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Background: Evidence suggests that Egypt, a country in North Africa, has a significant number of children at serious risk of excess body weight. Yet, there is a dearth of studies on overweight and obesity among children under 5 years in the country. This study examined the prevalence and correlates of overweight and obesity among under-five children in Egypt. Methods: Data were retrieved from the latest (2008 and 2014) Egypt Demographic and Health Surveys (EDHS). A total of 42,568 children under 5 years were included. The prevalence of overweight and obesity was described using proportions whereas the factors associated with the prevalence were examined using logistic regression. Results: Of the 42,568 children under 5 years, about one in every six (17%) were overweight or obese. Children aged 19–37 months, those with birth weights >4 kg, those given large portions of protein foods (eggs and meat), and those whose mothers were in the rich wealth quintile had significant risks of overweight or obesity. Conclusion: Overweight and obesity are highly prevalent among children under 5 years in Egypt. Interventions developed to address these two overnutrition indicators in Egypt need to consider variations in risk factors across age, birth weight, food types and portions, and maternal wealth status.
Since 1980, several surveys have been carried out in Egypt to obtain data from the community on the current health situation including a series of Demographic and Health Surveys (DHS) of which the 2014 Egypt Demographic and Health Survey (EDHS) is the most recent (18). The 2014 EDHS is of special importance as it is the latest and first national health survey since 2008. The initial results of the 2014 EDHS show that key maternal and child health indicators, including antenatal care coverage and medical assistance at delivery, have improved. However, the survey also documents several critical challenges, particularly relating to fertility and family planning (18). The findings of the 2014 EDHS together with the service-based data are very important for measuring the achievements of health and population programs. The 2014 EDHS was conducted under the jurisdiction of the Ministry of Health and Population (18). International classification of functioning, disability and Health (ICF) provided technical support for the survey through the DHS program. The DHS Program is sponsored by the United States Agency for International Development (USAID) to assist countries worldwide to obtain information on key population and health indicators (18). USAID/Cairo also provided funding to support the implementation of the survey. UNICEF and UNFPA also contributed funding to the survey. The 2014 EDHS survey design has two components; a survey of ever-married women aged 15–49 years and a special Health Issues survey to obtain updated information on other critical health problems facing Egypt (18). The data are publicly available at http://measuredhs.org. Details on the approach used in gathering the data including the sampling methods can be found in the EDHS reports (18, 19). This study was based on the latest [2014 (EGKR61DT.ZIP) and 2008 (EGKR61DT.ZIP)] children’s data drawn from Egypt’s Demographic and Health Surveys (EDHS). The EDHS children’s data contained information on children’s nutrition and women aged 15–49 years. Approximately, 42,589 children under five were sampled to partake in the study (18, 19). A total of 18 variables were included in the study, and these variables were categorized into three: (i) Child variables which included age (0–18 months = infant, 19–37 months = toddlers, 38–59 months = children), sex (males and females), birth weight (<2.5 kg = low birth weight, 2.5–4.0 kg = Normal weight, 4.1 and above = overweight), place of residence, access to a bicycle, access to vehicle, child given carbohydrate foods, child given protein foods, child given fatty foods and child given fruits, (ii) Maternal variables including maternal age (11–19 years = adolescent, 20–28 years = young adult, 29 years and above = adult), educational level, wealth index, maternal BMI (when BMI 25 kg/m2 = Overweight/obese) (20), marital status (married = currently married, widow+divorce+never married = not married), postnatal visit, and current work status), (iii) Husband/partner’s educational level (Table 1). Variable categorization and description. Body mass index (BMI) was measured and calculated using the WHO’s new standard for child growth (21). The new standard is an international standard for assessing nutritional status, physical growth, and child development from birth to the 5th year. Overnutrition (overweight and obesity) was calculated in standard deviation using the z-score ≥ 2. Childhood overweight/obese was defined as z-scores ≥ 2. Also, the mother’s overweight/obese was considered a BMI > 25 kg/m2 (21). To determine the actual child BMI value in the datasets, the measure was divided by 100. With regards to other covariates, we assessed child food consumption by these questions: “Did you give your child eggs and meat (protein food)?” “Did you give your child any other fruits?” and “Did you give your child oil, fats, and butter products?” The responses to these questions are described in Table 1. Descriptive statistics including frequencies and percentages were performed. Aside from the descriptive statistics multivariate analyses (logistic regression) were computed in the final model to observe associations between the independent and dependent variables. Based on recommendations from empirical literature (15), the logistic regression analysis was set at a 95% confidence interval and adjusted for other covariates which included: age of child, sex of child, birthweight, place of residence, access to car, access to bicycle, child given carbohydrate, child given protein food, child given fatty foods, child given fruits, maternal age at first birth, mother’s educational level, wealth index, mother’s BMI, antenatal visit, postnatal visit, father’s educational level, and current work status. Logistic regression was used because the outcome variable was categorized into two, Overweight/obese = 1 and Not overweight/obese = 2. The analysis was performed using Stata/SE 14.
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