BRINDA Equations for Inflammation Adjustment
The BRINDA (Biomarkers Reflecting Inflammation and Nutritional Determinants of Anemia) equations use regression correction to adjust micronutrient biomarker concentrations—including zinc, ferritin, retinol-binding protein, and soluble transferrin receptor—for the confounding effects of inflammation using C-reactive protein (CRP) and/or α-1-acid glycoprotein (AGP) as inflammatory markers 1, 2.
What BRINDA Does
The BRINDA approach addresses a critical problem: inflammation artificially lowers certain micronutrient biomarkers (like zinc and vitamin A) and raises others (like ferritin), leading to overestimation of zinc and vitamin A deficiencies and underestimation of iron deficiency 1. This is particularly problematic in preschool children and, to a lesser extent, in women of reproductive age 1.
The Regression Correction Method
The BRINDA regression correction approach works by:
- Using linear regression models that predict the relationship between micronutrient biomarker concentrations and inflammatory markers (CRP and/or AGP)
- Adjusting individual biomarker values based on their measured inflammation levels to estimate what the value would be in the absence of inflammation
- Applying population-specific correction equations rather than using fixed cutoffs 2, 3
For zinc specifically, the method adjusts plasma or serum zinc concentrations when there is a consistent negative association between zinc and CRP or AGP 4. In preschool children where this association exists, applying regression correction reduced estimated zinc deficiency prevalence by a median of 11 percentage points (range: 4-18 percentage points) compared to unadjusted values 4.
When to Apply BRINDA Adjustments
Critical decision point: You must first conduct correlation and decile analyses before applying any inflammation adjustments 4. The evidence shows:
- For preschool children (6-59 months): Apply BRINDA regression correction for zinc when surveys demonstrate a significant negative association between plasma zinc and CRP or AGP 4
- For women of reproductive age: The association between zinc and inflammatory markers is weak and inconsistent—there is currently insufficient evidence to warrant routine inflammation adjustment 4
- For school-age children and adolescents (5-19 years): Associations are weak with no clear patterns—routine adjustment for zinc is not supported 5
Practical Implementation
BRINDA has developed publicly available tools to standardize this process 1, 2:
- An R package (available at https://cran.r-project.org/web/packages/BRINDA/index.html) 6
- A SAS macro for users preferring SAS 2
- These tools provide "all-in-one" inflammation adjustment equations for multiple micronutrients including zinc, using AGP or CRP as inflammation indicators 6, 2
Important Caveats
Always report both unadjusted and adjusted results to allow comparison with surveys that did not measure inflammation markers, as recommended by WHO 1. This maintains transparency and comparability across different survey methodologies.
The BRINDA approach has been adopted by most recent national nutrition surveys as the standard method for inflammation adjustment, replacing older approaches like categorical exclusion (removing individuals with CRP >5 mg/L or AGP >1 g/L) or arithmetic correction factors 1. However, recent longitudinal data suggest the regression correction may overcorrect ferritin in some settings 7, highlighting that the method continues to evolve with new evidence.
For zinc measurement specifically: Ensure samples are collected with precautions to avoid contamination, as zinc is particularly susceptible to preanalytical errors 1. The lack of external quality assurance programs for zinc (unlike iron and vitamin A) means interlaboratory differences can contribute to result variability 1.