Maternal Under-nutrition and Effect of Amaranth Grain Flat-bread on Anemia in Northern Zone of Sidama Region, Ethiopia.

In Ethiopia, maternal malnutrition is a major public health concern. Underweight and anaemia are the two most common nutritional disorders in pregnant women, and they frequently co-exist. A prevalent kind of nutritional anaemia is iron-deficiency anaemia (IDA). These issues are primarily caused by a lack of important micro and macronutrients in the diet, as pregnant women eat primarily cereal-based foods. As a result, the burden of under-nutrition in Ethiopia necessitates a more in-depth investigation of underused crops that are high in nutrients and have the potential to minimize food and nutrition insecurity. Although the amaranth plant grows widely in Ethiopia and can boost food intake, its nutritional potential has yet to be acknowledged by community consumers and health professionals.

Methods: A community-based cross-sectional study will be conducted on a sample of 528 pregnant women in their first trimester to examine the prevalence of anemia and identify its risk factors and determine the prevalence of co-existing anemia and under-nutrition among pregnant women. From pregnant women who will be diagnosed for anemia, C-reactive protein (CRP) and serum ferritin will be analyzed to determine IDA. Following this, a parallel-group community-based randomized controlled trial will be conducted for six months among 306 anemic women to evaluate the effect of locally prepared amaranth grain flat-bread on hemoglobin concentration and anemia prevalence compared to the frequently consumed maize bread among pregnant women. A multi-stage sampling method will be utilized to select eligible pregnant women. The households with pregnant women will be identified by conducting the house-to-house census.For categorical variables, summary measures will be presented as absolute frequencies and percentages, but for numerical variables, the mean with standard deviation (SD) will be utilized as a descriptive measure after the distribution is checked for normality. A multi-level mixed-effect logistic/linear regression model will be used to account for between and with cluster effects. We will be used intention-to-treat analyses approach.