sources, with recipe data comprising 46 % and less than 20 % extracted from regional, U.S database, and diverse online sources. This study is the first effort in which we gathered data from reliable sources representing local eating patterns, with some exceptions. Future studies will hugely benefit from this database, especially as we face a high prevalence of undernutrition in our part of the world.
KW - Food composition data
KW - Infants
KW - Malnutrition
KW - Stunting
UR - https://www.scopus.com/pages/publications/85197537584
U2 - 10.1016/j.jfca.2024.106471
DO - 10.1016/j.jfca.2024.106471
M3 - Article
AN - SCOPUS:85197537584
SN - 0889-1575
VL - 133
JO - Journal of Food Composition and Analysis
JF - Journal of Food Composition and Analysis
M1 - 106471
ER -