1,721,036 research outputs found
Ann N Y Acad Sci
Full text linkAnemia affects a third of the world's population and contributes to increased morbidity and mortality, decreased work productivity, and impaired neurological development. Understanding anemia's varied and complex etiology is crucial for developing effective interventions that address the context-specific causes of anemia and for monitoring anemia control programs. We outline definitions and classifications of anemia, describe the biological mechanisms through which anemia develops, and review the variety of conditions that contribute to anemia development. We emphasize the risk factors most prevalent in low- and middle-income countries, including nutritional deficiencies, infection/inflammation, and genetic hemoglobin disorders. Recent work has furthered our understanding of anemia's complex etiology, including the proportion of anemia caused by iron deficiency (ID) and the role of inflammation and infection. Accumulating evidence indicates that the proportion of anemia due to ID differs by population group, geographical setting, infectious disease burden, and the prevalence of other anemia causes. Further research is needed to explore the role of additional nutritional deficiencies, the contribution of infectious and chronic disease, as well as the importance of genetic hemoglobin disorders in certain populations.CC999999/ImCDC/Intramural CDC HHSUnited States/WHO_/World Health OrganizationInternational/Evidence and Programme Guidance UnitInternational/Department of Nutrition for Health and Development of the World Health Organization (WHO)International
Novel strategies to improve iron intake in African infants: effects on anemia and vaccine efficacy
No full text
PLoS One
Full text linkThe usefulness of anthropometry to define childhood malnutrition is undermined by poor measurement quality, which led to calls for new measurement approaches. We evaluated the ability of a 3D imaging system to correctly measure child stature (length or height), head circumference and arm circumference. In 2016-7 we recruited and measured children at 20 facilities in and around metro Atlanta, Georgia, USA; including at daycare, higher education, religious, and medical facilities. We selected recruitment sites to reflect a generally representative population of Atlanta and to oversample newborns and children under two years of age. Using convenience sampling, a total of 474 children 0-5 years of age who were apparently healthy and who were present at the time of data collection were included in the analysis. Two anthropometrists each took repeated manual measures and repeated 3D scans of each child. We evaluated the reliability and accuracy of 3D scan-derived measurements against manual measurements. The mean child age was 26 months, and 48% of children were female. Based on reported race and ethnicity, the sample was 42% Black, 28% White, 8% Asian, 21% multiple races, other or race not reported; and 16% Hispanic. Measurement reliability of repeated 3D scans was within 1 mm of manual measurement reliability for stature, head circumference and arm circumference. We found systematic bias when analyzing accuracy-on average 3D imaging overestimated stature and head circumference by 6 mm and 3 mm respectively, and underestimated arm circumference by 2 mm. The 3D imaging system used in this study is reliable, low-cost, portable, and can handle movement; making it ideal for use in routine nutritional assessment. However, additional research, particularly on accuracy, and further development of the scanning and processing software is needed before making policy and clinical practice recommendations on the routine use of 3D imaging for child anthropometry
Ann N Y Acad Sci
Full text linkThe correct interpretation of hemoglobin (Hb) to identify anemia requires adjusting for altitude and smoking. Current adjustments were derived using data collected before 1985, from low-income preschool-aged children (PSC) in the United States and indigenous men in Peru for altitude, and from White women of reproductive age (WRA) in the United States for smoking. Given the oldness and limited representativeness of these data, we reexamined associations between Hb and altitude and/or smoking using 13 population-based surveys and 1 cohort study each conducted after 2000. All WHO regions except South-East Asia were represented. The dataset included 68,193 observations among PSC (6-59 months) and nonpregnant WRA (15-49 years) with data on Hb and altitude (-28 to 4000\ua0m), and 19,826 observations among WRA with data on Hb and smoking (status or daily cigarette quantity). Generalized linear models were used to assess the robustness of associations under varying conditions, including controlling for inflammation-corrected iron and vitamin A deficiency. Our study confirms that Hb should be adjusted for altitude and/or smoking; these adjustments are additive. However, recommendations for Hb adjustment likely need updating. Notably, current recommendations may underadjust Hb for light smokers and for those residing at lower altitudes and overadjust Hb for those residing at higher altitudes.20192020-02-01T00:00:00ZCC999999/ImCDC/Intramural CDC HHS/United States31231812PMC6697572672
J Nutr
Full text linkWe aim to provide a practical approach to assess anemia and its primary causes, both in clinical settings and in the context of public health programs. Anemia remains a global challenge; thus, to achieve goals for anemia reduction and assess progress, standardized approaches are required for the assessment of anemia and its causes. We first provide a brief review of how to assess anemia, based on hemoglobin concentrations and cutoffs that correspond to age, sex, and physiologic status. Next, we discuss how to assess the likely causes of anemia in different settings. The causes of anemia are classified as non-nutritional (for example, because of infection, inflammation, blood loss, or genetic disorders) or nutrition-specific (for example, because of deficiencies of iron, vitamin A, riboflavin, vitamin B|, or folate). There is an important overlap between these 2 categories, such as the increased likelihood of iron deficiency in the context of inflammation. Given the multifaceted nature of anemia etiology, we introduce a framework for anemia assessment based on the "ecology of anemia," which recognizes its many overlapping causes. This conceptual framework is meant to inform what data on anemia causes may need to be collected in population surveys. The framework has a supporting table with information on the diagnostic tests, biomarkers and proposed cutoffs, characteristics, and feasibility of collecting the myriad information that can help elucidate the anemia etiology. We also provide examples of how this framework can be applied to interpret the anemia risk factor data from population-based surveys that can inform decisions about context-specific interventions. Finally, we present research gaps and priorities related to anemia assessment.CC999999/ImCDC/Intramural CDC HHSUnited States
PLoS One
Full text linkAnthropometric data collected in clinics and surveys are often inaccurate and unreliable due to measurement error. The Body Imaging for Nutritional Assessment Study (BINA) evaluated the ability of 3D imaging to correctly measure stature, head circumference (HC) and arm circumference (MUAC) for children under five years of age. This paper describes the protocol for and the quality of manual anthropometric measurements in BINA, a study conducted in 2016-17 in Atlanta, USA. Quality was evaluated by examining digit preference, biological plausibility of z-scores, z-score standard deviations, and reliability. We calculated z-scores and analyzed plausibility based on the 2006 WHO Child Growth Standards (CGS). For reliability, we calculated intra- and inter-observer Technical Error of Measurement (TEM) and Intraclass Correlation Coefficient (ICC). We found low digit preference; 99.6% of z-scores were biologically plausible, with z-score standard deviations ranging from 0.92 to 1.07. Total TEM was 0.40 for stature, 0.28 for HC, and 0.25 for MUAC in centimeters. ICC ranged from 0.99 to 1.00. The quality of manual measurements in BINA was high and similar to that of the anthropometric data used to develop the WHO CGS. We attributed high quality to vigorous training, motivated and competent field staff, reduction of non-measurement error through the use of technology, and reduction of measurement error through adequate monitoring and supervision. Our anthropometry measurement protocol, which builds on and improves upon the protocol used for the WHO CGS, can be used to improve anthropometric data quality. The discussion illustrates the need to standardize anthropometric data quality assessment, and we conclude that BINA can provide a valuable evaluation of 3D imaging for child anthropometry because there is comparison to gold-standard, manual measurements.201729240796PMC57302091020
Am J Trop Med Hyg
Full text linkTo determine the association between a range of inherited blood disorders and indicators of poor nutrition, we analyzed data from a population-based, cross-sectional survey of 882 children 6-35 months of age in western Kenya. Of children with valid measurements, 71.7% were anemic (hemoglobin < 11 g/dL), 19.1% had ferritin levels < 12 \u3bcg/L, and 30.9% had retinol binding protein (RBP) levels < 0.7 \u3bcmol/L. Unadjusted analyses showed that compared with normal children, homozygous \u3b1(+)-thalassemia individuals had a higher prevalence of anemia (82.3% versus 66.8%, P = 0.001), but a lower prevalence of low RBP (20.5% versus 31.4%, P = 0.024). In multivariable analysis, homozygous \u3b1(+)-thalassemia remained associated with anemia (adjusted odds ratio [aOR] = 1.8, P = 0.004) but not with low RBP (aOR = 0.6, P = 0.065). Among young Kenyan children, \u3b1(+)-thalassemia is associated with anemia, whereas G6PD deficiency, haptoglobin 2-2, and HbS are not; none of these blood disorders are associated with iron deficiency, vitamin A deficiency, or poor growth.091758/Wellcome Trust/United Kingdom092654/Wellcome Trust/United Kingdom100693/Wellcome Trust/United Kingdom091758/PEPFAR/United State
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