Frequent Consumption of Micronutrient-Rich Foods Is Associated With Reduced Risk of Anemia Among Adolescent Girls and Boys in Indonesia: A Cross-Sectional Study

Dietary quality, anaemia prevalence and their associated factors among rural school- going adolescents in Acholi sub -region of Uganda

BACKGROUND

Globally, iron deficiency anaemia is a widespread public health problem affecting vulnerable populations including adolescents. However, over the years, the Uganda Demographic Health Surveys mostly report the status of anaemia for women of reproductive age (15-49 years) and children up to 5 years, leaving out the focus on adolescents. Moreover, high prevalence of anaemia among children below five years could suggest that anaemia still persists at adolescence. Therefore, the study aimed at determining dietary quality, prevalence of anaemia and their associated factors among school-going adolescents.

METHODS

A cross-sectional study involving 341 adolescent boys and girls aged 10-19 years was carried out in two rural schools in Gulu district. Prevalence of anaemia was determined by obtaining blood specimens from a finger prick into a microcuvette and analysed for haemoglobin (Hb) level using Haemoglobin analyser, whereas dietary quality was assessed using the Individual Dietary Diversity Score (IDDS). Socio-economic and demographic data were collected using a semi-structured questionnaire.

RESULTS

The overall prevalence of anaemia was 16.0% (Girls:18.1%; Boys:13.0%), while the mean Hb level was 13.2 ± 1.4 g/dl (Girls 13.0 ± 1.3 g/dl; Boys 13.5 ± 1.6 g/dl). The mean number of food groups consumed among the adolescents was 3.5 ± 2.1 for girls and 3.0 ± 1.8 for boys (p˃0.05). Animal source foods, fruits and vitamin A-rich vegetables, other fruits and vegetables were consumed by adolescent girls more than the boys. Similarly, a higher proportion of adolescent girls than boys consumed iron-rich foods: fish and meat, organ meat and dark green leafy vegetables. Further, all the socio-demographic factors in the study did not predict dietary diversity (p ˃ 0.05). On the other hand, education attainment by parent/guardian and nature of menstruation predicted the prevalence of anaemia amongst adolescents (p < 0.05).

CONCLUSIONS

The prevalence of anaemia was high among adolescents. Coupled with this, there, was low dietary diversity among the adolescents. The level of education of the parent/guardian and nature of the menstrual discharge were significant predictors of anaemia amongst girls. From this study, we recommend interventions by both health and agricultural-related practitioners to strengthen activities in rural schools such as health and nutrition education to create awareness about dietary diversity and promotion of agricultural practices such as school vegetable gardens, orchards poultry production and rearing of small ruminants to support consumption of diverse foods in schools with the view of reducing the burden from iron deficiency anaemia.

Influence of intermittent iron and folic acid supplementation on cognitive abilities among adolescent girls in northwestern Tanzania

Iron and folic acid (IFA) supplementation to reduce anemia is key for improving substantial lost disability adjusted life years (DALYs) for adolescent girls. This study assessed the impact of weekly IFA supplementation (WIFAS) on cognitive ability among adolescent girls in the Simiyu Region in northernwestern Tanzania. This cross-sectional comparative evaluation study of 770 adolescent girls (396 -WIFAS supplemented; 374 -not supplemented) evaluated the association between WIFAS and cognitive ability through a face-to-face survey and cognitive ability assessment using standardized tests (Span-forward Test, Span-backward Test and Maze Test). Using a modified Poisson regression, we controlled for the geographic setting (urban vs rural), availability of potable water and feeding programs in schools, age and school level of adolescent girls, parental status, main parental economic activities, and the number of teachers. Participants were between the ages of 11 and 19 years, with more than half (57%) between 12-15 years of age. Those with WIFAS had higher cognitive ability (Span-forward scores, χ2 = 46.34% p <0.001; Span-forward, χ2 = 46.34% p <0.001; and Global Composite Cognitive Performance (GCCP), χ2 = 32.52% p<0.001). Among the IFA supplemented adolescent girls, secondary school level had a significantly higher score with respect to Span-backward (aPR = 1.43, 95% CI = 1.06-1.62); Span-forward ability (aPR = 1.26, 95% CI = 1.04-1.53) and Maze Test ability (aPR = 1.12, 95% CI = 1.01-1.25) as compared to their counterpart in primary school level. Individual adolescent girls with WIFAS and living with both parents performed much better on the Span-backward Test (aPR = 1.22, 95% CI = 1.07-1.68) as compared to those living with relatives and/or orphans. The presence of potable water program among the WIFAS schools resulted in a higher Span-backward ability (aPR = 1.34, 95% CI = 1.03-1.89); and GCCP (aPR = 1.27, 95% CI = 1.03-1.75). Adolescent girls from WIFAS schools with feeding program had higher Span-forward (aPR = 1.38, 95% CI = 1.03-1.63) ability as well as a higher Maze Test (aPR = 1.15, 95% CI = 1.07-1.26) score. The present study provides compelling evidence that WIFAS is positively associated with higher cognitive ability among adolescent girls. Nevertheless, IFA interventions are still rare in communities across Tanzania.

A New Artificial Intelligence Approach Using Extreme Learning Machine as the Potentially Effective Model to Predict and Analyze the Diagnosis of Anemia

The procedure to diagnose anemia is time-consuming and resource-intensive due to the existence of a multitude of symptoms that can be felt physically or seen visually. Anemia also has several forms, which can be distinguished based on several characteristics. It is possible to diagnose anemia through a quick, affordable, and easily accessible laboratory test known as the complete blood count (CBC), but the method cannot directly identify different kinds of anemia. Therefore, further tests are required to establish a gold standard for the type of anemia in a patient. These tests are uncommon in settings that offer healthcare on a smaller scale because they require expensive equipment. Moreover, it is also difficult to discern between beta thalassemia trait (BTT), iron deficiency anemia (IDA), hemoglobin E (HbE), and combination anemias despite the presence of multiple red blood cell (RBC) formulas and indices with differing optimal cutoff values. This is due to the existence of several varieties of anemia in individuals, making it difficult to distinguish between BTT, IDA, HbE, and combinations. Therefore, a more precise and automated prediction model is proposed to distinguish these four types to accelerate the identification process for doctors. Historical data were retrieved from the Laboratory of the Department of Clinical Pathology and Laboratory Medicine, Faculty of Medicine, Public Health, and Nursing, Universitas Gadjah Mada, Yogyakarta, Indonesia for this purpose. Furthermore, the model was developed using the algorithm for the extreme learning machine (ELM). This was followed by the measurement of the performance using the confusion matrix and 190 data representing the four classes, and the results showed 99.21% accuracy, 98.44% sensitivity, 99.30% precision, and an F1 score of 98.84%.

The effect of maternal anaemia on low birth weight among newborns in Northwest Ethiopia

Low birth weight is an indicator of maternal-related multifactorial problems such as malnutrition, illness, and work overload. As a result, low birth weight is associated with maternal anaemia, and both of them were significant public health issues in developing nations. Low birth weight and anaemia are caused by insufficient nutrient intake, which is especially severe during pregnancy. So, this study aimed to assess the effect of maternal anaemia during the late trimester on low birth weight among newborns in Northwest Ethiopia. A systematic random sampling technique was used to select 211 participants for the primary data collection. Face-to-face interviews were used to collect data, while blood samples were collected using standard operating procedures. For further analysis, the data file was imported into Stata version 16 (MP) software. The binary logistic regression model was used to investigate significant factors related to low birth weight. Finally, the statistical significance of the variables was determined using a p value of ≤ 0.05. The prevalence of anaemia among pregnant women in the late trimester and newborns was 34 (16.11%, 95% CI: 11.42, 21.78) and 64 (30.33%, 95% CI: 24.20, 37.01), respectively. The mean ± standard deviation of the newborn babies' weight was 3.19 ± 0.49 kg. The proportion of low birth weight among newborns was 26 (12.32%, 95% CI: 8.20, 17.53%). The independent effect of anaemia on low birth weight was 4.19 times while all other factors were constant (COR = 4.19, 95% CI: 1.70, 10.30). Maternal educational status [unable to read and write (AOR = 10.94, 95% CI: 1.74, 68.58) and attained secondary education (AOR = 8.06, 95% CI: 1.53, 42.36)], and maternal anaemia (AOR = 3.51, 95% CI: 1.29, 9.55) were associated with low birth weight after adjusting with all other variables. In this study, the proportion of low birth weight was high. Here, maternal anaemia alone had a significant independent role in the development of low birth weight. Maternal education status and anaemic conditions were associated with low birth weight among newborns. Early detection and treatment of maternal anaemia during pregnancy is crucial with the usual nutritional-related care.