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Dietary diversity (DD) is a concern for poor people in developing countries, particularly in Africa. Most people’s diets consist primarily of monotonous carbohydrate staples, with little or no animal products and few fresh fruits and vegetables. The aim of this intervention was to see how nutrition education delivered by trained health professionals improved preschool-aged children’s consumption of DD and animal-sourced foods. The study used a quasi-experimental design with 588 preschool-aged children. Researchers used a multistage sample technique followed by a systematic random sampling technique. A χ2 test was used to determine the baseline differences in demographic and socioeconomic factors between the two groups, as well as the relationship between predictors and child DD and animal-source foods (ASFs). The researchers used generalized estimating equations to assess the change in the difference in outcomes between the intervention and control groups, as well as the association between predictors and child DD and ASFs. The adjusted odds ratio with the corresponding 95% confidence intervals was reported to show the strength of the association. The findings of this study revealed that there was a highly significant difference in both DD scores (DDS) and ASFs between the control and intervention groups DDS (p < 0.003) and ASF (p < 0.001). According to the findings of this study, nutrition education can significantly improve DDS and ASF consumption among preschool-aged children.
Ilu Abba Bor is a zone in the Oromia regional state, 600 km from the country's capital, Addis Ababa. There are 14 districts in the zone: one administrative town and 13 rural districts, with a total population of 934,783 people, including 153,585 children under the age of 5 and 100,209 children aged 2–5 years. The western section of the country runs from 70°27′40″ N to 90°02′0″ N latitude and 340°52′12″ E to 410°34′55″ E longitude. There are three main climate zones: temperate, humid, rainy and dry arid. The highest mean annual temperature in most highland areas of Ilu Abba Bora ranges from 10.6°C to 26°C. A quasi‐experimental design with pretest–posttest and control groups was used to assess the effects of community‐based nutritional education on DD and ASFs among preschool‐aged children in 22 rural kebeles. The sample size was calculated using a G‐Power model with the following assumptions: 52.5% expected prevalence of the previous study among children aged 24–59 months, 2.07 odds ratio (OR) (Dewana et al., 2017), 80% power and a 5% margin of error. After accounting for a design effect of 2 and a 15% nonresponse rate, the total sample size was 588 participants (Figure 1). This paper is part of a PhD dissertation. The project sample size was determined after the sample size for each objective was calculated and the largest one was chosen. Flow diagram of the research process A multistage sampling technique followed by a systematic random sampling technique was used to identify caregivers with preschool‐aged children. In the first step, four districts were selected at random from a total of 14 districts. To avoid information contamination, two neighbouring districts from the selected districts were chosen as interventions and the other two adjacent districts as control groups due to their similarity in terms of access to health care, water and other services. The intervention group received two districts at random, whereas the control group received two districts. Each group (intervention and control) had 11 kebeles (Ethiopia's smallest administrative units) selected at random. Following the selection of kebeles, preschool‐aged children (2–5 years) were identified and registered in each chosen kebele. A code was given to households with children aged 2–5 years old, which was used as a sample frame. A proportional allocation was carried out after the registration of preschool‐aged children, and a sample was taken from both the intervention and control groups using a systematic random sampling procedure. If the caregivers/households had more than one child, the lottery technique was used to choose one at random. In all intervention groups, NE was implemented for a total of 9 months after baseline data collection was completed. A NE package was developed using family dietary guidelines (Burgess & Glasauer, 2004) and other relevant nutritional education intervention modules and topics were adopted and modified as local situations from literature (Mushaphi et al., 2015; Siew et al., 2020) for community‐based nutrition intervention as well as using the findings of a baseline survey. All health extension workers, trained health professionals and caregivers/mothers can use it to implement nutrition interventions for mothers of preschool‐aged children. It is easy to use, interactive and user‐friendly. This NE package consists of three educational modules and a number of supporting educational materials. The education modules focus on three areas: healthy diet awareness, nutrition and hygiene, with a total of 10 topics, namely, eating a variety of foods, providing preschoolers aged 2–5 years with starchy foods, consuming a variety of vegetables and fruits on a regular basis and consuming dry beans, split peas, lentils and soy regularly. It also included daily consumption of chicken, fish, meat, milk and eggs; however, salt and fat should be used sparingly, and sugar‐containing foods and beverages should be consumed in moderation and not between meals to ensure food safety and cleanliness. To summarize the content of the modules, the first module was about caregiver awareness about healthy diets and feeding children aged 2–5 years. These topics were addressed in Sessions 1 and 2. The first and second sessions are more focused on mothers' or caregivers', child feeding knowledge and practice. A second module was about child nutrition (DD), which focuses on the seven food groups and related issues. In this module, Sessions 3–9 were covered. In module three, the issues of hygiene and sanitation were addressed in Session 10. The caregivers/mothers gathered in a place that was convenient for them and comfortable for the group, such as a school, health post or health centre. Each kebele was allotted one trained health professional and one health extension worker, suggesting that health extension workers served as helpers and facilitators. Over the course of 5 months, 10 sessions were held every 2 weeks for approximately 30–45 min, with two sessions held in the seventh month as a refresher. The caregivers were introduced to the topic of the day on the day of the presentation. To assess prior knowledge and to encourage discussion, specific questions were asked about the topic. At the end of the session, caregivers were evaluated to see how well they understood the information. The mechanism of communication is determined by context, cultural preference and how people normally receive and obtain information. The educational materials included group discussions, lectures, role‐plays, active participation and demonstrations to teach mothers about child feeding. In this study, the group discussion method was utilized more because it is an excellent way to encourage interaction between group members and it allows for more participation. To improve and track compliance with the intervention, monitoring activities and process evaluations were used. The principal investigator and supervisors visited each home to check on the intervention's progress and talk with the mothers and caregivers about what they were doing. Investigators and supervisors have been meeting on a regular basis to discuss the project's progress and any necessary modifications. The process evaluation's goal was to document the intervention's implementation process to see if the activities were carried out as planned, determine the degree to which the activities reached children and mothers/caregivers and investigate contextual factors that may have impacted on target children and caregivers. The caregiver's or father's phone number, as well as the home address, was registered with the researcher, supervisors and educators in charge of that kebele as assigned by the researcher. The educators assigned to the area would call the caregivers 2 days before and on the eve of visitation day to remind them of the visitation day. The educators provided individualized counselling during follow‐up. This was done on various days based on each participant's visitation day at home, and when not available at home, any convenient and available location was always used as an alternative. During visitation day, the supervisors assessed the number of training sessions including cooking demonstrations held with trained health professionals, the number of training session role‐plays and cooking demonstrations held with caregivers and also the number of lecture and group discussion sessions held with educators. It also provided information that can help in the interpretation of outcome indicators and can also be used to monitor the attendance of mothers and caregivers during nutritional education sessions. The supervisor took attendance on the number of recruited caregivers, the number of caregivers attending the education session and the number of home visits conducted by educators. To ensure that the study arms were similar in terms of sociodemographic characteristics, child care practices, dietary practices and child nutrition status, a baseline analysis of 569 caregivers/mothers with preschool‐aged children was undertaken at the time of recruitment. All caregivers/mothers were interviewed by trained data collectors using a structured interviewer questionnaire at the baseline and end of the study. To ensure consistency, the questionnaire was written in English first and then translated into the local language (Afan Oromo), and then back to English. Before the actual data collection, a pretest of the questionnaire was conducted on 5% of the total samples outside the study area to determine the acceptability and application of the instruments and procedures. Twelve bachelor's degree nurses were hired as data collectors, and six bachelor's degree public health officers were responsible for supervising. All data collectors and supervisors received intensive training over the course of 3 days. Investigators, qualified supervisors and data collectors took all anthropometric measurements to prevent within‐examiner error. A principal investigator and professional supervisors supervised the data collection. They supervised and double‐checked each questionnaire for completeness, irregularities, inconsistencies and out‐of‐the‐ordinary answers, making immediate corrections as needed. Computer frequencies were used to check for missing variables, outliers and other errors during data entry. The original questionnaire was revised at this time to correct any identified errors. The survey included socioeconomic and demographic characteristics, as well as water and hygiene habits, maternal and child health and child feeding habits. Trained data collectors conducted face‐to‐face interviews with the mothers/caregivers in their homes. The age of the child was calculated using the child's date of birth and the date of the interview. When the actual day of birth was not recorded or was unclear, the caregiver was asked to make a guess based on recent occurrences in the area. The age of the child was determined by subtracting the date of birth from the date of data collection. The DD score (DDS) was assessed using the repeated 24‐h dietary recall method, which was taken three times (two weekdays and one weekend). Fasting and feasting days were included in the description of each day of the week. The children's caregivers were asked to remember everything their children ate or drank during the 24‐h period of study. The individual DDS of the study respondents was calculated according to the FAO guidelines (FANTA II, 2010). The sum of scores in each of the seven food groups, on a scale of 0–7, was used to calculate DD. At least four of the seven food groups listed below were used to compute the minimal DD (MDD) indicator: (1) grains, roots and tubers; (2) dairy products; (3) animal/flesh meals; (4) legumes and nuts; (5) vitamin A‐rich fruits and vegetables; (6) eggs; and (7) other fruits and vegetables (19). The Ethiopia Demographic and Health Survey factors were used to create the Household Wealth Index, which is focused on household ownership of fixed assets, services, housing characteristics and other factors (UNICEF/WHO/WorldBankGroup, 2016). Data were checked, cleaned, coded and entered into Epi‐data 3.1 and then exported to SPSS 21.0 for further analysis. Recoding and transforming of some variables were performed. A χ 2 test was used to look at the baseline differences in demographic and socioeconomic characteristics between the two groups. An independent sample t test was used to determine the mean difference in DDS and ASFs between the intervention and control groups. The change in the difference in outcome between the intervention and control groups, as well as the association of predictors with DDS and ASFs in children, were determined using generalized estimating equations (GEEs) with a binary logistic function and exchangeable correlation structure. GEE adjusts the standard errors by accounting for clustered observations. An independent covariance matrix was chosen for the main models by assuming two observations are equally correlated within a cluster, with no correlation between observations from different clusters. Accordingly, the bivariable GEE for sociodemographic and economic factors, water and hygiene habits, maternal and child health and child feeding habits factors for child DDS and ASFs were fitted. A multivariable GEE was used to fit all the variables in the bivariable with a p value of 0.25. Time and treatment interaction were used to determine the intervention's effectiveness. The adjusted OR (AOR) with the corresponding 95% confidence intervals was reported to show the strength of the association. All analyses were carried out with the purpose of taking into account the intention‐to‐treat (ITT) concept. Variables having a p value less than 0.05 were declared statistically significant in multivariable analysis.
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