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Micronutrient and related health indicators

This section describes indicators for selected micronutrients (iron, iodine, folate and vitamins A, B12, and D) and related health issues (anaemia, iron deficiency and iron deficiency anaemia).

Throughout the section, recommended cutoff values for defining deficiency or insufficiency are listed. It is important to note that cutoffs may not be available for all population groups of interest. In addition, inflammation is an area of current research that affects micronutrient measures and new methods to adjust for inflammation are being explored.

Cutoff values for populations groups

Given the higher nutrient demands required for growth and reproduction, young children and women of reproductive age are the most vulnerable population groups and are thus the most common targets of nutrition surveys.

For pregnant women, unique cutoff values are only available for haemoglobin (anaemia), ferritin during the first trimester (iron deficiency) and urinary iodine. No cutoff values specific to this group are available for other micronutrients, and research is not sufficient to determine whether such values are needed. If stable representative estimates for pregnant women are needed in a survey, then this group will need to be oversampled and the results categorized separately.

Box 3.1 BOND papers available as of June 2021

Vitamin B12
Allen LH, Miller JW, de Groot L, Rosenberg IH, Smith AD, Refsum H et al. Biomarkers of Nutrition for Development (BOND): vitamin B-12 review. J Nutr. 2018;148(suppl_4):1995S-2027S. doi: 10.1093/jn/nxy201 (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6297555/) 1.

Iron
Lynch S, Pfeiffer CM, Georgieff MK, Brittenham G, Fairweather-Tait S, Hurrell RF et al. Biomarkers of Nutrition for Development (BOND) – iron review. J Nutr. 2018;148(suppl_1):1001S-1067S. doi: 10.1093/jn/nxx036 (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6297556/) 2.

Vitamin A
Tanumihardjo SA, Russell RM, Stephensen CB, Gannon BM, Craft NE, Haskell MJ et al. Biomarkers of Nutrition for Development (BOND) – vitamin A review. J Nutr. 2016;146:1816S-48S. doi: 10.3945/jn.115.229708 (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4997277/) 3.

Zinc
King JC, Brown KH, Gibson RS, Krebs NF, Lowe NM, Siekmann JH et al. Biomarkers of Nutrition for Development (BOND) - zinc review. J Nutr. 2016;146:858S-885S (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4807640/) 4.

Folate
Bailey LB, Stover PJ, McNulty H, Fenech MF, Gregory JF 3rd, Mills JL et al. Biomarkers of Nutrition for Development -folate review. J Nutr. 2015;145:1636S-1680S. doi: 10.3945/jn.114.206599 (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4478945/) 5.

Iodine
Rohner F, Zimmermann M, Jooste P, Pandav C, Caldwell K, Raghavan R, Raiten DJ. Biomarkers of Nutrition for Development – iodine review. J Nutr. 2014;144:1322S-1342S. doi: 10.3945/jn.113.181974 (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4093988/) 6.

These papers are also included in the reference list at the end of this module.

Inflammation

The acute phase response, triggered by infection and trauma, is a collection of non-specific changes including the production of proteins that promote inflammation and activate, complement, and stimulate phagocytic cells. All of these are inflammatory markers. This cascade of immune response activity is intended to remove harmful molecules and pathogens and to prevent further damage to tissues 7.

Inflammation affects the circulating concentrations of multiple micronutrients. During the acute phase response there is a change in many indicators of micronutrient status, such as retinol and ferritin, leading to an over- or under-estimation of deficiency. The acute phase proteins, C-reactive protein (CRP) and alpha-1-acid glycoprotein (AGP), are commonly used indicators of inflammation 7. The concentration of some acute phase proteins (APPs) in plasma, called positive APPs, will increase in the presence of inflammation. Examples of such APPs include CRP, AGP, and ferritin. Other APPs decrease in the presence of inflammation. These negative APPs include retinol, retinol binding protein (RBP), and albumin.

The BRINDA project (Biomarkers Reflecting Inflammation and Nutritional Determinants of Anemia) has been investigating approaches to adjust population estimates of iron, vitamin A, and zinc in the presence of inflammation. The progress for iron and vitamin A has been published, and work on zinc is ongoing. In general, BRINDA described methods that incorporate an internal (country- or survey-specific) regression-correction approach 8. This is a rapidly evolving area and it is important to review the literature for updated information. The BRINDA website also contains useful resources 9.

In many lower income countries, the prevalence of infection and resultant inflammation is high, and many individuals will have elevated APPs even without clinical signs or symptoms of disease. Additionally, chronic conditions without infection, such as diabetes, hypertension and obesity, result in low grade inflammation.

Measuring inflammation by CRP:

CRP concentration increases rapidly during inflammatory processes, and returns to pre-infection levels over 18-20 hours when the stimuli end, which is more quickly than AGP 7.

Specimen collection and management: CRP is typically measured in serum samples obtained by centrifuging whole blood that was collected by venipuncture or capillary sampling. CRP is stable, so whole blood processing can be delayed for 1-2 days. Serum is stable for up to two weeks at 4˚C and up to one year at -20˚C.

Biomarker analysis: CRP and high-sensitivity CRP (hs-CRP) 10, 11 are measured by immunoassays (nephelometry or turbidimetry), either on a fully automated clinical analyser or by using a manual ELISA assay. Commercial assay kits are available for both analytical techniques. The required analysis volume is normally <25 µL; however, a minimum specimen volume of >150 µL may be needed to fill the sample cup for the clinical analyser. The assay product sheet will explain matrix requirements. Not all assays can utilize EDTA (ethylenediaminetetraacetic acid) or heparin plasma. Serum is the preferred matrix.

Quality control: Appropriate quality control measures must be followed to ensure high quality results. The assay kits include calibration materials and may include quality control materials. It is nonetheless recommended to establish “in-house” quality control materials that can be tracked over a longer period to verify that the method did not shift over time. The method imprecision is typically ~10%. A human serum international reference material (ERM-DA474/IFCC) is available through the Institute for Reference Materials and Measurements (IRMM) at the European Commission Joint Research Centre. However, not every assay may be able to use this material because the assay performance may differ between patient samples and reference materials that have undergone some processing. Moderate differences between assays can be observed in proficiency testing programmes, such as the Immunology Survey of the US College of American Pathologists (CAP) and the National Institute of Standards and Technology (NIST).

Approximate budget requirements for analysis: Approximate budget requirements for analysis: Instrumentation needed for CRP includes either a clinical analyser (approximately US$ 100 000) or a plate-washer, plate-reader, and various pipettes (approximately US$ 30 000). The cost for materials and supplies is roughly US$ 3 to US$ 5 per sample for a commercial kit assay. Material costs may be slightly lower for locally developed ELISA assays that measure CRP in addition to other micronutrients.

Interpretation of results: The suggested CRP cutoff value to define inflammation is >5 mg/L 712.

Measuring inflammation by AGP:

The concentration of AGP normally increases within 24 to 48 hours following an infection and stays elevated for a longer duration than CRP. Typically, it is elevated for 5 days, from day 2 to day 7 after a single clinical infection 13,14,15. Hence, AGP captures a unique phase of the acute phase response, compared to CRP 7.

Specimen collection and management: Like CRP, AGP is stable, and specimens can be handled using similar conditions.

Biomarker analysis: The analytical techniques to measure AGP are the same as for CRP; however, there are fewer clinical analysers available that measure AGP. A human serum international reference material (ERM-DA470K/IFCC) is available from the European IRMM. AGP is usually not covered in proficiency testing programmes and it is therefore difficult to compare among assays.

Approximate budget requirements for analysis: The same resources and instrumentation described for CRP are needed for the measurement of AGP.

Interpretation of results: The suggested AGP cutoff value to define inflammation is >1 g/L 7-12.

Note regarding stability of biomarkers in serum samples
The following sub-section refers to stability of the biomarker at 4oC and -20oC (16, 17). The section discusses the collection of specimens and management of serum samples for analysis of: retinol, retinol binding protein, ferritin, transferrin receptor, vitamin B12, 25-hydroxy vitamin D and CRP.

  1. Allen LH, Miller JW, de Groot L, Rosenberg IH, Smith AD, Refsum H et al. Biomarkers of Nutrition for Development (BOND): Vitamin B-12 review. J Nutr. 2018;148(suppl_4):1995S–2027S. doi: 10.1093/jn/nxy201. 

  2. Lynch S, Pfeiffer CM, Georgieff MK, Brittenham G, Fairweather-Tait S, Hurrell RF et al. Biomarkers of Nutrition for Development (BOND) – iron review. J Nutr. 2018;148(suppl_1):1001S–1067S. doi: 10.1093/jn/nxx036. 

  3. Tanumihardjo SA, Russell RM, Stephensen CB, Gannon BM, Craft NE, Haskell MJ et al. Biomarkers of Nutrition for Development (BOND) – vitamin A review. J Nutr. 2016;146:1816S–48S. doi: 10.3945/jn.115.229708. 

  4. King JC, Brown KH, Gibson RS, Krebs NF, Lowe NM, Siekmann JH et al. Biomarkers of Nutrition for Development (BOND) – zinc review. J Nutr. 2016;146:858S–885S. 

  5. Bailey LB, Stover PJ, McNulty H, Fenech MF, Gregory JF 3rd, Mills JL et al. Biomarkers of Nutrition for Development – folate review. J Nutr. 2015;145:1636S–1680S. doi: 10.3945/jn.114.206599. 

  6. Rohner F, Zimmermann M, Jooste P, Pandav C, Caldwell K, Raghavan R, Raiten DJ. Biomarkers of Nutrition for Development – iodine review. J Nutr. 2014;144:1322S–1342S. doi: 10.3945/jn.113.181974. 

  7. Raiten DJ, Sakr Ashour FA, Ross AC, Meydani SN, Dawson HD, Stephensen CB et al. Inflammation and Nutritional Science for Programs/Policies and Interpretation of Research Evidence (INSPIRE). J Nutr. 2015;145:1039S–1108S. doi: 10.3945/jn.114.194571.  2 3 4 5 6

  8. Suchdev PS, Namaste SM, Aaron GJ, Raiten DJ, Brown KH, Flores-Ayala R et al. Overview of the Biomarkers Reflecting Inflammation and Nutritional Determinants of Anemia (BRINDA) Project. Adv Nutr. 2016;7:349–56. doi: 10.3945/an.115.010215. 

  9. Biomarkers Reflecting Inflammation and Nutritional Determinants of Anemia (BRINDA) [website]. 2017 (https://brinda-nutrition.org, accessed 14 June 2020). 

  10. Dominici R, Luraschi P, Franzini C. Measurement of C-reactive protein: two high sensitivity methods compared. J Clin Lab Anal. 2004;18:280–4. 

  11. Grützmeier S, von Schenck H. Four immunochemical methods for measuring C-reactive protein in plasma compared. Clin Chem. 1989;35:461–3. 

  12. Priorities in the assessment of vitamin A and iron status in populations. Panama City, Panama, 15–17 September 2010. Geneva: World Health Organization; 2012 (https://apps.who.int/iris/bitstream/handle/10665/75334/9789241504225_eng.pdf; accessed 11 May 2020).  2

  13. Ceciliani F, Lecchi C. The immune functions of α1 acid glycoprotein. Curr Protein Pept Sci. 2019;20:505–24. doi:10.2174/1389203720666190405101138. 

  14. Bteich M. An overview of albumin and alpha-1-acid glycoprotein main characteristics: highlighting the roles of amino acids in binding kinetics and molecular interactions. Heliyon. 2019;5:e02879. doi:10.1016/j.heliyon.2019.e02879. 

  15. Hochepied T, Berger FG, Baumann H, Libert C. Alpha(1)-acid glycoprotein: an acute phase protein with inflammatory and immunomodulating properties. Cytokine Growth Factor Rev. 2003;14:25–34.