Study area, design, and period
A community-based cross-sectional study was conducted from March 2019 to April 25, 2019, in Sinan District, Northwest Ethiopia. Sinan District is located about 327 km far from Addis Ababa the capital city of Ethiopia and, 303 km away from Bahir Dar. The District is divided into 17 Keble's, two Keble's in the urban and 15 Keble's are rural. The total population was estimated as 120,000, children aged 6–23 months years old were 4251. There are 5 health centers and 20 health posts in the District. The people in this area are engaged in different activities such as farming, and trade. The District is also known by its potato which is the main income-generating means for the community. The socio-cultural interaction is strong which shows working together during harvesting, good participation of celebration (wedding, mahiber, Edir, Ekub) together (Sinan District communication office) [19].
Population
The source population was all children aged 6–23 months who reside in Sinan District. The study population was all children aged 6–23 months living –in the selected Kebeles in Sinan District. All children from 6 months to 23 months old age who live in the selected Keble for at least 6 months were included in the study. However, children with a visible physical deformity like kyphosis, scoliosis were excluded from the study since it may under or overestimate anthropometric results.
Sample Size And Sampling Procedure
The required sample size was calculated by considering wasting, underweight, and stunting as exposure variables. Moreover, stunting was considered as an independent variable since it yielded a maximum sample size of which 374. The sample size was computed on single population proportion formula by using: 95% CI (two-sided), 5% margin of error, and 58.1% proportion of stunting among children 6–23 months [14]. By considering 10% for non-response rate a total sample size of 411 mother-child pairs was proposed. Of the 17 administrative clustered Keble’s in the District, 6 clusters were selected by simple random sampling technique. A list of households with children aged between 6 to 23 months was obtained from the health post-EPI registration book. Then all the clustered households were included in the study. By using a cluster sampling technique a total of 431 infants and young children within the selected clustered Keble's was studied.
Data Collection Tool And Procedure
Data were collected through the home to home visits from the mothers or caregivers of the children using an interviewer-administered questionnaire. To maintain consistency, the questionnaire was first prepared in English and then translated to Amharic and then translated back to English. Six data collectors and three field supervisors were recruited for the study. The training was given to data collectors and supervisors. Length and weight measurements of children were taken using calibrated equipment and standardized techniques. The functionality of the equipment used to measure weight and length was checked each in each participant before measurement. Weight was measured to the nearest 10 g using a salter scale for less than 24 months old children. For all measurements, three readings were taken from each child, and the largest was recorded on the questionnaire. A standardized seven food group containing the Dietary Diversity Score (DDS) was used to assess the dietary intake of children [20]. A 24-hour dietary recall method was used, accordingly, the mothers were asked to report the food items consumed by the child in the previous 24-hours proceeding the days of the survey.
The household wealth index was computed using a composite indicator for urban and rural residents by considering properties such as selected household assets and the size of agricultural land. Using Principal Component Analysis (PCA), the factor scores were summed and ranked into poor, medium, and rich.
Data processing and analysis
Data were coded and entered into EPI-data version 4.2 statistical software and analysis was done by SPSS Version 25. Nutrition-related data (length and weight) were analyzed using the WHO Anthro software. The Z-scores of indices, Weight-for-Length Z-score (WLZ), WAZ, and Length-for-Age Z-score (LAZ) were calculated and compared using the WHO Multicenter Growth Reference Standard [21].
Bivariable Analysis was done individually for all independent variables with stunting, wasting, and underweight. Variables with a p-value of < 0.25 in the Bivariable analysis were entered into a multivariable logistic regression analysis to identify the independent factors. Odds ratio a corresponding 95% Confidence interval (CI) were computed to assess the strength of the association. In the multivariable logistic regression analysis, variables with a p-value of < 0.05 were considered as statistically significant. The fitness of the model was checked using the Hosmer and Lemeshow goodness of fit test.
Operational Definitions
Undernutrition was defined as the child having either of H/Age Z-score <-2, or W/Age Z-score <-2 or W/H Z-score <-2 SD [22, 23].
Underweight was defined as children having W/Age Z-score < -2 SD [22, 23].
Stunting was defined as children having H/Age Z-score < -2 SD [22, 23].
Wasting was defined as children having W/H Z-score < -2 SD [22, 23].
Minimum Dietary Diversity
if a child has taken four food groups as the minimum acceptable dietary diversity, a child with a DDS of less than four was classified as poor dietary diversity; otherwise it was deemed to have good dietary diversity [20]
Food insecurity; Food insecurity is a condition in which people experienced limited or uncertain physical and economic access to safe, sufficient, and nutritious food to meet their dietary needs or food preferences for a productive, healthy, and active life [24]. It was assessed by using the household food insecurity access scale. Household food insecurity was measured using the Household Food Insecurity Access Scale (HFIAS) that was developed by the Food and Nutrition Technical Assistance (FANTA) project [24]. For the Household Food Insecurity Access Scale (HFIAS) measurement, each of the questions was asked with a recall period of four weeks (30 days). The respondent was first asked an occurrence question-that is, whether the condition in the question happened at all in the past four weeks (yes or no). If the respondent answers "yes" to an occurrence question, a frequency-of-occurrence question was asked to determine whether the condition happened rarely (once or twice), sometimes (three to ten times), or often (more than ten times) in the past four weeks.
Wealth index
The composite indicator of socio-economic status, which was computed by the application of principal component analysis (PCA). Initially, household asset data were prepared for analysis. Before the PCA, using frequency, important variables that can discriminate households were selected to reduce the number of variables. The binary variables were coded to 0 and 1 and categorical variable options were converted into binary variables and dummy variable was created as 0 and 1.After data preparation, variables were standardized to change variables into the same scale for comparison by subtracting the mean from each value and then dividing the standard deviation. Once standardized, the variables have a mean of 0 and a standard deviation of 1. It was categorized as poor, medium, and rich.
Poor socioeconomic status
household which belonged to lower tercile of wealth index score.
Medium socioeconomic status
household which belonged to medium tercile of wealth index score.
Rich socioeconomic status
household which belonged to a higher tercile of wealth index score.