DOI: 10.5061/dryad.djh9w0w9p
title: Postwar dietary diversity among children aged 6-23 months in northern Ethiopia

description: Introduction: Conflict exacerbates poor complementary feeding and reduces
 dietary diversity. Before the 2020–2022 war in northern Ethiopia, around
 74% of children aged 6–23 months failed to meet minimum dietary diversity
 (MDD) and post-war prevalence was unknown. This study aims to assess MDD
 prevalence and associated factors among children aged 6–23 months in a
 town in northern Ethiopia two years after the ceasefire. Methodology: A
 health facility-based cross-sectional study of 584 participants was
 conducted in a town in northern Ethiopia. Sociodemographic and dietary
 data were collected using a 24-hour dietary recall questionnaire and
 analyzed in STATA ® version 15. Pre-war dietary diversity was estimated
 using data from the 2016 and 2019 Ethiopian Demographic and Health
 Surveys. Results: MDD declined from 33.2% pre-war period to 25.2% (95% CI:
 21.6-28.7) in the post-war period. Children aged 18–23 months were 3.2
 times more likely to achieve MDD than those aged 6–11 months (p = 0.001).
 Middle- and high-income households had 6.13-fold and 13.58-fold higher
 odds of meeting MDD, respectively (both p &lt; 0.001). Households with
 5–8 members had 3.6-fold higher odds of providing MDD compared to those
 with 1–3 members (p = 0.017). Children of mothers aged 26–35 years (AOR =
 0.48, p = 0.026) and 36–42 years (AOR = 0.29, p = 0.017) had lower odds of
 meeting MDD. Higher paternal education (AOR = 2.58, p = 0.031) and
 paternal occupation as a merchant (AOR = 3.17, p = 0.001) were positively
 associated with MDD. Post-war, grain (77.5% to 92.1%) and legume (33.9% to
 69.3%) consumption increased significantly, while flesh foods (20.9% to
 7.2%) and vitamin A-rich foods 46.8% to 26%) declined. Conclusion:
 Post-war dietary diversity in remains low, influenced by socioeconomic and
 demographic factors. Significant reductions in nutrient-dense foods
 highlight critical gaps in child nutrition. Targeted nutrition education
 for caregivers and interventions promoting dietary diversity are essential
 in conflict-affected settings.
description: Study Design and Population This study
 employed a facility-based cross-sectional design, conducted in late 2024,
 in a town in northern Ethiopia. The study population comprised
 mothers/caregivers with children aged 6–23 months who attended Extended
 Program on Immunization (EPI) services at one of three randomly selected
 health centers. Participants were recruited through random sampling. Data
 on sociodemographic characteristics and dietary intake were collected via
 face-to-face interviews using a pretested and standardized
 questionnaire. <strong>Study
 Setting</strong> This study was conducted in a
 town in northern Ethiopia two years after the end of the war in northern
 Ethiopia (2020-2022). The town, located in nothern Ethiopia, has an
 estimated population of 600,000 as of 2024. It is served by several
 hospitals and health centers. <strong>Study
 variables</strong> The outcome variable was
 Minimum Dietary Diversity (MDD), defined as the consumption of foods and
 beverages from at least five of eight defined food groups within a 24-hour
 period, according to the updated WHO/UNICEF definition ((UNICEF) 2021).
 The eight food groups are: 1) breast (milk); 2) grains (grains, roots,
 tubers, and plantains); 3) legumes (beans, peas, lentils, nuts, and
 seeds); 4) dairy products (milk, infant formula, yogurt, cheese); 5) flesh
 foods (meat, fish, poultry, organ meats); 6) eggs; 7) vit-A (vitamin-A
 rich fruits and vegetables); and 8) other (fruits and vegetables)
 (Kennedy, Ballard et al. 2011, UNICEF 2022). Consumption of a specific
 food groups was coded as 1, and a sum of the eight columns “food-sum” was
 created by merging the eight columns. A second column “mdd” identified the
 child’s dietary diversity as “<em>diverse=1</em>” when
 food-sum &gt;=5, or “<em>not-diverse=0</em>”, when
 food-sum &lt;5.<br><br>
 <strong>Data Collection</strong>
 Data were collected using a structured, validated questionnaires
 adapted from FAO and EDHS tools (Kennedy, Ballard et al. 2011, ICF 2016).
 The questionnaire was initially developed in English, translated into
 Tigrigna (the local language), and then back-translated to ensure
 consistency and accuracy. Face-to-face interviews were conducted with
 mothers/caregivers, focusing on dietary intake over the previous 24 hours
 and relevant sociodemographic factors. Dietary data were collected based
 on the updated WHO/UNICEF minimum dietary diversity guidelines. To
 minimize recall bias caregivers were prompted to recall specific foods and
 meals consumed by the child during the reference period. Community health
 workers, who had prior experience in interviewing, were trained and
 recruited to conduct the data collection. Daily supervision was
 implemented to ensure the accuracy and completeness of the data. While we
 did not conduct a calibration study, the UNICEF dietary diversity tool has
 been validated in similar settings, providing confidence in its
 reliability for assessing minimum dietary diversity.
 <strong>Sampling technique</strong>
 This study used multistage sampling technique to identify the
 participants of this study. In the first stage of sampling, three three
 administrative areas were randomly selected. Then during the second stage,
 one health facility was randomly selected from each area. In the third
 stage, children were selected from each health center using a non-random,
 first-come, first-served approach, where the eligible children arriving at
 the health center on the vaccination day of the week were recruited. The
 final sample was proportionally allocated based on the number of children
 visiting each facility. Children who came with non-consenting caregivers
 and children with severe chronic illnesses or congenital anomalies were
 excluded from the study. <strong>Data
 Analysis</strong> Data were entered into
 Microsoft Excel ®, cleaned, and then analyzed using STATA ® statistical
 software version 15. Missing data were imputed using median imputation for
 continuous variables and mode imputation for categorical variables.
 Descriptive statistics were used to summarize sociodemographic
 characteristics and dietary diversity. Categorical variables were
 presented as frequencies and percentages, while continuous variables were
 categorized based on common frameworks. Chi-square or Fisher’s exact tests
 were used to assess associations between categorical variables, and binary
 logistic regression analysis was performed to identify factors associated
 with MDD. To address potential confounding, we included key
 sociodemographic variables in the final multivariable logistic regression
 model. These variables were selected based on prior literature and
 theoretical relevance to dietary diversity.
 <strong>Prewar estimation of MDD</strong>
 The pre-war dietary diversity estimates (EDHS 2016 and EDHS 2019)
 were obtained from the Ethiopian Demographic and Health Survey (DHS) and
 are not included in this dataset due to licensing restrictions.
 Researchers can access these data by registering on the DHS website (https://dhsprogram.com) and requesting permission for use. <strong>References</strong> Kennedy, G., Ballard, T., & Dop, M. C. (2011). <em>Guidelines for measuring household and individual dietary diversity</em>. Food and Agriculture Organization of the United Nations. ICF. 2016. Ethiopia Demographic and Health Survey 2016. Addis Ababa, Ethiopia, and Rockville, Maryland, USA: CSA and ICF World Health Organization and the United Nations Children’s Fund (UNICEF). (2021). <em>Indicators for assessing infant and young child feeding practices: definitions and measurement methods</em>. UNICEF. (2022). <em>United Nations Children’s Fund, Division of Data, Analysis, Planning and Monitoring (2022). Global UNICEF Global Databases: Infant and Young Child Feeding: Egg and/or flesh food consumption, Minimum dietary diversity, Minimum meal frequency, Minimum acceptable diet</em>
description: # Postwar dietary diversity among children aged 6-23 months in northern
 Ethiopia
 [https://doi.org/10.5061/dryad.djh9w0w9p](https://doi.org/10.5061/dryad.djh9w0w9p) ## Description of the data and file structure This dataset was collected as part of a cross-sectional comparative study examining the impact of war on child malnutrition by assessing dietary diversity among children aged 6–23 months in northern Ethiopia. Data were obtained from caregiver-reported 24-hour dietary recalls across post-conflict (2024) periods. The study aimed to determine changes in minimum dietary diversity (MDD) prevalence and identify factors influencing child nutrition in a post-war setting. Data collection involved structured interviews in randomly selected health facilities, with additional sociodemographic and household characteristics recorded. The dataset includes nutritional intake, socioeconomic variables, and household composition to facilitate further analysis of war-related disruptions in infant and young child feeding practices. ### Files and variables #### File: mdd\_anon.csv **Description:** Contains post-war (2024) dietary diversity data from a town in northern Ethiopia, including child feeding practices, household characteristics, and sociodemographic variables. ##### Variables * **childage**: age of child in months (6-11, 12-17,18-23) * **hhnumber**: family size including parents and siblings (small, medium, large)            * **childorder**: birth order of the child (first-born, later-born)    * **religion**: religion of the mother (1, 2)    * **momage**: age of mother in years (17-25, 26-35, 36-42)        * **marital**: marital status of the mother (1, 2) * **momedu**: educational level of the mother (1, 2, 3)       * **momjob**: occupation of the mother (Homemaker, Government, Other)       * **dadedu**: educational level of the father (1, 2, 3)                   * **dadjob**: occupation of the father (Government, Merchant, Other) * **hhincome**: monthly household income tercile in Ethiopian birr (Low, Middle, High)       * **delivery**: place of delivery of the child (Health Facility, Home)           * **internet**: does the mother use internet (Yes, No)           * **wassick**: has the child suffered from diarrhea in the last two weeks (Yes, No) * **breast**: was the child breastfed in the last 24 hours    (Yes, No) * **dairy**: has the child consumed dairy products (milk, yoghurt, ) in the last 24 hours  (Yes, No) * **grains**: has the child consumed grains, tubers and roots in the last 24 hours  (Yes, No) * **vit_A**: has the child consumed vitamin A rich fruits and vegetables in the last 24 hours (Yes, No)     * **other**: has the child consumed other fruits and vegetables in the last 24 hours (Yes, No)        * **eggs**: has the child consumed eggs in the last 24 hours (Yes, No)         * **flesh**: has the child consumed meat and organ meat in the last 24 hours (Yes, No)      * **legumes**: has the child consumed legumes in the last 24 hours (Yes, No) **Missing values** **Blank cells** indicate missing data. ## Code/software The dataset (`mdd_anon.`csv) is provided in comma-separated value format, which can be accessed using free and open-source software such as LibreOffice Calc, Google Sheets, or the free online version of Microsoft Excel (Office365). The statistical analyses were conducted in Stata 15, which was used for data cleaning, descriptive statistics, logistic regression, and sensitivity analysis. The submission contains `.do` files used at different stages of the analysis. The `data_cleaning.do` script handles missing data, variable recoding, and dataset preparation. The `descriptive_stats.do` script generates summary statistics and initial exploratory data analysis. The `regression_analysis.do` script runs logistic regression models and tests assumptions such as linearity of logit. The `sensitivity_analysis.do` script compares complete case analysis with multiple imputation results to assess the robustness of findings. ## Access information The pre-war dietary diversity data (2016–2019) was obtained from the Ethiopian Demographic and Health Surveys (EDHS), which is publicly available through the Demographic and Health Surveys (DHS) Program at [https://www.dhsprogram.com/](https://www.dhsprogram.com/). Access to EDHS datasets requires registration and approval from the DHS Program. The data is provided under the DHS Terms of Use, which permit use for academic and research purposes. This dataset does not include the pre-war EDHS data, and researchers interested in accessing it must obtain it directly from the DHS Program. The post-war dietary diversity data (2024) was collected as part of this study and is publicly available within this repository. This dataset is shared under a CC0 license, ensuring unrestricted use for research and analysis.