Nutrition Behavior on Micronutrient Among Growth Children in Central Highland of Ethiopia: Cluster Randomized Trial.

Overview

Hypotheses of the study 1. Mothers/ caregivers who have less knowledge and attitude about the prevention of IDD their table salt obtained from in the households has less quantity of iodide than those mothers/ caregivers who might have knowledge and attitude. 2. Mothers/ caregivers with poor knowledge and attitude in iodized salt utilization circumstances that their index children have at higher risk of iodine deficiency compared with their properly utilizes counterparts. linear 3. Children's poor dietary intake has low hemoglobin concentration compared to their peers who used diversified dietary intake. 4. Children with a low concentration of iodine have stunted growth (linear growth) compared with their high iodine concentration peers at the end of the follow-up period of fifteen months. 5. Children with a low concentration of hemoglobin have stunted growth (linear growth) compared with their high hemoglobin concentration peers at the end of the follow-up fifteen months. 6. Higher concentrations of micronutrients due affect the growth of children compared with their higher concentration of micronutrients at the end of the follow-up period of fifteen months.

Objective: The aim of this study is to determine effect of BCC on micronutrients intake and growth of children age 6-59 month old in Arsi Zone highland, Oromiya, Ethiopia. Chapter 1 knowledge and attitude about the prevention of iodine deficiency disorders among women and quantification of iodine found in table salt. This chapter presents the investigation of iodine content in table salts samples obtained from households and headquarters markets and the women's understanding and approach status about iodine deficiency disorders. Chapter 2 Median urinary iodine concentration and associated factors among children age 6 to 59 months; It summarizes the median level of iodide found in children's urine and determined significant associated factors. Chapter 3 hemoglobin level and associated factors among children age 6 to 59 months. It describes predictors of knowledge and attitude about the prevention of iron deficiency anemia among women and it presents the hemoglobin threshold of children and determines factors. Chapter 4 effect of NBC on iodised salt utilization and median urine iodine concentration among the growth of children. This chapter describes the impact of NBC intervention on iodised salt utilization in the HH, compaction of the endine - baseline difference of median urine concentration, and its significant association with the growth of children. Chapter 5 effect of NBC on prevent anemia and hemoglobin concentration among the growth of children. This chapter describes the impact of NBC on iron-rich dietary intake in the HH. Also, the chapter described the comparition of endine - baseline mean differences of hemoglobin concentration, and factors associated with the growth of children. Chapter 6 micronutrient concentration effects on growth defect among children; this chapter describes the deference endline - baseline difference of the mean differences in iron and iodine and concentration association with linear growth of children. Methods: Community based, clustered randomized controlled trial will be carried out. Study sample size: The sample size was determined using Gpower 3.0 software assuming a power of 95%, precision of 5%, and an effect size of 0.25 giving 834. Additionally, we considered the loss of study participants due to an increase in age of children above 59 months for the given intervention period was 11% =95. Where the design effect had 10% =83 and a final the estimated sample size was 1012. Multistage sampling method was applied to select 16 kebeles \[lower administration Units\] randomly and equally assigned into intervention and control clusters using computer ENA 2011 version software. Further, systematic random sampling will be used to select mothers/caregivers with their children from randomly assigned kebeles Baseline data will be collected from recruited mothers and from their pair children. Questionnaire on behaviours on dietary intake of children and micronutrients utilization, and anthropometric data will be collected; Households' table salt samples will be collected and analyzed with a titration biomarker in Ethiopian Public health institute food and nutrition laboratory (EPI). Urine samples for baseline will be collected and transported to EPI and analyzed to determine urine iodine Concentration (UIC) and this will be applicable at the end line of nutrition behavior change intervention. Blood samples will be collected to determine hemoglobin level before after nutrition behavior change intervention implementation. Data processing and analysis: Anthropometric and other data were entered into EpiData 3.0 version software and transferred and analyzed using the Statistical Package for Social Science statistical software for Windows, version 21, Anthropometric data will be exported to Emergency Nutrition Assessment \[ENA\] software to generate height for age Z-score (HAZ) and weight for height z-score \[WHZ\]. HAZ ≥ -2 Z-score will be categorized as normal growth status and HFA \< -2 z-score will be indicated as a growth defect. According to WHO classification, \> 40% is very high and 30 to 39% is high and 20 to 29 medium and \< 20% is low (22). Also, weight for height Z score (WHZ) was generated to determine wasting among children (16, 17). Anthropometric results of children's growth at baseline and end-line surveys were compared with the WHO 2005 growth standard using ENA software. Linear regression was used to determine the effect of iron and iodine concentration on the linear growth of children. Independent sample t test will be used to determine mean differences between end-line-baseline in micronutrient concentrations (iodine and iron) and will be compared between intervention and control groups and significance will be determined with Standard Error (P\<0.05) . Finally, independent variables that will have P \<0.25 in samples t-test will be transferred to Generalized Estimating Equations \[GEE\] for further analysis and the results presented using Beta coefficients (β) and 95% confidence intervals.