A practical guide to adjust micronutrient biomarkers for inflammation using the BRINDA method
The Biomarkers Reflecting Inflammation and Nutritional Determinants of Anemia (BRINDA) research group was formed over a decade ago to improve the interpretation of micronutrient biomarkers in settings with inflammation. The BRINDA inflammation adjustment method uses regression correction to adjust f...
| Autores principales: | , , , , , , , |
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| Formato: | Journal Article |
| Lenguaje: | Inglés |
| Publicado: |
Elsevier
2023
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| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/175726 |
| _version_ | 1855541589245427712 |
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| author | Luo, Hanqi Geng, Jiaxi Zeiler, Madeleine Nieckula, Emily Sandalinas, Fanny Williams, Anne Young, Melissa F. Suchdev, Parminder S. |
| author_browse | Geng, Jiaxi Luo, Hanqi Nieckula, Emily Sandalinas, Fanny Suchdev, Parminder S. Williams, Anne Young, Melissa F. Zeiler, Madeleine |
| author_facet | Luo, Hanqi Geng, Jiaxi Zeiler, Madeleine Nieckula, Emily Sandalinas, Fanny Williams, Anne Young, Melissa F. Suchdev, Parminder S. |
| author_sort | Luo, Hanqi |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | The Biomarkers Reflecting Inflammation and Nutritional Determinants of Anemia (BRINDA) research group was formed over a decade ago to improve the interpretation of micronutrient biomarkers in settings with inflammation. The BRINDA inflammation adjustment method uses regression correction to adjust for the confounding effects of inflammation on select micronutrient biomarkers and has provided important insights to micronutrient research, policy, and programming. However, users may face challenges when applying the BRINDA inflammation adjustment methods to their own data due to varying guidance on the adjustment approach for different biomarkers and the need to develop statistical programming to conduct these analyses. This may result in lost opportunities to have results of micronutrient data readily available during critical decision-making periods. Our research objectives are to 1) provide an all-in-one summary of the BRINDA method in adjusting multiple micronutrient biomarkers for inflammation, 2) evaluate whether malaria as a binary variable should be included in the BRINDA inflammation adjustment method, and 3) present standardized and user-friendly BRINDA adjustment R package and SAS macro. This paper serves as a practical guidebook for the BRINDA inflammation adjustment approach and aids users to use the BRINDA R package and SAS to streamline their analyses. |
| format | Journal Article |
| id | CGSpace175726 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2023 |
| publishDateRange | 2023 |
| publishDateSort | 2023 |
| publisher | Elsevier |
| publisherStr | Elsevier |
| record_format | dspace |
| spelling | CGSpace1757262025-12-08T09:54:28Z A practical guide to adjust micronutrient biomarkers for inflammation using the BRINDA method Luo, Hanqi Geng, Jiaxi Zeiler, Madeleine Nieckula, Emily Sandalinas, Fanny Williams, Anne Young, Melissa F. Suchdev, Parminder S. trace elements biomarkers inflammation computer applications The Biomarkers Reflecting Inflammation and Nutritional Determinants of Anemia (BRINDA) research group was formed over a decade ago to improve the interpretation of micronutrient biomarkers in settings with inflammation. The BRINDA inflammation adjustment method uses regression correction to adjust for the confounding effects of inflammation on select micronutrient biomarkers and has provided important insights to micronutrient research, policy, and programming. However, users may face challenges when applying the BRINDA inflammation adjustment methods to their own data due to varying guidance on the adjustment approach for different biomarkers and the need to develop statistical programming to conduct these analyses. This may result in lost opportunities to have results of micronutrient data readily available during critical decision-making periods. Our research objectives are to 1) provide an all-in-one summary of the BRINDA method in adjusting multiple micronutrient biomarkers for inflammation, 2) evaluate whether malaria as a binary variable should be included in the BRINDA inflammation adjustment method, and 3) present standardized and user-friendly BRINDA adjustment R package and SAS macro. This paper serves as a practical guidebook for the BRINDA inflammation adjustment approach and aids users to use the BRINDA R package and SAS to streamline their analyses. 2023-04 2025-07-22T17:15:21Z 2025-07-22T17:15:21Z Journal Article https://hdl.handle.net/10568/175726 en Open Access Elsevier Luo, Hanqi; Geng, Jiaxi; Zeiler, Madeleine; Nieckula, Emily; Sandalinas, Fanny; et al. 2023. A practical guide to adjust micronutrient biomarkers for inflammation using the BRINDA method. Journal of Nutrition 153(4): 1265-1272. https://doi.org/10.1016/j.tjnut.2023.02.016 |
| spellingShingle | trace elements biomarkers inflammation computer applications Luo, Hanqi Geng, Jiaxi Zeiler, Madeleine Nieckula, Emily Sandalinas, Fanny Williams, Anne Young, Melissa F. Suchdev, Parminder S. A practical guide to adjust micronutrient biomarkers for inflammation using the BRINDA method |
| title | A practical guide to adjust micronutrient biomarkers for inflammation using the BRINDA method |
| title_full | A practical guide to adjust micronutrient biomarkers for inflammation using the BRINDA method |
| title_fullStr | A practical guide to adjust micronutrient biomarkers for inflammation using the BRINDA method |
| title_full_unstemmed | A practical guide to adjust micronutrient biomarkers for inflammation using the BRINDA method |
| title_short | A practical guide to adjust micronutrient biomarkers for inflammation using the BRINDA method |
| title_sort | practical guide to adjust micronutrient biomarkers for inflammation using the brinda method |
| topic | trace elements biomarkers inflammation computer applications |
| url | https://hdl.handle.net/10568/175726 |
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