BRINDA

BRINDA adjusts micronutrient biomarker measurements for the effects of inflammation using regression-based corrections to improve interpretation of iron, vitamin A, and zinc status.

Key Features:

• Regression Correction: Uses regression-based correction to mitigate the confounding influence of inflammation on biomarkers such as iron, vitamin A, and zinc.
• Comprehensive Adjustment: Provides an all-in-one approach for adjusting multiple micronutrient biomarkers for inflammation within a consistent framework.
• Statistical Implementations: Offers computational implementations as an R package and a SAS macro for applying the adjustment methods.
• Malaria as Covariate: Evaluates inclusion of malaria status as a binary covariate in the inflammation-adjustment models.

Scientific Applications:

• Public Health Surveillance: Produces inflammation-adjusted micronutrient estimates to improve population-level assessments of iron, vitamin A, and zinc status.
• Nutrition and Program Evaluation: Informs interventions and monitoring for malnutrition and anemia by providing adjusted biomarker data.
• Epidemiology of Infection-Related Inflammation: Supports studies examining how inflammation and infections such as malaria affect micronutrient biomarker interpretation.

Methodology:

Applies regression-based correction models to adjust micronutrient biomarker values for inflammation, optionally includes malaria status as a binary covariate, and provides implementations in R and SAS.