Overview of the biomarkers reflecting inflammation and nutritional determinants of anemia (BRINDA) project
Open accessAbstract
Anemia remains a widespread public health problem. Although iron deficiency is considered the leading cause of anemia globally, the cause of anemia varies considerably by country. To achieve global targets to reduce anemia, reliable estimates of the contribution of nutritional and non-nutritional causes of anemia are needed to guide interventions. Inflammation is known to affect many biomarkers used to assess micronutrient status and can thus lead to incorrect diagnosis of individuals and to overestimation or underestimation of the prevalence of deficiency in a population. Reliable assessment of iron status is particularly needed in settings with high infectious disease burden, given the call to screen for iron deficiency to mitigate potential adverse effects of iron supplementation. To address these information gaps, in 2012 the CDC, National Institute for Child Health and Human Development, and Global Alliance for Improved Nutrition formed a collaborative research group called Biomarkers Reflecting Inflammation and Nutrition Determinants of Anemia (BRINDA). Data from nationally and regionally representative nutrition surveys conducted in the past 10 y that included preschool children and/or women of childbearing age were pooled. Of 25 data sets considered for inclusion, 17 were included, representing ∼30,000 preschool children, 26,000 women of reproductive age, and 21,000 school-aged children from all 6 WHO geographic regions. This article provides an overview of the BRINDA project and describes key research questions and programmatic and research implications. Findings from this project will inform global guidelines on the assessment of anemia and micronutrient status and will guide the development of a research agenda for future longitudinal studies.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Serum albumin has a 3-week half-life.
“Serum albumin has a 3-wk half-life, and in a nutrient-deficient state such as starvation the serum albumin will decrease only slightly as the body compensates to maintain visceral protein status.”
From The Value of Integrating the Nutritional Ecology into the Nutrition Care Continuum—A Conceptual and Systems Approach (2025) · cites this paper as [13]
In a nutrient-deficient state such as starvation, serum albumin decreases only slightly as the body compensates to maintain visceral protein status.
“Serum albumin has a 3-wk half-life, and in a nutrient-deficient state such as starvation the serum albumin will decrease only slightly as the body compensates to maintain visceral protein status.”
From The Value of Integrating the Nutritional Ecology into the Nutrition Care Continuum—A Conceptual and Systems Approach (2025) · cites this paper as [13]
In catabolic states due to trauma, infection, or burns, serum albumin concentration decreases rapidly even when nutritional status may be preserved.
“However, if an individual enters a state of catabolism because of trauma, infection, or burns, the serum albumin concentration decreases rapidly, even when their nutritional status may be preserved.”
From The Value of Integrating the Nutritional Ecology into the Nutrition Care Continuum—A Conceptual and Systems Approach (2025) · cites this paper as [13]
Interpreting nutrition-related biomarkers in a context-specific manner is more important for individuals with conditions that can compromise nutrition-sensitive systems, such as compromised immune systems or disease-related inflammation and the acute phase response.
“Clearly, the nuances of interpreting nutrition-related biomarkers in a context-specific manner assumes greater importance for individuals with conditions that can potentially compromise nutrition-sensitive systems, e.g. those with compromised immune systems or disease-related inflammation and the concomitant acute phase response [[13], [14], [15], [16], [17]].”
From The Value of Integrating the Nutritional Ecology into the Nutrition Care Continuum—A Conceptual and Systems Approach (2025) · cites this paper as [13]
Cites
Strimbu, K., & Tavel, J. A. (2010) · Current Opinion in HIV and AIDS · doi:10.1097/coh.0b013e32833ed177 · Cited by 2,062 · see citing works
The epidemiology of global micronutrient deficiencies
Bailey, R. L., West Jr., K. P., & Black, R. E. (2015) · Annals of Nutrition and Metabolism · doi:10.1159/000371618 · Cited by 2,035 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Serum ferritin thresholds for the diagnosis of iron deficiency in pregnancy: A systematic review
Daru, J., Allotey, J., Peña‐Rosas, J. P., & Khan, K. S. (2017) · Transfusion Medicine · doi:10.1111/tme.12408 · Cited by 138 · see citing works
Raiten, D. J., Combs, G. F., Steiber, A. L., & Bremer, A. A. (2021) · Advances in Nutrition · doi:10.1093/advances/nmab046 · Cited by 33 · see citing works
“In addition to this reciprocity, we have come to appreciate the impact and need to account for the inflammatory response on the performance and interpretation of nutritional biomarkers (22).”
BackgroundSelf-citationNga, H. T., Quyen, P. N., Chaffee, B. W., Diep Anh, N. T., Ngu, T., & King, J. C. (2020) · PLOS ONE · doi:10.1371/journal.pone.0232197 · Cited by 32 · see citing works
Urbanski, G., Chabrun, F., Lavigne, C., Lacout, C., Delattre, E., Reynier, P., & Requin, J. (2024) · QJM: An International Journal of Medicine · doi:10.1093/qjmed/hcad218 · Cited by 12 · see citing works
Raiten, D. J., Steiber, A. L., & Bremer, A. A. (2025) · Advances in Nutrition · doi:10.1016/j.advnut.2025.100385 · Cited by 10 · see citing works
Self-citationResponse of Iron Deficiency Markers to Blood Lead Levels and Synergistic Outcomes at Prenatal Stage
Arshad, S., Arif, A., & Wattoo, J. I. (2022) · Dose-Response · doi:10.1177/15593258221101744 · Cited by 9 · see citing works
- Authors
- Suchdev, P. S., Namaste, S. M., Aaron, G. J., Raiten, D. J., Brown, K. H., & Flores-Ayala, R.
- Affiliations
- Centers for Disease Control and Prevention (US)
- Helen Keller International (US)
- Global Alliance for Improved Nutrition (CH)
- National Institutes of Health (US)
- Gates Foundation (US)
- Corresponding author
- Suchdev, Parminder S
- Venue
- Advances in Nutrition
- Publisher
- Elsevier BV
- Published
- 2016-03
- Volume
- 7
- Issue
- 2
- Pages
- 349-356
- ISSN
- 2156-5376 (ISSN-L)
- 2161-8313
- PMC
- PMC4785469
- OpenAlex
- W2298371667
- Cited by
- 207
- References
- 2
- Citations by year
- 2026: 12 · 2025: 19 · 2024: 23 · 2023: 20 · 2022: 22 · 2021: 12 · 2020: 22 · 2019: 20 · 2018: 14 · 2017: 35 · 2016: 7 · 2015: 1
- FWCI
- 3.60
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Advances in Nutrition (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Funders
- Office of Dietary Supplements
- Bill and Melinda Gates Foundation
- National Institutes of Health
- Centers for Disease Control and Prevention
- National Institute of Child Health and Human Development
- Topics
- Health Sciences › Medicine › Hematology › Iron Metabolism and Disorders
- Health Sciences › Nursing › Nutrition and Dietetics › Child Nutrition and Water Access
- Health Sciences › Nursing › Nutrition and Dietetics › Trace Elements in Health
- Keywords
- anemia, inflammation, iron deficiency, iron status assessment, micronutrient status, preschool children, women of reproductive age, school-aged children, iron supplementation, infectious disease burden
- MeSH terms
- Adolescent, Adult, Anemia, Child, Child Nutritional Physiological Phenomena, Child, Preschool, Congresses as Topic, Diagnosis, Differential, Female, Humans, Infant, Male, Middle Aged, Nutritional Status, Global Health, Biomarkers, Anemia, Iron-Deficiency, Evidence-Based Medicine, Maternal Nutritional Physiological Phenomena, Young Adult
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
