1. Predictors of anemia in women of reproductive age: Biomarkers Reflecting Inflammation and Nutritional Determinants of Anemia (BRINDA) project
- Author
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Wirth, James P, Woodruff, Bradley A, Engle-Stone, Reina, Namaste, Sorrel Ml, Temple, Victor J, Petry, Nicolai, Macdonald, Barbara, Suchdev, Parminder S, Rohner, Fabian, and Aaron, Grant J
- Subjects
Medical Microbiology ,Biomedical and Clinical Sciences ,Nutrition and Dietetics ,Clinical Sciences ,Infectious Diseases ,Vector-Borne Diseases ,Prevention ,Hematology ,Nutrition ,Rare Diseases ,2.2 Factors relating to the physical environment ,Aetiology ,Infection ,Good Health and Well Being ,Clean Water and Sanitation ,Adolescent ,Adult ,Age Factors ,Anemia ,Anemia ,Iron-Deficiency ,Biomarkers ,Body Mass Index ,Cross-Sectional Studies ,Female ,Hemoglobins ,Humans ,Infections ,Inflammation ,Iron Deficiencies ,Malaria ,Middle Aged ,Nutritional Status ,Risk Factors ,Socioeconomic Factors ,Vitamin A Deficiency ,anemia ,determinants ,inflammation ,iron ,malaria ,micronutrient deficiencies ,risk factors ,women ,women of reproductive age ,Engineering ,Medical and Health Sciences ,Nutrition & Dietetics ,Clinical sciences ,Nutrition and dietetics - Abstract
Background: Anemia in women of reproductive age (WRA) (age range: 15-49 y) remains a public health problem globally, and reducing anemia in women by 50% by 2025 is a goal of the World Health Assembly.Objective: We assessed the associations between anemia and multiple proximal risk factors (e.g., iron and vitamin A deficiencies, inflammation, malaria, and body mass index) and distal risk factors (e.g., education status, household sanitation and hygiene, and urban or rural residence) in nonpregnant WRA.Design: Cross-sectional, nationally representative data from 10 surveys (n = 27,018) from the Biomarkers Reflecting Inflammation and Nutritional Determinants of Anemia (BRINDA) project were analyzed individually and pooled by the infection burden and risk in the country. We examined the severity of anemia and measured the bivariate associations between anemia and factors at the country level and by infection burden, which we classified with the use of the national prevalences of malaria, HIV, schistosomiasis, sanitation, and water-quality indicators. Pooled multivariate logistic regression models were constructed for each infection-burden category to identify independent determinants of anemia (hemoglobin concertation
- Published
- 2017