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Household‐level consumption data can be redistributed for individual‐level Optifood diet modeling: analysis from four countries
A barrier to using Optifood linear programming (LP), which identifies nutrient gaps and supports population‐specific food‐based recommendation (FBR) development, is the requirement for dietary intake data. We investigated whether Household Consumption and Expenditure Surveys (HCESs) could be used in...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9299870/ https://www.ncbi.nlm.nih.gov/pubmed/34850396 http://dx.doi.org/10.1111/nyas.14709 |
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author | Knight, Frances Woldt, Monica Sethuraman, Kavita Bergeron, Gilles Ferguson, Elaine |
author_facet | Knight, Frances Woldt, Monica Sethuraman, Kavita Bergeron, Gilles Ferguson, Elaine |
author_sort | Knight, Frances |
collection | PubMed |
description | A barrier to using Optifood linear programming (LP), which identifies nutrient gaps and supports population‐specific food‐based recommendation (FBR) development, is the requirement for dietary intake data. We investigated whether Household Consumption and Expenditure Surveys (HCESs) could be used instead of individual‐level 24‐h recalls (24HRs). The 24HR data from 12‐ to 23‐month‐old breastfeeding children in rural Kenya, Uganda, Guatemala, and Bangladesh were paired with HCES food consumption data from similar areas (n = 8) and time periods. HCES food intakes (g/week) were estimated using adult male equivalents, adjusted for breastfeeding. Paired HCES‐ and 24HR‐defined LP inputs and outputs were compared using percentage agreement. Mean overall percentage agreements were 42%, 63%, and 80%, for food, food subgroup, and food‐group model parameters, respectively. HCES food lists were on average 1.3 times longer than 24HR. Similar nutrient gaps (77–100% agreement), food sources of nutrients (71–100% agreement), and FBRs (80–100% agreement) were identified. The results suggest that HCES data can be used in Optifood analyses for 12‐ to 23‐month‐old children, despite recognized challenges of using it to estimate dietary intakes of young children compared with older age groups. Further analyses, however, are required for different age groups and locations to confirm expectations that it would perform equally well. |
format | Online Article Text |
id | pubmed-9299870 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-92998702022-07-21 Household‐level consumption data can be redistributed for individual‐level Optifood diet modeling: analysis from four countries Knight, Frances Woldt, Monica Sethuraman, Kavita Bergeron, Gilles Ferguson, Elaine Ann N Y Acad Sci Original Articles A barrier to using Optifood linear programming (LP), which identifies nutrient gaps and supports population‐specific food‐based recommendation (FBR) development, is the requirement for dietary intake data. We investigated whether Household Consumption and Expenditure Surveys (HCESs) could be used instead of individual‐level 24‐h recalls (24HRs). The 24HR data from 12‐ to 23‐month‐old breastfeeding children in rural Kenya, Uganda, Guatemala, and Bangladesh were paired with HCES food consumption data from similar areas (n = 8) and time periods. HCES food intakes (g/week) were estimated using adult male equivalents, adjusted for breastfeeding. Paired HCES‐ and 24HR‐defined LP inputs and outputs were compared using percentage agreement. Mean overall percentage agreements were 42%, 63%, and 80%, for food, food subgroup, and food‐group model parameters, respectively. HCES food lists were on average 1.3 times longer than 24HR. Similar nutrient gaps (77–100% agreement), food sources of nutrients (71–100% agreement), and FBRs (80–100% agreement) were identified. The results suggest that HCES data can be used in Optifood analyses for 12‐ to 23‐month‐old children, despite recognized challenges of using it to estimate dietary intakes of young children compared with older age groups. Further analyses, however, are required for different age groups and locations to confirm expectations that it would perform equally well. John Wiley and Sons Inc. 2021-11-30 2022-03 /pmc/articles/PMC9299870/ /pubmed/34850396 http://dx.doi.org/10.1111/nyas.14709 Text en © 2021 The Authors. Annals of the New York Academy of Sciences published by Wiley Periodicals LLC on behalf of New York Academy of Sciences https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Articles Knight, Frances Woldt, Monica Sethuraman, Kavita Bergeron, Gilles Ferguson, Elaine Household‐level consumption data can be redistributed for individual‐level Optifood diet modeling: analysis from four countries |
title | Household‐level consumption data can be redistributed for individual‐level Optifood diet modeling: analysis from four countries |
title_full | Household‐level consumption data can be redistributed for individual‐level Optifood diet modeling: analysis from four countries |
title_fullStr | Household‐level consumption data can be redistributed for individual‐level Optifood diet modeling: analysis from four countries |
title_full_unstemmed | Household‐level consumption data can be redistributed for individual‐level Optifood diet modeling: analysis from four countries |
title_short | Household‐level consumption data can be redistributed for individual‐level Optifood diet modeling: analysis from four countries |
title_sort | household‐level consumption data can be redistributed for individual‐level optifood diet modeling: analysis from four countries |
topic | Original Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9299870/ https://www.ncbi.nlm.nih.gov/pubmed/34850396 http://dx.doi.org/10.1111/nyas.14709 |
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