Streamlining Micronutrient Biomarker Statistical Analysis in Populations: An Introduction to the SAMBA R Package

• DOI: 10.1016/j.tjnut.2023.06.024
• Publication Date: 2023-06-23T04:44:03Z
• Authors: Hanqi Luo; Ty Beal; Tineka Blake; Madeleine Zeiler; Jiaxi Geng; E Rochelle Werner; O Yaw Addo; Parminder S. Suchdev; Melissa F. Young
• Keywords: Micronutrient deficiency

Micronutrient deficiency is a common global health problem, and accurately assessing micronutrient biomarkers crucial for planning managing effective intervention programs. However, analyzing data applying appropriate cutoffs to define deficiencies can be challenging, particularly when considering the confounding effects of inflammation on certain biomarkers. To address this challenge, we developed Statistical Apparatus Biomarker Analysis (SAMBA) R package, new tool that increases ease accessibility population-based biomarker analysis. The SAMBA package analyze various assess status iron, vitamin A, zinc, B vitamins; adjust inflammation; account complex survey design appropriate; produce reports summary statistics prevalence estimates using recommended age-specific sex-specific cutoffs. In study, aimed provide step-by-step procedure how use including customize it broader use, made both user manual publicly available GitHub. was validated by comparing results 24 sets nonpregnant women reproductive age from 23 countries 30 preschool-aged children 26 with those obtained an independent analyst. generated identical means, percentiles, calculated conclusion, simplifies standardizes process deriving survey-weighted inflammation-adjusted (when appropriate) deficiencies, reducing time cleaning result generation. valuable facilitates accurate rapid analysis data, which inform public research, programs, policy across contexts.