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In Sub-Saharan Africa, being overweight in childhood is rapidly rising while stunting is still remaining at unacceptable levels. A key contributor to this double burden of malnutrition is dietary changes associated with nutrition transition. Although the importance of socio-economic drivers is known, there is limited knowledge about their stratification and relative importance to diet and to different forms of malnutrition. The aim of this study was to assess diet diversity and malnutrition in preschoolers and evaluate the relative importance of socioeconomic resources. Households with children under five (5467) were enrolled using a multi-stage sampling procedure. Standardized tools and procedures were used to collect data on diet, anthropometry and socio-economic factors. Multivariable analysis with cluster adjustment was performed. The prevalence of stunting was 19.6% (18.5–20.6), wasting 3.2% (2.8–3.7), and overweight/obesity 11.4% (10.6–12.2). Stunting, overweight, wasting and limited diet diversity was present in all social strata. Low maternal education was associated with an increased risk of stunting (Adjusted odds ratio (AOR): 1.8; 1.4–2.2), limited diet diversity (AOR: 0.33; 0.26–0.42) and reduced odds of being overweight (AOR: 0.61; 0.44–0.84). Preschoolers in Addis Ababa have limited quality diets and suffer from both under-and over-nutrition. Maternal education was an important explanatory factor for stunting and being overweight. Interventions that promote diet quality for the undernourished whilst also addressing the burgeoning problem of being overweight are needed.
This study is a cross-sectional population-based survey covering the entire city of Addis Ababa, Ethiopia. Ethiopia is the second-most populous country in Africa, and the fastest-growing economy in the region [29]. Currently, the urban population constitutes 16% of the country’s population and is expected to double by 2037 [30]. Addis Ababa, the capital city of Ethiopia, has an estimated 3.4 million inhabitants [31] and is home to one-fourth of the countries urban population [32]. Despite the city being the main hub for economic activity, contributing approximately 50% towards the national GDP, it faces many challenges: high rates of unemployment (23.5%), poor housing conditions, and severe inequalities among the socio-economic strata [28,32]. The city is administratively divided into 10 sub-cities and each sub-city has 10–15 woredas (districts). This study covered all 116 woredas using a multi-stage sampling strategy; first, each woreda was divided spatially into five equal sections to serve as a cluster, of which one was selected using a computer-generated simple random sampling. In each cluster, guided by an interval of every third household, the team visited 60 households. All households that had at least one child under the age of five years and a caregiver/mother who consented to participate were included in the study. Mothers who were not available after three consecutive visits were deemed ineligible. Anthropometric measurements were taken from all children under five in the selected household. For the dietary assessment, one child from each household was selected. If the household had more than one eligible child, one was randomly selected to serve as a reference (index); this was enabled through the Open Data Kit (ODK) software on tablets. Data collection for this study was based on two rounds of population-based surveys. The first round of collection took place during the wet season, reflecting a lean period, and the second round took place during the dry season, reflecting the post-harvest period. Data were collected using a structured pre-coded interviewer-administered questionnaire uploaded onto tablets. The items included in the questionnaire were socioeconomic factors such as demographics, education, household assets, food security, and food consumption. The questionnaire was first prepared in English and then translated into the Amharic language, the official language of Ethiopia. A bilingual expert panel composed of English and Amharic speakers was convened to translate the study tool [33]. Ten teams of field workers, each consisting of five data collectors and one supervisor, collected the data. Everyone in the team received two weeks of training on interviewing techniques, the questionnaire contents, anthropometric measurements, and the use of tablets for data collection. Field personnel in charge of anthropometric measurements were given training which included a theoretical explanation, demonstration of said skills, and practice sessions both in class and in a mock field setup. Standardization was done according to recommendations [34]. The entire field procedure was pretested in clusters outside of the study sample. Necessary modifications were done following the pretest, which mainly involved replacing ambiguous words. The field supervisors and the researchers were closely involved at every stage of the fieldwork. Data were sent directly to a password-protected server. Stata version 14 software was used for data cleaning, which involved applying logic checks and running frequencies [35]. Anthropometric measurements were taken for each child. Weight and length/height of each child were measured according to the World Health Organization (WHO) standards [36]. The weight of each child, minimally clad and/or removing wet diapers, was measured to the nearest 0.1 kg using the United Nations Children’s Fund (UNICEF) electronic scale. Recumbent length or height was measured to the nearest 0.1 cm using the UNICEF model wooden board as per the WHO protocol. The participant’s socio-demographic characteristics were summarized by sex (male or female), age of mother in years, age of the child in months, family size (2–4, 5–7, 8+), current marital status (married/living together, divorced/widowed/separated), sex of the household head (female/male), and whether the mother was involved in an income-earning activity (yes/no). Socioeconomic resources for the purpose of this study were defined as maternal education, household wealth, and household food security. They were measured as follows: Maternal education was assessed by asking what the highest level of schooling completed by the mother at the time of the survey was. The level of education was then grouped into five categories: never attended/not finished first grade, grade 1–4, grade 5–8, grade 9–12, and college-educated, reflecting the Ethiopian educational system [37]. The household wealth index was constructed using principal component analysis (PCA). The indicator variables included were: ownership of house, type of housing unit, housing material (floor, roof, wall material), access to separate toilet facility and clean drinking water, as well as assets such as a bicycle, motorbike, car, cell phone, radio, TV, refrigerator, bed, Metad (electric stove used for making a local bread called Injera) and a savings account. Principal components with eigenvalues greater than one were retained to construct wealth index values and then categorized into wealth tertiles (low, medium and high) to serve as relative measures of household economic status [38]. The household food security status was assessed using the Household Food Insecurity Access Scale (HFIAS). A 1-month recall period was used to assess the food security of households. The household was categorized as food secure if it had not experienced any food insecurity conditions or had rarely worried about not having enough food, whereas food-insecure households were categorized as mild, moderate and severe in accordance with the guidelines [39]. The dietary assessment followed the Food and Agriculture Organization (FAO) recommendations [40]. First, the mothers/caretakers were asked to provide a 24-h recall of foods consumed by the child both at home and outside the home. For each item, the mother was asked whether the child consumed more than a spoonful. Once the mother completed listing the foods, including all the ingredients, she was shown pictures of common foods from each food group to help her recall and verify the food her child consumed within the past 24 h. The child food groups were developed based on the food items recommended in the Infant and Young Child Feeding (IYCF) guidelines. Total dietary diversity score (which was a count of “yes” response for the 7 food groups the child consumed) was calculated for each child. In accordance with the IYCF guidelines, children were considered to have adequately diversified dietary intake if they had at least four of the seven food groups, and those who had 3 or less of the food groups were considered to have inadequate diversity [41]. Anthropometric indices were calculated using the WHO Anthro software [42]. The Z-scores of indices height-for-age Z-score (HAZ), and weight-for-height Z-score (WHZ) were categorized using the WHO child growth standards. A child with a HAZ less than −2 standard deviations (SD) was defined as stunted, while those with WHZ less than −2 SD from the reference population were classified as wasted and +2 SD as overweight/obese [36]. Data analyses were done using Stata version 14 [35]. Frequencies and percentages were calculated for all categorical variables. Cross-tabulation with a chi-square test for association and linear trend was done. Further, three statistical models were tested to evaluate independent effect associations while adjusting for potential confounders. The first model assessed the association of child nutritional status and diet diversity with each of the selected socioeconomic variables (household wealth, maternal education, household food security, and child sex) individually. The second model controlled for potential confounders (maternal age and child age) and the third model included both the potential confounders and all four socio-economic resources of interest. The generalized equation estimate (GEE) was used in all three models to estimate the crude odds ratios, and the adjusted odds ratios (AOR) along with their respective 95% confidence intervals (95% CI). All models were adjusted for clustering and the level of significance was set at p-value (<0.05). Multicollinearity was checked using the variance inflation factor (VIF) with the cut off set at below 5. The study protocol was approved by the institutional review board of Addis Continental Institute of Public Health Ref No. ACIPH/IRB/004/2015 on 15 December 2015. Permission was granted by all the sub-cities and woreda level health offices to facilitate the fieldwork. Each study participant was provided with comprehensive information about the objectives and goals of the research and oral consent was obtained prior to the data collection.
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