BackgroundStandardized practices are needed in the analysis of inflammation biomarker values outside limits of detection (LODs) when used for inflammation correction of nutritional biomarkers. ObjectiveWe assessed the direction and extent to which serum C-reactive protein (CRP) and α-1-acid-glycoprotein (AGP) values outside LODs (<0.05 mg/L and >4.0 g/L, respectively) affect inflammation regression correction of serum ferritin and compared approaches to addressing such values when estimating inflammation-adjusted ferritin and iron deficiency (ID). MethodsWe examined 29 cross-sectional datasets from 7 countries with reproductive-age women (age 15–49 y) (n = 12,944), preschool-age children (age 6–59 mo) (n = 18,208), and school-age children (age 6–14 y) (n = 4625). For each dataset, we compared 6 analytic approaches for addressing CRP <LOD: listwise deletion, single imputation (lower, middle, or upper bound; LOD/√2; random number), with multiple imputation (MI). For each approach, inflammation-adjusted ferritin and ID using BRINDA (Biomarkers Reflecting Inflammation and Nutritional Determinants of Anemia) regression correction were estimated. We calculated deviance of each estimate from that given by MI within each dataset and performed fixed-effects multivariate meta-regression with an analytic approach as a moderator to compare the reliability of each approach to MI. ResultsAcross datasets, observations outside LOD ranged from 0.0 to 35.0% of CRP values and 0.0 to 2.5% of AGP values. Pooled deviance estimates for mean ferritin (μg/L) and ID (percentage points) were: listwise deletion −0.46 (95% CI: −0.76, −0.16) and 0.14 (−0.43, 0.72), lower bound 0.45 (0.14, 0.76) and −0.36 (−0.91, 0.20), middle bound −0.21 (−0.51, 0.09) and 0.22 (−0.34, 0.79), LOD/√2 −0.26 (−0.57, 0.04) and 0.25 (−0.31, 0.81), upper bound −0.31 (−0.61, −0.01) and 0.30 (−0.27, 0.86), and random number −0.08 (−0.38, 0.22) and 0.11 (−0.46, 0.67). There was moderation by approach in the ferritin model (P < 0.001). ConclusionsThese findings demonstrate the need for standardized analyses of inflammation biomarker values outside LODs and suggest that random number single imputation may be a reliable and feasible alternative to MI for CRP <LOD.