Introduction
The double burden of malnutrition (DBM) is defined as the co-occurrence of under-nutrition along with over-nutrition or diet related non communicable diseases (NCDs) [
1‐
4]. This co-occurrence or simultaneous existence of under-nutrition (predominately stunting) and over-nutrition (overweight/obesity) is also termed as nutritional dual-burden [
5]. It can occur at population, household and individual levels [
5‐
7].
The DBM is a global problem posing a serious public health challenge especially in low- and middle-income countries (LMIC), where high prevalence of under-nutrition continues to exist and overweight is increasing at an alarming rate [
1,
8‐
11].
According to the global nutrition report for the year 2018, the prevalence of the co-existence of overweight and stunting among under-five children is 1.87% (8.23 million) globally. The magnitude of the coexistence of overweight/obesity and stunting is 2.7% in Europe, 2.3% in Africa and 0.8% in the Americas [
12].
Evidence have indicated that DBM is more prevalent in urban areas and it is a concern particularly for countries having a high prevalence rate of stunting [
13,
14]. It particularly affects the urban poor, the rural rich and people living in slum areas [
15]. Children aged below 5 years are also the most susceptible age group to DBM [
6].
Sub-Saharan Africa (sSA) is suffering with the DBM with high magnitude of under-nutrition and an increasing burden of overweight/obesity and diet-related NCDs [
16]. Ethiopia is not an exception since, the country is undergoing nutrition transition as a result of economic growth and urbanization, which could led to rise in the magnitude of DBM [
17]. In Ethiopia, malnutrition has been declining over the last two decades as a result of the implementation of both nutrition specific interventions and nutrition sensitive interventions guided by the National Nutrition Programs (NNP I & NNP II) [
18]. However, the problem of under nutrition particularly stunting remains as a major public health problem in Ethiopia and simultaneously the magnitude of overweight and obesity is increasing rapidly especially in urban areas [
19‐
21]. The problem of childhood obesity in Ethiopia is not recognized as a serious problem and lacks adequate attention [
22].
The study setting, Addis Ababa, is the capital city of Ethiopia and it is the biggest and most rapidly growing city where 25% of the country’s urban population lives [
23]. Although the prevalence of stunting is lower in Addis Ababa compared to the other regions of Ethiopia, still 19.6% of under-five children are suffering with stunting and 11.4% with overweight/obesity [
24]. Evidence regarding DBM in Ethiopia is very scarce especially at individual level and particularly in children. Most of the studies are concentrated in investigating under-nutrition and overweight/obesity independently. Therefore, this study was aimed to assess the co-existence of overweight/obesity and stunting and associated factors among children aged 6–59 months.
Methods
Study area
The research was carried out in Addis Ababa, Ethiopia’s capital and largest city. Addis Ababa is a chartered city with three levels of authority: city government at the top, 11 sub-cities in the middle, and 126 woredas at the bottom. The total population of the city for the year 2020 was estimated to be 4,793,699 [
25]. According to Addis Ababa health bureau, the number of under-five children in 2021 was 342,989 and 304,879 (6.4%) of them were children between 6 and 59 months of age. In the city, six governmental hospitals and 98 health centers are providing comprehensive health care services to the population of the city.
Study design and period
An institution based cross-sectional study design was conducted from May to June, 2021.
Study population
All children aged 6 to 59 months with their respective mothers/care givers who were residing in Addis Ababa, Ethiopia was the source population. The study population was all randomly selected children aged 6 to 59 months with their respective mothers/caregivers who visited public health centers for growth monitoring and promotion services, vaccination services, Vitamin A supplementation, deworming and under-five outpatient department (OPD) in Addis Ababa during the study period.
Sample size determination
Sample size was determined based on a single population proportion formula assuming, proportion (P = 50%) because of lack of evidence in Ethiopia, and to get maximum sample size, confidence level (95%) and margin of error (5%), the minimum required sample size was 384. Adding 10% for non-response rate, the final sample size was 422.
Sampling procedure
Simple random sampling method was employed among 98 health centers to select 29 (30%) of the health centers. Then the final sample size was allocated proportionally to each of randomly selected health centers based on their performances (daily average number of under-five children who have been coming to the health center seeking health care services). Systematic sampling method was used to select study participants (mother to child pairs) from each of randomly selected health centers within the predetermined study period.
Data collection procedures
Data were collected using interviewer administered questionnaire which was adapted from various similar studies [
17,
26‐
32] from mothers /caregivers of children aged 6 to 59 months. Six B.Sc. holder health professionals (four data collectors and two supervisors) who had experience in data collection and supervision were recruited and deployed to collect data and supervise the process. Prior to data collection, the data collectors and supervisors received 3 days theoretical and practical training on the study.
Anthropometric measurement
Height
Height/length measurements were carried out with standard measuring boards to the nearest 0.1 cm. Children under the age of 24 months were measured in lying down (recumbent) position on the board, while children aged 24 to 59 months were measured in a standing-up position. Mothers were requested to remove their children’s shoes, hair ornaments and other things that interfere in the measurement of the length/height of the child [
33].
Weight
Weight of infants was measured using a Salter spring scale while young children using digital beam balance with a minimum cloth and barefoot to the nearest of 0.1 kg. Weighting scales were calibrated regularly. Height for age Z score (HAZ) and weight for height Z score (WHZ) were determined using WHO Anthro software version 3.1.0.
Wealth index
Wealth index was calculated using principal component analysis (PCA). Mothers were asked questions about their household fixed assets and housing condition adapted from the Ethiopian demographic and health survey report (EDHS-2016) [
34].
Data management analysis
Data were entered in to Epi-Info version 7.2 Software. Then data were exported into statistical software package for social sciences (SPSS) version 20 for analysis after performing data cleaning. Descriptive statistics were computed to summarize and describe the data. Binary logistic regression model was fitted to identify factors associated with the outcome variable. Variables with the result of p-value of less than 0.25 in the bi-variable analysis were entered in to the multivariable analysis (hierarchical logistic regression model). Crude odds ratio (COR) and adjusted odds ratio (AOR) using 95% confidence interval were computed to see the strength of associations. A p – value of less than 0.05 in the hierarchical logistic regression analysis was used to declare statistical significance.
Data quality management
To ensure data quality, experienced data collectors and supervisors were recruited, deployed and trained. Furthermore, pre-testing of the questionnaire was carried out. The data collectors were also supervised and provided onsite technical assistance both by the supervisors and the principal investigator to assure the quality of data. In addition to this, data completeness and consistency were checked on daily basis and corrective measures were taken timely. Moreover, measurement equipment was calibrated regularly before starting the anthropometric measurements. After data collection, each questionnaire was coded and checked for completeness and consistency prior to data entry. Checking of data for missed values, inconsistencies and outliers were also done after data entry in to EPI-Info version 7.2 and after exporting into SPPS version 20.
Variable measurement
Outcome variable
The outcome variable was co-existence of overweight/obesity and stunting which is defined as the existence of both overweight/obesity (WHZ score > + 2 SD) and stunting (HAZ score of < − 2 SD) with in the same child. It was dichotomized in to co-existence of overweight/obesity and stunting as “Yes” or “No”.
Exposure variables
The predictor variables were categorized into child characteristics, distal factors, intermediate factors and proximal factors. The child characteristics include child age and child sex. The distal factors were maternal education, maternal occupation, father’s education, and head of the household and house hold wealth index category.
The Intermediate factors were marital status; family size, number of under-5 children, maternal age at child birth, and type of family, availability of health insurance, child birth order, and child ever received any vaccinations and type of latrine.
The proximal factors were weight of the child at birth, child ever breast fed, time of initiation of breast feeding, duration of breast feeding, age initiated for complementary feeding (CF), diarrhea in the previous 2 weeks, cough in the previous 2 weeks, fever in the previous 2 weeks, vitamin A dose supplementation within last 6 months, and child dewormed within the last 6 months.
Discussion
The study revealed that magnitude of the co-existence of overweight/obesity and stunting among under-five children was 5.1%: showing that Ethiopia is experiencing the double burden of malnutrition at individual level. The finding is comparable with a study conducted in Mexico (5%) and India (5.4%) [
29,
35]. But it is higher than studies conducted in Kenya (1%), South Africa (1.2%), Vietnam (1.4%), Bolivia (2.3%), Thailand (1.3%) and Colombia (0.1%) [
13,
27,
28,
36‐
38]. The possible reason for this might be high prevalence rate of stunting in Ethiopia [
19]. This is because countries having higher magnitude of under-nutrition are more at risk for an increased prevalence of obesity [
31,
39]. However the result is lower than findings from Egypt (10.9%), Ghana (19%) and Mexico (10.3%) [
8,
29,
32]. The possible reason for this may be the difference in socio-economic status, urbanization and the stage of nutrition transition among countries. The difference in study period and sample size might be also another possible reasons for the discrepancies in the prevalence of CEOS across countries.
The study showed that child age is significantly associated with the co-existence of overweight/obesity and stunting in model two. The odd of the co-existence of overweight/obesity and stunting among children aged 6–23 months was 2.86 times higher than that of children aged 24–59 months. This finding is in line with a study conducted in Indonesia and Papua New Guinea [
31,
40]. The possible reason could be due to feeding practices of the mother/caretaker within the first 1000 days of life. Malnutrition in children is associated with poor breastfeeding practice and inappropriate offering of solid foods [
41]. This is explained by the fact that inappropriate offering of solid food and poor breast-feeding practice will cause stunting because of infection as of breast feeding is a means to boost the immunity of the child and the other hand it may be leads to an intentional weight gain. That is why children aged under 3 years are most at risk for stunting, which may be associated with increased risk of being overweight in later life [
32].
The study also noted that maternal education status was strongly associated with the co-existence of overweight/obesity and stunting in the final model. The odd of the co-existence of overweight/obesity and stunting among children belonging to non-educated mothers was 4.98 times higher than that of children belonging to educated mothers. This result is in agreement with a study conducted in Cameroon [
30], china [
42] and Guatemala cited in Kosaka and Umezaki, 2017 [
43]. This might be because women are often considered as primary caregivers [
44] and therefore lack of knowledge and certain attitudinal factors by the mother could eventually influence nutritional status of children through feeding practices [
45]. Having formal education also enables mothers to take better care, better utilization of the health services, and also to implement better hygiene practice of their child [
46].
The other factor which is significantly associated with the co-existence of overweight/obesity and stunting in the final model is maternal age during birth of the child. Children whose mother had maternal age < 28 during birth were 78% more likely to experience the co-existence of overweight/obesity and stunting compared to mothers aged ≥28 during birth. This result is in agreement with a study conducted in Cameroon [
30]. It is also supported by a finding from Mexico [
29]. The possible explanation for this could be young maternal age during pregnancy is correlated with shorter newborn birth length and small for gestational age delivery [
47].
In the final model, children of 3rd and above birth order were 6.38 times more likely to be affected by the co-existence of overweight/obesity and stunting compared to children of 1st birth order. This is supported by studies conducted in Bangladesh [
48] and Sub Saharan Africa in 18 countries [
49]. This is because children born later are vulnerable to sub-optimal nutrition and health outcomes [
50]. The other explanation could be that as the number of births rises, the food and resources allocated to family members in a household decreases. Therefore, births of higher order might be affected by malnutrition and other health problems [
48].
Study limitations
The study was a facility based and as a result prevents generalization to all under five children living in Ethiopia. In addition to this, the study did not assess variables which could be potentially linked to the co-existence of overweight/obesity and stunting such as children’s physical activity, dietary diversity, maternal height and weight. Moreover, the study was also subjected to recall bias since some of the variables were dependent on the memory of mothers and might lead to recall bias.
Conclusion
The study revealed that the magnitude of the co-existence of overweight/obesity and stunting among under-five children in Addis Ababa was low. In addition to this, child age, maternal education, birth order of the child and maternal age during birth were found to be significantly associated with the co-existence of overweight/obesity and stunting. Therefore, access to formal education for females should be improved. Maternal health programs should also emphasize on improving service uptake and quality of family planning services to delay early pregnancy and reduce the number of high birth order pregnancies. Further research using longitudinal study design and large sample size are also needed to understand the real contributors of the co-existence of overweight/obesity and stunting.
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