Abstract
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.