Iron-Fortified Drinking Water Studies for the Prevention of Children's Anemia in Developing Countries

Sensory evaluations of a novel iron and zinc-enriched powder for the potential treatment and prevention of iron deficiency in women of reproductive age

Iron deficiency (ID) and ID with anaemia (IDA) are serious global health problems that disproportionately affect women aged 15-49 years. Although food fortification is one of the most effective and sustainable ways to combat nutritional deficiencies, iron remains one of the most difficult micronutrients to fortify, given its tendency to react strongly with food constituents. Therefore, it is important to assess the sensory properties of foods fortified with iron to determine the acceptability and palatability in target populations. We aimed to determine the palatability and acceptability of a novel iron and zinc-enriched powder fortified in tap water by conducting sensory evaluations in 35 women of reproductive age using a 9-point hedonic scale, where participants rated the sensory properties of six samples containing different amounts of the active or placebo powder. We found significant differences between samples reconstituted at 1, 2, and 3 g/L for sensory properties, including overall taste. Participants were found to be more willing to drink the mineral-enriched powder when prepared at the lowest concentration (1 g/L) compared to higher concentrations. Our results provide important insight into the sensory qualities of a novel formulation of an iron and zinc-enriched powder for at-home fortification and indicate consumer acceptability in reproductive-aged women, a key group at risk for ID/IDA. If found to improve iron status, novel treatments like this product will contribute to global efforts to develop safe, acceptable and sustainable interventions for ID and IDA.

Iron-fortified water: a new approach for reducing iron deficiency anemia in resource-constrained settings

A new approach for fortification of drinking water is presented for combating iron deficiency anemia (IDA) worldwide. The idea is to leach Fe from a bed containing granular metallic iron (Fe0), primarily using ascorbic acid (AA). AA forms very stable and bioavailable complexes with ferrous iron (FeII). Calculated amounts of the FeII-AA solution can be added daily to the drinking water of households or day-care centers for children and adults (e.g. hospitals, kindergartens/schools, refugee camps) to cover the Fe needs of the populations. Granular Fe0 (e.g., sponge iron) in filters is regarded as a locally available Fe carrier in low-income settings, and, AA is also considered to be affordable in low-income countries. The primary idea of this concept is to stabilize FeII from the Fe0 filter by using an appropriate AA solution. An experiment showed that up to 12 mg Fe can be daily leached from 1.0 g of a commercial sponge iron using a 2 mM AA solution. Fe fortification of safe drinking water is a practicable, affordable and efficient method for reducing IDA in low-income communities.

Prevalence and Triggering Factors of Childhood Anemia: An Application of Ordinal Logistic Regression Model

INTRODUCTION

Anemia is indeed a significant risk factor for children's health as it affects growth retardation and has severe short and prolonged effects that follow in morbidity and death. Notwithstanding such ways to tackle anemia, the prevalence remains high in India and poses a severe public health concern.

OBJECTIVES

The primary focus of this study was to find the prevalence and to determine the factors associated with the anemia of children under five years of age in India. Problem Statement. The increasing prevalence of childhood anemia and the life-threatening consequences for millions of children in India are a major concern. Knowing the relevant associated factors with childhood anemia is essential to reduce the frequency and severity level. Study design. For analysis purposes, this study utilized a cross-sectional study design. Methodology. Using the Indian Demographic and Health Survey 2015-16 data, we used chi-squared and gamma tests to find the association. Then, we utilized multinomial logistic regression and ordinal logistic regression to find the better model and the influencing factors of anemia in India.

RESULTS

In our study, we have found that children with highly educated mothers were 36.7% less likely (OR = 0.633, P ≤ 0.001, 95% CI: 0.608, 0.658) to be higher anemic than the children with not educated mother. Children with moderate and severe anemic mothers were 163.3% (OR = 2.633, P ≤ 0.001, 95% CI: 2.565, 7.704) more likely to be higher anemic than the children with not anemic mother. Not stunting children were 21.9% (OR = 0.781, P ≤ 0.001, 95% CI: 0 .764, 0.797) less likely to be higher anemic than the stunting children. Children aged 36-59 months were 73.9% (OR = 0.361, P ≤ 0.001, 95% CI: 0.353, 0.369) less likely to be higher anemic than the children aged 6-24 months. Again, the ACI value revealed that ordinal logistic regression was a better-fitted model for these data.

CONCLUSION

and contribution. The variables such as stunting, underweight, wasting, child age, size of the child, and source of drinking water were the most critical indicators for child anemia in India. In summary, our study result indicated the major socioeconomic and demographic factors associated with childhood anemia in India, which can help the policymaker to take quick decision to reduce the severity level.

Prevalence of childhood anaemia in Brazil: still a serious health problem: a systematic review and meta-analysis

OBJECTIVE

To estimate the prevalence of anaemia in Brazilian children up to 83·9 months old.

DESIGN

Systematic review and meta-analysis, using databases PubMed, Scopus, SciELO, Lilacs, Google Scholar, Periódicos Capes, Arca, Biblioteca Virtual em Saúde, Microsoft Academic Search and Cochrane Library using search terms: anaemia, prevalence, child and Brazil. PROSPERO Registration number: CRD42020208818.

SETTING

Cross-sectional, cohort, case-control and intervention studies published between 2007 and 2020 were searched, excluding those who assessed children with an illness or chronic condition. The main outcome was anaemia prevalence. Random effects models based on the inverse variance method were used to estimate pooled prevalence measures. Sensitivity analyses removed studies with high contribution to overall heterogeneity.

PARTICIPANTS

From 6790 first screened, 134 eligible studies were included, totalling 46 978 children aged zero to 83·9 months analysed, with adequate regions representativeness.

RESULTS

Pooled prevalence of anaemia was 33 % (95 % CI 30, 35). Sensitivity analyses showed that withdrawal of studies that contributed to high heterogeneity did not influence national average prevalence.

CONCLUSIONS

Childhood anaemia is still a serious public health problem in Brazil, exposing 33 % of Brazilian children to the anaemia repercussions. The main limitation of the study is the estimation of national prevalence based on local surveys, but a large number of studies were included, with representation in all regions of the country, giving strength to the results. In Brazil, more public policies are needed to promote supplementation, fortification and access to healthy eating to reduce the high level of anaemia among children.

Assessing the relative importance of social determinants of health in malaria and anemia classification based on machine learning techniques

Disparate types of data including biological and environmental have been used in supervised learning to predict a specific disease outcome. However, social determinants of health, which have been explored very little, promise to be significant predictors of public health problems such as malaria and anemia among children. We considered studying their contribution power in malaria and anemia predictions based on Variable Importance in Projection (VIP). This innovative method has potential advantages as it analyzes the impact of independent variables on disease prediction. In addition, we applied five machine learning algorithms to classify both diseases, using social determinants of health data, and compared their results. Of them all, artificial neural networks gave the best results of 94.74% and 84.17% accuracy for malaria and anemia prediction, respectively. These results are consistent and reflect the significance of non-medical factors in disease prediction.

Cognitive deficits and ALA-D-inhibition in children exposed to multiple metals

Children are especially vulnerable to adverse effects of multiple metals exposure. The aim of this study was to assess some metals concentrations such as lead (Pb), arsenic (As), chromium (Cr), manganese (Mn) and iron (Fe) in whole blood, serum, hair and drinking water samples using inductively coupled plasma-mass spectrometry (ICP-MS) in rural and urban children. In addition, evaluate the adverse effects of multiple metals exposure on cognitive function and δ-aminolevulinate dehydratase (ALA-D) activity. The cognitive ability assessment was performed by the Raven's Colored Progressive Matrices (RCPM) test. The ALA-D activity and ALA-D reactivation index (ALA-RE) activity with DTT and ZnCl2 also were determined. Forty-six rural children and 23 urban children were enrolled in this study. Rural children showed percentile IQ scores in the RCPM test significantly decreased in relation to urban children. According to multiple linear regression analysis, the Mn and Fe in hair may account for the cognitive deficits of children. Manganese and Fe in hair also were positively correlated with Mn and Fe in drinking water, respectively. These results suggest that drinking water is possibly a source of metals exposure in children. ALA-D activity was decreased and ALA-RE with DTT and ZnCl2 was increased in rural children in comparison to urban children. Moreover, ALA-D inhibition was correlated with Cr blood levels and ALA-RE/DDT and ALA-RE/ZnCl2 were correlated with levels of Cr and Hg in blood. Thus, our results indicated some adverse effects of children's exposure to multiple metals, such as cognitive deficits and ALA-D inhibition, mainly associated to Mn, Fe, Cr and Hg.