Dietary Diversity among Children Aged 6-23 Months in Aleta Wondo District, Southern Ethiopia

Background. Dietary diversity (DD) is among the core infant and young child feeding (IYCF) indicators. However, in many developing countries, meeting the minimum standards of DD is challenging and information concerning its determinants is limited. Objective. To assess the level and predictors of DD among children aged 6-23 months in rural communities of Aleta Wondo district, Sidama zone, Southern Ethiopia. Method. A community-based cross-sectional study was conducted in rural Aleta Wondo in February 2016. Multistage sampling was employed to recruit 502 children aged 6-23 months. DD was assessed by asking the mother whether the index child had received food from the standard seven food groups in the previous day, without setting minimum intake restrictions. Ultimately, the dietary diversity score (DDS) was rated on a 7-point scale, and it was modeled using linear regression analysis. The outputs are presented using adjusted regression coefficients (β). Results. Only 12.0% (95% confidence interval: 9.0-15.0%) of the children met the minimum recommended DD, receiving from four or more from seven food groups. The analysis identified eleven significant predictors of DDS. As the maternal knowledge of IYCF increases by a unit, DDS raised by 0.21 units (p=0.004). Unit increment in the husband’s involvement in the IYCF score was linked with 0.32 units improvement in DDS (p=0.016). One unit change in the ordinal category of household food insecurity was associated with 0.13 reduction in DDS (p=0.001). Similarly, household wealth index (β = 0.54, p=0.041), father’s literacy (β = 0.48, p=0.002), ownership of home garden (β = 0.38, p=0.01), mother’s participation in cooking demonstrations (β = 0.19, p=0.036), and child age in months (β = 0.04, p=0.001) were all positively associated with DDS. Furthermore, receiving IYCF information via mass media (β = 0.04, p=0.001) and during antenatal (β = 0.91, p=0.022) and postnatal checkups (β = 0.21, p=0.043) were positive predictors of DDS. Conclusions. Promoting the socioeconomic status of the community, strengthening of home gardening, involving husbands in IYCF, and enhancing maternal knowledge of IYCF may advance DD. The study was conducted among mothers of children aged 6–23 months living in the Aleta district, Sidama zone. The capital of the district Aleta Wondo town is located 330 km south of Addis Ababa. According to a 2015 estimate, the district has a population of 205,000, of whom 89% dwell in rural areas and 12,729 (6.2%) were children under the age of two years. The vast majority of the inhabitants are Sidama in ethnicity (92%) and are affiliated to Protestant Christianity (73%). Administratively, the district is organized into 2 urban and 27 rural villages—the smallest administrative unit in Ethiopia comprising approximately 1,000 households. The Aleta Wondo district has an area of 210 km2, and more than 70% of the land is considered arable. The inhabitants are mainly reliant on subsistence agriculture, and the major crops grown are maize, root crops especially Ensete (false banana), haricot bean, and cash crops such as coffee and Khat. Regarding access to health services, the district has 7 health centers and 27 health posts. A community-based cross-sectional study with both descriptive and analytic elements was conducted in February 2016. All children aged 6–23 months who were permanent residents of the 27 rural villages of Aleta Wondo district were considered as the source population of the study, while children in 8 rural randomly selected villages were considered as the study population. The sample size for determining the percentage of children aged 6–23 months who met the minimum DD was estimated as 509 using single population proportion formula [19]. The computation was made assuming 10.6% expected proportion [16], 95% confidence level, 4% margin of error, design effect of 2, and 10% compensation for possible nonresponse. On the contrary, a sample size of 109 was considered optimal for identifying determinants of DDS. The computation was made using G∗power software [20] assuming the data analysis would be made via the multivariable linear regression model based on 22 predictors. Other specifications made during the computation were 95% confidence level, 90% power, 0.3 (medium) effect size, and 10% contingency for possible nonresponse. Accordingly, the largest sample size (509) was taken as the ultimate sample size of the study. The study employed the multistage cluster sampling technique for identifying the study subjects. Initially, the 27 rural villages were stratified into two agroecological zones: highland and midland based on their altitude above sea level (ASL). villages located 1,500 to 2,300 and above 2,300 meters ASL were considered as having midland and highland agroecology, respectively. From the available 23 midland and 4 highland villages, 6 and 2 villages, respectively, were selected using a lottery method. The total sample size (n = 509) was proportionally distributed to the 8 selected villages in consideration of their population size. Then, in each villages, exhaustive listing of the eligible children was made by engaging the local health development army (HDA) members, and the list was used as the sampling frame of the study. Ultimately, the required number of children was selected using a systematic sampling technique. The data were gathered by eight trained data collectors and two field supervisors using a pretested and structured questionnaire. The tool was developed in English, translated into the local Sidama language, and back translated to English to check its consistency. Sociodemographic, economic, and IYCF-related questions were directly adopted from the standard DHS questionnaire [21]. Dietary diversity was assessed by asking the mother whether the child had received food from the standard seven food groups in the preceding day, without setting minimum intake restrictions [15]. The seven food groups were grains, roots, and tubers; legumes and nuts; dairy products excluding breast milk; flesh foods (meat, fish, poultry, or organ meats); eggs; vitamin A-rich fruits and vegetables; and other fruits and vegetables. A dietary diversity score (DDS), which ranges from 0 to 7, was computed. Children who received at least 4 of the 7 food groups in the reference period were considered to have met the minimum DD [15]. Meal frequency was measured as a proxy indicator of calorie intake in accordance with the recommendation of the WHO [15]. Children aged 6–8 months who received at least two meals and children aged 9–23 who received 3 or more meals in the preceding day were assumed to have met the minimum meal frequency standard [15]. Children who had satisfied both the minimum standards for DD and meal frequency were considered to have an acceptable diet [15]. Continued breastfeeding rate at one and two years was estimated based on proportion of children aged 12–15 and 20–23 months, respectively, who received breast milk in the preceding day. Timely introduction of complementary foods was determined based on proportion of children aged 6–8 months of age who received solid, semisolid, or soft foods in the previous day. Similarly, age-appropriate breastfeeding was estimated based on the percentage of children who received breast milk, as well as solid, semisolid, or soft foods, during the previous day [15]. Household food security was measured using Household Food Insecurity and Access Scale (HFIAS) based on the frequency of occurrence of nine food insecurity-related events in the preceding 4 weeks. The scale classifies the extent of food insecurity into four ordinal categories: food secure and mild, moderate, and severe insecurity [22]. Mothers’ knowledge of IYCF was assessed based on their response to ten questions developed by the investigators. The questions were focused on issues including optimal duration of exclusive and total breastfeeding; appropriate time for introducing complementary food; dietary diversity; and opinions on feeding infants and young children with animal source foods. Right responses were coded as 1, and all other responses were coded as 0. Ultimately, it was scored on a 10-point composite scale. The questions used for assessing the mother’s knowledge on IYCF are provided as a supporting file with this article (Supporting ). Husband involvement in IYCF was measured based on the response of the mothers to seven questions pertaining their husbands’ support in child feeding. These include practice of the husband in terms of discussing child feeding issues at home, availing money to buy special foods (animal source foods) for the baby, bringing special foods home, supporting the mother while preparing meals for the baby, feeding the child himself, supporting the mother in domestic chores while she engages in food preparation or child feeding, and following and encouraging her for proper child feeding. Positive practices were coded as 1, and the rest were coded as 0. Ultimately, it was scored on an 8-point composite scale. As depicted in Figure 1, the study considered various predictors of DDS. These include sociodemographic characteristics of the mother (age, educational status, marital status, and involvement in income-generating activities), educational status of the father of the child, socioeconomic status of the household including wealth index, household food insecurity and land size, age and sex profile of the index child, number of children under the age of five years in the household, agroecology of the village, maternal knowledge of IYCF, husband’s involvement in IYCF, ownership of livestock and home garden, exposure to nutrition counseling and education through mass media and interpersonal communication with health extension workers (HEWs) and HDA members, participation in cooking demonstrations, and exposure to IYCF information during antenatal (ANC) and postnatal (PNC) visits (Figure 1). Conceptual framework of the study. Data entry was made using EPi Info 7 software and exported to SPSS 20 for analysis. Frequency distribution, measures of central tendency, and dispersion were used to summarize the data. Core and selected optional IYCF indicators were computed as recommended in the WHO guideline [15]. Wealth index was computed as a measure of household wealth using principal component analysis (PCA). Fifteen variables related to ownership of selected household assets, size of agricultural land, quantity of livestock, materials used for housing construction, and ownership of improved water and sanitation facilities were considered. Finally, the generated principal component was divided into 5 equal quintiles (lowest, second, middle, fourth, and highest). Bivariable and multivariable linear regression analyses were used to model DDS. All explanatory variables that demonstrated a p value less than 0.25 in bivariable analysis were considered as candidates for the multivariable models. In order to avoid overadjustment bias and unnecessary adjustment, independent variables were fitted into two different distal and proximate models in accordance with the conceptual framework of the study [23]. The outputs of the analyses are presented via crude and adjusted unstandardized regression coefficients (β). In final multivariate linear regression models, the extent of multicollinearity was measured using variance inflation factor (VIF) and found to be within tolerable range (less than 10). Linearity of the association and normality, homoscedasticity, and independence of the error terms were evaluated using partial plots. The goodness-of-fit of the models was assessed using the F-test and adjusted R-squared value. The study was cleared by the Institutional Review Board of College of Medicine and Health Sciences, Hawassa University. Permissions were taken from regional, zonal, and district health offices. Data were collected after taking informed written consent from the mothers. All information gathered was kept confidential. At the end of the survey, mothers who were providing a poorly diversified diet to their children were given nutrition education.