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Am J Clin Nutr. 2017 Jul;106(Suppl 1):402S-415S. doi: 10.3945/ajcn.116.142323. Epub 2017 Jun 14.

Predictors of anemia in preschool children: Biomarkers Reflecting Inflammation and Nutritional Determinants of Anemia (BRINDA) project.

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Department of Nutrition, University of California, Davis, CA.
Global Alliance for Improved Nutrition, Geneva, Switzerland.
Division of Biostatistics and Bioinformatics, Department of Oncology, Johns Hopkins University, Baltimore, MD.
GroundWork, Fläsch, Switzerland.
Strengthening Partnerships, Results, and Innovations in Nutrition Globally, Arlington, VA.
Department of Pediatrics, Emory University, Atlanta, GA.
Department of Global Health, Rollins School of Public Health, Atlanta, GA.
School of Medicine and Health Sciences, University of Papua New Guinea, Port Moresby, Papua New Guinea.
Department of Nutrition for Health and Development, WHO, Geneva, Switzerland.
Canadian Foodgrains Bank, Winnipeg, Manitoba, Canada; and.
Department of Pediatrics, Emory University, Atlanta, GA;
Nutrition Branch, CDC, Atlanta, GA.


Background: A lack of information on the etiology of anemia has hampered the design and monitoring of anemia-control efforts.Objective: We aimed to evaluate predictors of anemia in preschool children (PSC) (age range: 6-59 mo) by country and infection-burden category.Design: Cross-sectional data from 16 surveys (n = 29,293) from the Biomarkers Reflecting Inflammation and Nutritional Determinants of Anemia (BRINDA) project were analyzed separately and pooled by category of infection burden. We assessed relations between anemia (hemoglobin concentration <110 g/L) and severe anemia (hemoglobin concentration <70 g/L) and individual-level (age, anthropometric measures, micronutrient deficiencies, malaria, and inflammation) and household-level predictors; we also examined the proportion of anemia with concomitant iron deficiency (defined as an inflammation-adjusted ferritin concentration <12 μg/L). Countries were grouped into 4 categories on the basis of risk and burden of infectious disease, and a pooled multivariable logistic regression analysis was conducted for each group.Results: Iron deficiency, malaria, breastfeeding, stunting, underweight, inflammation, low socioeconomic status, and poor sanitation were each associated with anemia in >50% of surveys. Associations between breastfeeding and anemia were attenuated by controlling for child age, which was negatively associated with anemia. The most consistent predictors of severe anemia were malaria, poor sanitation, and underweight. In multivariable pooled models, child age, iron deficiency, and stunting independently predicted anemia and severe anemia. Inflammation was generally associated with anemia in the high- and very high-infection groups but not in the low- and medium-infection groups. In PSC with anemia, 50%, 30%, 55%, and 58% of children had concomitant iron deficiency in low-, medium-, high-, and very high-infection categories, respectively.Conclusions: Although causal inference is limited by cross-sectional survey data, results suggest anemia-control programs should address both iron deficiency and infections. The relative importance of factors that are associated with anemia varies by setting, and thus, country-specific data are needed to guide programs.


anemia; children; inflammation; iron; survey

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