Adolescence is characterized by rapid growth and development with a significantly increased need for macro and micronutrients. However, there is little empirical evidence on the burden of anaemia among adolescent girls in developing countries such as Ethiopia. This study aims to address this gap by evaluating the magnitude of anaemia with an aim to guide design of intervention modalities to address anaemia among adolescent girls. The study employed a community based cross sectional design. The study was conducted on weekends to capture both in school and out of school adolescent girls. Data was collected from a total 1323 adolescent girls. From each district, we randomly selected villages and ensured that the sampled households had a range geographical spread (lowlands, highlands) within the larger category of rural and urban. We performed anaemia testing using HemoCue B-Haemoglobin analyser. We applied a complex survey data analysis method to estimate the level of anaemia. The hemoglobin level was adjusted for altitude and smoking status. We ran a logistic regression model to evaluate predictors of anaemia. The overall anaemia prevalence ranged from 24 to 38%, with an average rate of 29%. Less than half of the girls heard the term anaemia, and about one third knew the relationship between anaemia and the intake of iron rich foods. The risk of anaemia is higher among adolescent girls in their early adolescence period (10–14 years) (Adjusted Odds Ratio (AOR); 1.98; 95% CI; 1.03, 3.82] and among adolescent girls who lived in moderately food insecure households (AOR 1.48; 95% CI; 1.05–2.09). However, knowing the term “anaemia” was found to be protective against the risk of anaemia. The risk of anaemia was particularly high among adolescent girls in their early age and among those living in food insecure households. The prevalence of anaemia among adolescent girls is a moderate public health problem. According to the WHO set criteria, the districts could be candidates for intermittent iron and Folic acid supplementation program.

Understanding the national burden and trend of micronutrient deficiencies helps to guide effective intervention strategies under various circumstances. There is, however, a lack of evidence on tren...

Background: The etiology and risk factors of anemia are multifactorial and varies across context. Due to the geospatial clustering of anemia, identifying risk factors for anemia should account for the geographic variability. Failure to adjust for spatial dependence whilst identifying risk factors of anemia could give spurious association. We aimed to identify risk factors of anemia using a Bayesian geo-statistical model. Methods: We analyzed the Ethiopian Demographic and Health Survey (EDHS) 2016 data. The sample was selected using a stratified, two- stage cluster sampling design. In this survey, 9268 children had undergone anemia testing. Hemoglobin level was measured using a HemoCue photometer and the results were recorded onsite. Based on the World Health Organization’s cut-off points, a child was considered anaemic if their altitude adjusted haemoglobin (Hb) level was less than 11 g/dL. Risk factors for anemia were identified using a Bayesian geo-statistical model, which accounted for spatial dependency structure in the data. Posterior means and 95% credible interval (BCI) were used to report our findings. We used a statistically significant level at 0.05. Result: The 9267 children in our study were between 6 and 59 months old. Fifty two percent (52%) of children were males. Thirteen percent (13%) of children were from the highest wealth quintile whereas 23% from the lowest wealth quintile. Most of them lived in rural areas (90%). The overall prevalence of anemia among preschool children was 57% (95% CI: 54.4–59.4). We found that child stunting (OR = 1.26, 95% BCI (1.14–1.39), wasting (OR = 1.35, 95% BCI (1.15–1.57), maternal anemia (OR = 1.61, 95% BCI (1.44–1.79), mothers having two under five children (OR = 1.2, 95% BCI (1.08–1.33) were risk factors associated with anemia among preschool children. Children from wealthy households had lower risk of anemia (AOR = 0.73, 95% BCI (0.62–0.85). Conclusion: Using the Bayesian geospatial statistical modeling, we were able to account for spatial dependent structure in the data, which minimize spurious association. Childhood Malnutrition, maternal anemia, increased fertility, and poor wealth status were risk factors of anemia among preschool children in Ethiopia. The existing anaemia control programs such as IFA supplementation during pregnancy should be strengthened to halt intergenerational effect of anaemia. Furthermore, routine childhood anaemia screening and intervention program should be part of the Primary health care in Ethiopia.

Accumulating evidence clearly shows poor implementation of nutrition interventions, in Ethiopia and other African countries, with many missed opportunities in the first 1000 days of life. Even though there are high‐impact interventions in this critical period, little is known about the barriers and facilitators influencing their implementation. This paper aims to explore barriers and facilitators for the implementation of nutrition services for small children with a focus on growth monitoring and promotion, iron‐folic acid supplementation and nutrition counselling. We conducted a qualitative study in four districts of Ethiopia. The data collection and analysis were guided by the consolidated framework for implementation research (CFIR). A total of 42 key informant interviews were conducted with key stakeholders and service providers. Interviews were transcribed verbatim and coded using CIFR constructs. We found that from 39 constructs of CFIR, 14 constructs influenced the implementation of nutrition interventions. Major barriers included lack of functional anthropometric equipment and high caseload (complexity), poor staff commitment and motivation (organisational incentive and reward), closed health posts (patient need and resource), false reporting (culture), lack of priority for nutrition service (relative priority), poor knowledge among service providers (knowledge and belief about the intervention) and lack of active involvement and support from leaders (leadership engagement). Adaptability and tension for change were the facilitators for the implementation of nutrition interventions. Effective implementation of nutrition interventions at primary health care units requires several actions such as improving the healthcare providers' motivation, improving leadership engagement, and creating a strong system for monitoring, supportive supervision and accountability.

Malaria and malnutrition are the major causes of morbidity and mortality in under-five children in developing countries such as Ethiopia. Malnutrition is the associated cause for about half of the deaths that occur among under-five children in developing countries. However, the relationship between malnutrition and malaria is controversial still, and it has also not been well documented in Ethiopia. The aim of this study was to assess whether malnutrition is associated with malaria among under-five children. A case–control study was conducted in Adami Tulu District of East Shewa Zone in Oromia Regional State, Ethiopia. Cases were all under-five children who are diagnosed with malaria at health posts and health centres. The diagnosis was made using either rapid diagnostic tests or microscopy. Controls were apparently healthy under-five children recruited from the community where cases resided. The selection of the controls was based on World Health Organization (WHO) cluster sampling method. A total of 428 children were included. Mothers/caretakers of under-five children were interviewed using pre-tested structured questionnaire prepared for this purpose. The nutritional status of the children was assessed using an anthropometric method and analyzed using WHO Anthro software. A multivariate logistic analysis model was used to determine predictors of malaria. Four hundred twenty eight under-five children comprising 107 cases and 321 controls were included in this study. Prevalence of wasting was higher among cases (17.8 %) than the controls (9.3 %). Similarly, the prevalence of stunting was 50.5 % and 45.2 % among cases and controls, respectively. Severe wasting [Adjusted Odds Ratio (AOR) =2.9, 95 % CI (1.14, 7.61)] and caretakers who had no education [AOR = 3, 95 % CI (1.27, 7.10)] were independently associated with malarial attack among under-five children. Children who were severely wasted and had uneducated caretakers had higher odds of malarial attack. Therefore, special attention should be given for severely wasted children in the prevention and control of malaria.

Background: The widely used nutritional assessment tool used for the elderly includes the Mini Nutritional Assessment (MNA) and Mini Nutritional Assessment–Short Form (MNA-SF) tool. These tools have not been evaluated for their validity and reliability among the elderly population of developing countries such as Ethiopia. This study aimed to evaluate the reliability and validity of the full and short form of the Mini Nutritional Assessment tool among the elderly in Ethiopia. Method: We evaluated the reliability and validity of the tools using a community-based cross-sectional study among 506 elderly individuals. Accuracy, sensitivity, specificity and cut-off point were evaluated to determine the validity of both the full MNA and MNA-SF tool. Reliability was assessed using Cronbach’s α coefficient. The criterion-related validity of the MNA tool was evaluated by computing the correlation between the total MNA score and anthropometric measurements. The Youden index was used to determine best cut-off points of the full MNA and MNA-SF. Result: The mean MNA score was 19.9 ± 4.5. Cronbach’s α value of the full MNA tool was 0.7. The overall accuracy of the full MNA was 91% (95% CI, 87.5%–94.9%). The sensitivity and specificity of the full MNA tool using an established cut-off point was 87.9% and 89.6% respectively. Youden index analysis showed that the best cut-off point to detect the malnourished and those at risk of malnutrition using the full MNA was 16 (sensitivity 90.4% and specificity 86.8%). The reliability of the MNA-SF as measured by Cronbach’s α was 0.5. The overall accuracy of the MNA-SF was found to be 93% (95% CI, 0.90–0.96). By using the Youden index the best cut-off point for MNA-SF to detect malnutrition was 7.5 (sensitivity 85.7% and specificity 89%). Conclusion: The full MNA tool was a valid and reliable tool to identify elderly individuals who are malnourished, at risk of malnutrition and well-nourished with modulation of cut-off points. However, the short MNA tool was valid and but not reliable in this study.