Abstract
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Undernutrition and its determinants among children aged 6–59 months in Southern Ethiopia
Abstract
Malnutrition is responsible for over one-third of deaths among children under the age of five in low-and middle-income countries, including Ethiopia, and is largely preventable. The objective of this study was to determine the prevalence of undernutrition and its contributing factors among children aged 6–59 months in the Gedio zone of Southern Ethiopia. A community-based cross-sectional study design was used, and data were collected from 403 children and their mothers selected through random sampling technique. Anthropometric measures were converted to Z-scores using WHO-Anthro version 3.2.2 software. The prevalence of underweight, wasting, and stunting were 19.7% (95% CI 16-24%), 10% (95% CI 7–13%), and 49% (95% CI 44–54%) respectively. Low birth weight (AOR=2.8, 95% CI (1.585–4.895), feeding non-diversified diet (AOR=1.9, 95% CI (1.036–3.497), and being unvaccinated (AOR: 2.0; 95%CI (1.013–4.197) were significantly associated with being underweight. Family size of ≥5 (AOR=4.4, CI (1.274–5.059), meal frequency of <3 times per a day (AOR=2.3, CI (1.037–5.024), and index birth interval of <24 months (AOR=2.2, CI (1.015–4.843) were significantly associated with wasting. Similarly, children aged≥24 months (AOR=2.8, CI (1.769–4.474), feeding non-diversified diet (AOR=1.8, CI (1.153–2.894), total duration of breast-feeding<12 months (AOR=4.0, CI (2.547–6.429), and mothers BMI below 18.5 (AOR=2.2, CI (1.328–3.718) were identified as a predictors of stunting. The study revealed significant levels of undernutrition, including underweight, wasting, and stunting, among children in the study area. Factors such as birth weight, dietary diversity score, and vaccine status were found to be strongly linked to underweight. Additionally, living in a large family, meal frequency, and birth interval were significantly associated with wasting. The age of the child, duration of breastfeeding, dietary diversity score, and maternal BMI status were also significantly linked to stunting. To address this issue, the study recommends promoting healthier feeding practices, dietary diversification, optimal breastfeeding, complete vaccination, wider birth intervals, and improving maternal nutrition to reduce undernutrition among children aged 6–59 months in the area. Implementing these measures could significantly improve the health of children in the study area.
Introduction
Undernutrition arises from inadequate nutrient intake or absorption in the body and can present as acute undernutrition (wasting), chronic undernutrition (stunting), or a combination of both (underweight), along with deficiencies in essential micronutrients1. Undernutrition is the leading cause of mortality for nearly half of all under-five child deaths worldwide. It increases the chance of morbidity, puts children at risk of dying from common diseases, increases the severity of infections, and delays recovery2.
Globally, undernutrition contributes to nearly 3 million deaths annually, accounting for approximately 45% of all deaths in children under five years of age3. Despite efforts to reduce undernutrition, in 2022, globally 148.1 million, or 22.3% of children under the age of five were stunted and 45 million children under 5 (6.8%) were affected by wasting, of which 13.6 million (2.1%) were suffering from severe wasting4. Over the past two decades, undernutrition has emerged as a major child health concern in low-and-middle-income countries (LMICs) due to its strong association with child mortality5.
Childhood undernutrition is a prevalent issue in Africa, according to the 2023 Joint Child Malnutrition Estimates (JME) report. In 2022, 43% of all children under five affected by stunting lived in Africa, meaning that two out of five affected children are from this region. Additionally, more than one-quarter of all children under five affected by wasting also reside in Africa, and 22% of all children with severe wasting live there4. These conditions have both short-term and long-term consequences, impacting physical, intellectual, and emotional development, as well as increasing susceptibility to communicable and chronic diseases6.
Ethiopia, as a country in Sub-Saharan Africa, grapples with a high burden of malnutrition despite efforts to reduce hunger and undernutrition. The ongoing challenge of malnutrition in Ethiopia underscores the need for sustained public health interventions to address this pressing issue7. According to the Ethiopian Demographic and Health Survey (EDHS) 2016, approximately 10%, 24%, and 38% of children under five were found to be wasted, underweight, and stunted, respectively. In the southern region of Ethiopia, acute malnutrition affects 6% of children, while chronic malnutrition or stunting affects 39%8. To decline the high prevalence of under-five malnutrition; World Health Organization (WHO) is implementing a global nutrition-monitoring framework with six targets to be achieved by 20259.
According to previously conducted studies, various factors, including socio-demographic status, economic status, child and maternal health, feeding practices, and environmental conditions, have been identified as significant contributors to different forms of undernutrition among under-five children10–16.
While previous studies in Ethiopia have focused on specific forms of undernutrition in various regions, there remains a knowledge gap in understanding the overall prevalence and determinants of undernutrition, particularly in densely populated areas. Moreover, no research has been conducted on undernutrition among children under five in our study area, the Gedio zone. Although there are studies from other densely populated regions, these earlier investigations did not differentiate between the three forms of undernutrition; instead, they treated them collectively. In contrast, our study successfully identifies the specific factors associated with each form—underweight, wasting, and stunting. This distinction will enable us to pinpoint the contributing factors for each type and ultimately aid in reducing overall undernutrition among children. Therefore, this study aims to assess the prevalence and factors associated with underweight, wasting, and stunting among children in the Gedio zone of southern Ethiopia. The findings of this study are crucial for developing effective interventions and guiding policymakers and health program implementers in addressing childhood undernutrition.
Methods
Study design, setting and period
Study area and period
The study was conducted in in the Gedio zone, Southern Ethiopia from June 01 to June 30, 2021. Gedio zone is found in southern part of Ethiopia located 370 km away from the capital city of Ethiopia, Addis Ababa and 95 km from the capital of Southern Ethiopia region, Hawassa city. The zone has a total area covering 5,890 square km and contains 8 districts.
Accordiong to 2007 Census conducted by the Central Statistical Agency of Ethiopia reports this Zone has a total population of 847,434, of whom 424,742 are men and 422,692 women; with an area of 1210.89 square kilometers, Gedio has a population density of 699.84. While 107,781 or 12.72% are urban inhabitants, in addition to the 107,781 urban inhabitants, there are also 39 individuals in Gedio who are pastoralists. A total of 179,677 households were counted in this Zone, which results in an average of 4.72 persons to a household, and 172,782 housing units17. Concerning health facilities in the zone, there are 1 referral hospital, 3 district hospitals, 35 health centers, and 146 health posts18.
Study design and population
A community-based cross-sectional study design was employed among children aged 6–59 months in the study area. The source populations for this study were all mothers with children aged 6–59 months in the Gedio Zone, southern Ethiopia. The study populations consisted of mothers with children aged 6–59 months residing in the selected households during the study period.
Eligibility criteria
This study included children aged 6–59 months and their mothers, provided they had lived in the study area for at least six months. However, mothers were excluded if they were severely ill, pregnant, experiencing generalized edema, or unable to respond during data collection. Additionally, children aged 6–59 months who had generalized edema at the time of data collection were also excluded.
Sample size determination and sampling procedures
A single population proportion formula was applied in this study, assuming a 95% confidence level and a marginal error of 5%. This approach aimed to determine the prevalence of under-nutrition, which was found to be 48.5% based on data from a previous national-level study conducted in Ethiopia13.
where n=least sample size needed to conduct the study, Z=standard normal distribution with (Z=1.96), the confidence level of 95% and α=0.05, P=prevalence or the population proportion from the previous study (P=48.5%), d=is the tolerable margin of error for the study (0.05).
The minimum sample size needed for the study was 384, after adding, a 5% rate for non-respondents the sample size for the study was 403.
The sampling technique involved randomly selecting four out of the eight districts in the zone, each of which had three kebeles for administrative purposes. Population size, number of households, and total number of kebeles were obtained from each district’s administration office. Kebele and household lists were organized by house number for the selected districts. Following the rule of thumb, 30% of kebeles (1 kebele) from each district were selected. Subsequently, a fixed number of households were drawn from each kebele using a random sampling technique. After proportionally allocating the number of households in each kebele, the households were identified from the central place, particularly the kebele administrative offices. This process resulted in a total of 403 study participants, with 71, 148, 87, and 97 participants selected from Kochere district (Biloya kebele), Gedeb district (Halo hartume kebele), Dila zuria district (Tumticha kebele), and Chorso mazoria district (Kedida gubeta kebele) respectively.
Study variables
The study focused on undernutrition, specifically wasting, stunting, and underweight, as the dependent variables. Child-related factors, maternal & environmental health related factors, and socio-demographic factors were included in the study as the possible determinants of stunting, wasting, and underweight. Explanatory variables were classified using previously published articles10–16,19–21. The child-related factors includes, child’s gender, age of children, perceived birth weight, birth order number, duration of breastfeeding, colostrum feeding, exclusive breastfeeding, complementary feeding initiation, diet diversity score, child feeding frequency, immunization status, deworming status, dietary pattern, history of febrile illness, and diarrhea episodes. The maternal and environmental health related factors includes, Body Mass Index (BMI), Age of mother, antenatal care visits, family planning utilization, birth interval, iron folic acid supplementation, TT Vaccination drinking water source, Availability of toilet, and hand washing practice. The variables of socio-demographic factors includes, residence, education of mother, occupation of mother, education of father, occupation of father, family size, main source of family food, and wealth index.
Operational definition
Underweight: is a composite form of under-nutrition including elements of stunting and wasting and is defined by a weight-for-age <−2SD from the median of the WHO reference population1.
Wasting: is a form of acute under-nutrition, and expressed as weight-for-height/length<−2SD from the median of the WHO reference population1.
Stunting: is a form of chronic under-nutrition, and expressed as height/length-for-age<−2SD from the median of the WHO reference population1.
Diet diversity score: Sum of the number of individual food groups consumed over 24-hour period. Child diet diversity score is expressed as inadequate dietary diversity (when individual consumed<5of the 8 food groups including breast milk) and adequate dietary diversity (when the individual consumed≥5 of the 8 food groups)22.
Household wealth index: The wealth index is a composite measure of a household’s cumulative living standards. It is calculated using easily collectible data regarding a household’s ownership of selected assets. These assets include radios, televisions, non-mobile telephones, computers, electricity, refrigerators, tables, chairs, beds with cotton or spring mattresses, electric mitad, kerosene lamps or pressure lamps, watches, mobile telephones, bicycles, motorcycles or scooters, animal-drawn carts, cars or trucks, bajaj, bank accounts, cows or bulls, other cattle, horses, donkeys or mules, camels, goats, sheep, chickens or other poultry, and beehives. Additionally, housing characteristics such as the number of members per sleeping room and building materials (including main floor material, main roof material, and main wall material) are considered. Access to utilities and infrastructure is also taken into account, including the source of drinking water, type of toilet facility, type of cooking fuel, ownership of a house, and ownership of land along with the area of land in square meters.Using principal component analysis, the factor scores are categorized into poor, medium, and rich classifications23.
Data collection tools and procedures
Data were collected by face-to-face interviews using a pre-tested and structured questionnaires adapted from related literatures and Ethiopian demographic and health survey assessment questionnaires for determining factors of nutrition status among children under-five years in Ethiopia24–29. UNICEF SECA Electronic weight scale and portable stand meter with a sliding head plate were used to take anthropometric data. Eight health professionals were engaged in the data collection and four health workers who have above three-year experience in nutrition activity were enrolled to the supervision of daily data collection status. During data collection; face- to-face interviews on socio-economic data, child health, feeding practice, maternal health, and nutrition were conducted.
Anthropometrics data collection was made using length/height and weight measurements of the children and their mothers. Children over two years old were weighed using a UNICEF standard weight scale, with bulky clothing and shoes removed. Height was measured using a UNICEF standard wooden portable stand meter, with the sliding head plate, and participants’ shoes were also removed during the measurement30. For those children below two years, weight measurement was done by hanging the weight scale and length measurement in the horizontal position. The age of children was identified using vaccine cards and a local calendar system was used for those who have no vaccination cards.
Data quality control
The instrument was translated from English to local and then back to English by experts in the field who were unaware of the original English version. This was done to ensure reliable responses to the questions and maintain the integrity of the instrument’s meaning. Preceding the data collection, one-day training was given for data collectors and supervisors on techniques of sample identification and data collection. Prior to the actual data collection, 5% of participants were pre-tested to verify the effectiveness of the tool, with necessary corrections made accordingly. The chief investigator and supervisor inspected all questionnaires on-site for completeness and consistency of information collected, taking immediate action as needed.
Throughout the data collection period, onsite supervision was carried out daily by the supervisor and principal investigator. At the end of each day, they reviewed and crosschecked the questionnaires to ensure completeness, accuracy, and consistency, making any necessary corrections.
To maintain data integrity, the data collector managed the setup for providing and retrieving questionnaires from study participants. Structured interviews were conducted in a confidential and private setting to minimize bias. Simple frequencies and cross-tabulation were used to address missing values and outliers, cross-referencing with hard copies of the collected data.
Data processing and analysis
The data were coded, cleaned, edited and entered into Epi data version 3.1 to minimize logical errors and design skipping patterns. Then, the data were exported to SPSS software for analysis and finally data analyses was conducted with SPSS version 20. Descriptive statistics such as frequency, percentage, mean values, and standard deviations was computed for respondent characteristics and other measured study variables.
To evaluate the nutritional status of children, Z-scores for Weight-for-Height/Length (WH/LZ), Height-for-Age (HAZ), and Weight-for-Age (WAZ) were calculated using WHO Anthro version 3.2.2.1 software. Additionally, the mother’s nutritional status was assessed by determining her body mass index (BMI). Level of statistical significance was declared at p-value<0.05. Variables that have a p-value of <0.25 after binary logistic regression were fitted into a multivariable logistic regression model to identify the independent contribution of each variable. If the P- value is <0.05 for a given variable after multivariable analysis, the variable is significant, it has an association with the outcome variable, and the degree of association between variables were measured using odds ratio.
Results
Socio-demographic and economic characteristics of study participants
Out of the intended 403 study participants, a complete response was obtained from 386 (96%) participants. More than half (59.1%) of the children fell into the 24–59 months age category, with a mean age of 27.11 months and a standard deviation of +14.7 for both sexes. Approximately 40.2% of the mothers were aged between 20 and 34 years, with a mean maternal age of 24.7 and a standard deviation of +3.3 years. The majority (94.6%) of women were married, and 96.5% of households were headed by a male. Two-thirds (62.7%) of respondents had a family size greater than five, and over one-third (37.6%) of households were classified as having a poor wealth index (see Table 1).
Table 1
Variable | Category | Frequency (%) |
---|---|---|
Age of child | 6–23 months | 158 (40.9) |
24–59 months | 228 (59.1) | |
Age of the mother | <20 years | 166 (43.0) |
20–34 years | 155 (40.2) | |
>34 years | 65 (16.8) | |
Sex of child | Male | 201 (51.7 |
Female | 185 (48.3) | |
Residence | Urban | 60 (15.5) |
Rural | 326 (84.5) | |
Education status of mother | No formal education | 155 (40.2) |
Primary level | 167 (43.0) | |
Secondary & above | 65 (16.8) | |
Education status of Father | No formal education | 95 (24.6) |
Primary level | 210 (54.4 | |
Secondary & above | 81 (21.0) | |
Occupation of mother | Housewife | 262 (67.8) |
Employee | 76 (19.8) | |
Private work | 48 (12.4) | |
Family size | <5 family | 144 (37.3) |
≥5 family | 242 (62.7) | |
No of <5 children | 1-child | 230 (59.6) |
≥2 children | 156 (40.4) | |
The main source of family food | Own production | 251 (65.0) |
Purchase | 110 (28.5) | |
Other | 25 (6.5) | |
Household Wealth Index | Poor | 145 (37.6) |
Medium | 139 (36.0) | |
Rich | 102 (26.4) |
Child health and caring practices
Of the total participants in the study, around one-third (27.2%) of children were delivered in health facilities, and over two-thirds were not exclusively breastfed. Approximately 63.5% of children had evidence of being fully vaccinated. Diarrheal disease, followed by acute respiratory infections (ARIs), was the most frequent child health problem in the study area, affecting 17% and 15.4% of children in the past two weeks (Table 2).
Table 2
Variables | Category | Frequency (%) |
---|---|---|
Place of birth | Health facility | 105 (27.2) |
Home | 281 (72.8) | |
Perceived birth weight | Small | 143 (37.0) |
Average | 196 (50.8) | |
Bigger than average | 47 (12.2) | |
History of colostrum feeding | Yes | 160 (41.5) |
No | 226 (58.5) | |
Exclusive breastfed | Yes | 125 (32.4) |
No | 261 (67.6) | |
Duration of breastfeeding | <12 months | 161 (41.7) |
≥12 months | 225 (58.3) | |
The age of complementary feeding started | At 6 month | 146 (37.8) |
<6 month | 55 (14.3) | |
>6 month | 185 (47.9) | |
Diet diversity score | <5 food groups | 231 (59.8) |
≥5 food groups | 155 (40.2) | |
Meal frequency | <3 meals per day | 120 (31.1) |
≥3 meals per day | 266 (68.9) | |
Method of child feeding | Bottle | 238 (61.7) |
Cup and/or spoon | 67 (17.3) | |
Hand | 81 (21.0) | |
Vaccination status | Not started | 53 (13.7) |
Up to date | 88 (22.8) | |
Completed | 245 (63.5) | |
Vitamin-A supplemented in the last 6 months | Yes | 254 (65.8) |
No | 132 (34.2) | |
Deworming given in the last 6 months | Yes | 208 (53.9) |
No | 178 (46.2) | |
History of acute respiratory illness in the last two weeks | Yes | 59 (15.3) |
No | 327 (84.7) | |
History of diarrheal disease in the last two weeks | Yes | 66 (17.1) |
No | 320 (82.9) |
Dietary diversity score
Out of the total children, 155 (40.2%) had a diverse diet (consumed>5 out of the 8 food groups) in the previous 24 h, while 231 (59.8%) had a limited diet (consumed<5 out of the 8 food groups). The most commonly consumed food groups among the children were grains, roots, and tubers (92.5%), including the locally prevalent ‘Enset’, as well as dairy products (54.9%), followed by flesh foods such as meat (46%). Approximately one-third of the children (32.6%) were reported to be breastfeeding in the previous 24 h. Conversely, the least consumed food groups were Vitamin-A rich fruits and vegetables (22.6%) and other fruits and vegetables (18.9%) (Fig. 1).
Maternal health and environmental factors
In terms of maternal health and environmental factors, 58.3% of the mothers had a birth interval of >24 months for the index pregnancy, and 78.2% had received antenatal care (ANC) follow-up. Additionally, 59.3% of the mothers had a normal BMI. The majority of sampled families (60.9%) used an unsafe water source, and only 32% had access to improved latrines (Table 3).
Table 3
Variables | Category | Frequency (%) |
---|---|---|
The birth interval of index pregnancy* | <24 months | 89 (23.1) |
≥24 months | 225 (58.3) | |
History of ANC during the index pregnancy | Yes | 302 (78.2) |
No | 84 (21.8) | |
TT-vaccination status | Unvaccinated | 167 (43.3) |
TT1 | 77 (19.9) | |
TT2 plus | 142 (36.8) | |
Folic acid intake during index pregnancy | Yes | 209 (54.1) |
No | 177 (45.9) | |
Maternal BMI status | Normal weight | 229 (59.3) |
Underweight | 109 (28.2) | |
Overweight | 48 (12.4) | |
Ever used family planning | Yes | 244 (63.2) |
No | 142 (36.8) | |
Hand washing practice during food preparation | Yes | 156 (40.5) |
No | 230 (60.5) | |
Source of drinking water** | Safe | 151 (39.1) |
Unsafe | 235 (60.9) | |
Availability of Improved latrine*** | Yes | 114 (29.5) |
No | 272 (70.5) | |
Ever heard of safe nutrition information | Yes | 312 (80.8) |
No | 74 (19.2) |
*Respondent’s with 1st birth was not included.
**Safe source includes tap water, public tap, and protected well and the unsafe source includes unprotected spring, well, and river.
***Improved latrine includes any non-shared toilet of: flush/pour flush toilets, septic tanks, and pit latrines; ventilated improved pit latrines; pit latrines with slabs.
Magnitude of undernutrition
The study participants showed a prevalence of under-nutrition, with 19.7% (95% CI 16-24%) classified as underweight, 10% (95% CI 7-13%) as wasted, and 49% (95% CI 44-54%) as stunted. Among the children, severe underweight (WAZ<−3SD), severe wasting (WHZ<−3SD), and severe stunting (HAZ<−3SD) were prevalent at rates of 9.1%, 5.7%, and 29.5%, respectively. Furthermore, 4.6% of children exhibited both wasting and stunting simultaneously (Fig. 2).
Magnitude of Undernutrition in relation to age and sex category of children
The study also examined the prevalence of undernutrition in different age and sex categories. Male children aged 6–59 months exhibited a higher prevalence of underweight and stunting, with rates of 10.6% and 26.4%, respectively. In contrast, female children in the same age group showed a greater prevalence of wasting at 5.4%. When considering age groups, children aged 24–59 months had higher rates of all three forms of undernutrition compared to those aged 6–23 months, with prevalence rates of 13.5% for underweight, 6.2% for wasting, and 33.4% for stunting (Table 4).
Table 4
Variables | Category | Underweight (%) | Wasting (%) | Stunting (%) |
---|---|---|---|---|
Sex | Male | 10.6 | 4.7 | 26.4 |
Female | 9.1 | 5.4 | 22.5 | |
Age of child | 6–23 months | 6.2 | 3.9 | 15.5 |
24–59 months | 13.5 | 6.2 | 33.4 |
Determinants of undernutrition among children aged 6–59 months
The findings of this study indicated that children who were perceived to have had a small weight at birth were approximately three times more likely (AOR=2.8, 95% CI (1.585–4.895)) to experience underweight compared to those with an average weight at birth. Additionally, children who consumed an inadequate diversified diet had twice the risk (AOR=1.9, 95% CI (1.036–3.497)) of developing underweight compared to those who consumed a sufficiently diversified diet. Unvaccinated children were also found to be twice as likely (AOR=2.0, CI (1.024–4.235)) to be underweight compared to children who completed their vaccinations (Table 5).
Table 5
Variables | Underweight | COR ( 95% CI) | AOR ( 95% CI) | P-value | |
---|---|---|---|---|---|
Yes (N/%) | No (N/%) | ||||
Age of mother | |||||
<20 years | 41 (53.9) | 125 (40.3) | 1.8 (1.022-3.14)* | 1.5 (0.84-2.78) | |
20-34 years | 24 (31.6) | 131 (42.3) | 1 | 1 | |
>34 years | 11 (14.5) | 54 (17.4) | 1.1 (0.509-2.43) | 1.(0.48-2.47) | |
Perceived birthweight | |||||
Small | 47 (61.8) | 96 (31.0) | 3.3 (1.940-5.79)* | 2.8 (1.59-4.89)** | 0.001 |
Average | 25 (32.9) | 171 (55.2) | 1 | 1 | |
Bigger than average | 4 (5.3) | 43 (13.9) | 0.6 (0.210-1.93) | 0.7 (0.22-2.12) | |
Diet diversity score | |||||
<5 food groups | 57 (75.0) | 174 (56.1) | 2.3 (1.332-4.13)* | 1.9 (1.04-3.49)** | 0.024 |
>5 food groups | 19 (25.0) | 136 (43.9) | 1 | 1 | |
Vaccination status | |||||
Not started | 18 (23.7) | 35 (11.3) | 2.4 (1.253-4.66)* | 2.0 (1.03-4.24)** | |
Up to date | 15 (19.7) | 73 (23.5) | 0.9 (0.506-1.84) | 0.9 (0.46-1.82) | 0.037 |
Completed | 43 (56.6) | 202 (65.2) | 1 | 1 | |
Improved Latrine | |||||
Yes | 33 (43.4) | 81 (26.1) | 1 | 1 | |
No | 43 (56.6) | 229 (73.9) | 0.46 (0.27-0.77)* | 0.6 (0.34-1.05) |
In terms of wasting, children living in families with more than four members were at a significantly higher risk of developing wasting, with a four-fold increase compared to those living in smaller families (AOR=4.4, CI (1.274–5.059)). Children who had a meal frequency of less than three times per day were also at a higher risk of developing wasting, with a 2.3-fold increase compared to those who had a higher meal frequency (AOR=2.3, CI (1.037–5.024)). Children born within less than 24 months of the index birth interval were also at an increased risk of developing wasting, with a 2.2-fold increase compared to their counterparts (AOR=2.2, CI (1.015–4.843)) (Table 6).
Table 6
Variables | Wasting | COR (95% CI ) | AOR ( 95% CI) | P-values | |
---|---|---|---|---|---|
Yes (N/%) | No (N/%) | ||||
Education status of the father | |||||
Uneducated | 12 (30.8) | 83 (23.9) | 3.7 (1.02-13.83)* | 3.5 (0.72-16.96) | |
Primary level | 24 (61.5) | 186 (53.6) | 3.3 (0.98-11.46) | 3.7 (0.82-17.25) | |
Secondary & above | 3 (7.7) | 78 (22.5) | 1 | 1 | |
Family size | 0.019 | ||||
<5 family | 4 (10.3) | 140 (40.3) | 1 | 1 | |
>5 family | 35 (89.7) | 207 (59.7) | 2.2 (1.12-4.25)* | 4.4 (1.27-5.06)** | |
Vaccination status | |||||
Not started | 10 (25.6) | 43 (12.4) | 2.7 (1.20-6.36)* | 1.3 (0.48-3.74) | |
Up to date | 10 (25.6) | 78 (22.5) | 1.5 (0.68-3.42) | 1.5 (0.61-3.82) | |
Completed | 19 (48.7) | 226 (65.1) | 1 | 1 | |
Meal frequency | |||||
<3 meals/day | 21 (53.8) | 99 (28.5) | 2.9 (1.49-5.72)* | 2.3 (1.04-5.02)** | 0.040 |
>3 meals/day | 18 (46.2) | 248 (71.5) | 1 | 1 | |
Birth Interval of the index pregnancy | |||||
<24 months | 15 (46.9) | 74 (26.2) | 2.48 (1.18-5.22)* | 2.2 (1.02-4.84)** | 0.046 |
>24 months | 17 (53.1) | 208 (73.8) | 1 | 1 |
Regarding stunting, children over the age of 24 months were at a significantly higher risk of being stunted, with a 2.8-fold increase compared to those aged 6–23 months (AOR=2.8, CI (1.769–4.474)). Children who had an inadequate diversified diet had an 80% increased odds of developing stunting compared to those who had an adequate diversified diet (AOR=1.8, CI (1.153–2.894)). Children who were breastfed for less than 12 months were also at a significantly higher risk of developing stunting, with a four-fold increase compared to those who were breastfed for a longer duration (AOR=4.0, CI (2.547–6.429)). Additionally, stunting was found to be twice as likely in children whose mothers had a BMI in the underweight range compared to those with normal BMI range (AOR=2.2, CI (1.328–3.718)) (Table 7).
Table 7
Variables | Stunting | COR (95% CI) | AOR ( 95% CI) | P-value | |
---|---|---|---|---|---|
Yes (No/%) | No (N/%) | ||||
Age of child | |||||
6–23 months | 60 (31.7) | 98 (49.7) | 1 | 1 | |
24–59 months | 129 (68.3) | 99 (50.3) | 2.13 (1.40-3.22)* | 2.8 (1.769-4.47)* | 0.001 |
Diet diversity score | |||||
<5 food groups | 124 (65.6) | 107 (54.3) | 1.6 (1.06-2.42)* | 1.8 (1.153-2.89)** | 0.010 |
>5 food groups | 65 (34.4) | 90 (45.7) | 1 | 1 | |
Duration of breastfeeding | 0.000 | ||||
<12 months | 107 (56.6) | 54 (27.4) | 3.45 (2.26-5.28)* | 4.0 (2.55-6.43)** | |
>12 months | 82 (43.4) | 143 (72.6) | 1 | 1 | |
Ever used family planning | |||||
Yes | 109 (57.7) | 135 (68.5) | 1 | 1 | |
No | 80 (42.3) | 62 (31.5) | 1.3 (1.05-2.43)* | 1.4 (0.87-2.17) | |
Maternal BMI | |||||
Normal weight | 100 (52.9) | 129 (65.5) | 1 | 1 | |
Underweight | 71 (37.6) | 38 (19.3) | 2.4 (1.50-3.86)* | 2.2 (1.33-3.72)** | 0.002 |
Overweight | 18 (9.5) | 30 (15.2) | 0.77 (0.41-1.46) | 0.8 (0.38-1.54) |
NB: *AOR is significant at a P-value of <0.05, **COR is significant at a P-value of <0.25.
Discussion
This study found that underweight, wasting, and stunting were prevalent at rates of 19.7% (95% CI 16-24%), 10% (95% CI 7-13%), and 49% (95% CI 44-54%), respectively. When compared to the national rates reported in the Ethiopian DHS 2016, the study identified a slightly lower prevalence of underweight (19.7%), a similar prevalence of wasting (10%), and a higher prevalence of stunting (49%)31.The observed disparities could be attributed to differences in sampling methods and sample sizes.
The prevalence of stunting (49%) in the study area was notably higher than the regional average for Southern Ethiopia (39%)24. However, this finding is consistent with the prevalence of wasting (47.6%) reported in the Bule Hora district of Southern Ethiopia, which may reflect similar socio-economic conditions and age groups of the study population10. The prevalence of underweight, wasting, and stunting in the current study was lower, similar, and higher, respectively, compared to sub-Saharan Africa’s average (25%, 10%, and 39%, respectively). However, the prevalence of stunting was consistent with a previous study in East Africa (48%)32, suggesting that differences in socio-economic, cultural, sampling, and methodological factors may explain the variations.
According to this study, the three common forms of under-nutrition (stunting, wasting, and underweight) were significantly associated with different factors that varied by the type of under-nutrition. Underweight was associated with birth weight, dietary feeding, and vaccine status. Wasting was associated with family size, meal frequency, and birth interval. Stunting was associated with the age of the child, diet diversity score, duration of breastfeeding, and the mother’s BMI status.
The analysis of this study revealed that low perceived birth weight was a risk factor for under-nutrition among children, as those with low birth weight were more likely to be underweight. This finding is consistent with studies conducted in Ghana11 and Indonesia33, which reported a high risk of underweight among children with low birth weight. This suggests that low birth weight children require extra nutrition and care to achieve normal weight compared to those with normal birth weight.
Additionally, the study revealed that insufficient dietary diversity is a significant risk factor for under-nutrition, specifically underweight and stunting. Children who consume less than five of the eight major food groups are more likely to develop these conditions compared to those who consume five or more food groups. This finding is consistent with previous studies conducted in Ethiopia, Tanzania, and India12,34,35. The lack of dietary diversity can lead to macro and micro-nutrient deficiencies, resulting in under-nutrition, likely due to poor access to diverse foods and unequal food distribution within households10,20,21.
Furthermore, the study findings indicate that a child’s vaccination status is a significant predictor of being underweight. This observation is consistent with previous studies conducted in various regions, including northwest Ethiopia25, Ethiopian Somalia region27, and rural Bangladesh29. Unvaccinated children are more susceptible to vaccine-preventable diseases such as diarrhea and respiratory tract infections, which can cause nutrient depletion in the body and eventually lead to malnutrition.
The study’s results indicate that a larger family size is associated with an increased risk of wasting. Specifically, living with five or more family members was identified as a significant predictor of wasting. This observation aligns with several prior studies conducted in different regions, including northwest Ethiopia25, Ethiopian Somalia region27, Sudan36, and Pakistan37. The reason for this association may be that as the size of a family grows, the likelihood of implementing appropriate feeding practices for children and ensuring access to a nutritious diet decreases.
Furthermore, the study found that children who consumed less than three meals per day were at a higher risk of developing wasting. This discovery is consistent with previous research conducted in west Gojam, Ethiopia26. Inadequate meal consumption can hinder a child from receiving the necessary daily energy intake for proper nourishment. Additionally, the study revealed that children with birth intervals of less than 24 months were also at a higher risk of developing wasting. This finding is in line with research conducted in India35, and aligns with WHO’s recommendations for child feeding9. This is because a child with a short birth interval may not receive the recommended dietary intake due to competition with the preceding child.
Moreover, the latest research indicates that the likelihood of stunting increases as a child grows older, which is consistent with previous studies in Ethiopia24 and Kenya21. Children aged 12–23 months and older were found to have the highest risk of stunting. Similarly, a study conducted on trends of stunting from 1990 to 2020 in developing countries also showed similar findings38.
The study found that the duration of breastfeeding played a significant role in predicting stunting, as children breastfed for less than 12 months exhibited a notable association with stunting. This finding is in line with evidence from a study conducted in Ethiopia28 and aligns with WHO recommendations for child feeding9. Furthermore, the research indicated that children born to underweight mothers had an elevated risk of stunting. Previous studies have also demonstrated a higher likelihood of stunting among mothers with a low BMI6,28), potentially attributed to the long-term nutritional status of mothers before pregnancy impacting the early growth and development of their children, thereby contributing to the risk of stunting.
Limitations of the study
It is difficult to establish a cause-effect relationship between the predictors and outcome variable for it is a cross-sectional study design. Recall bias is another limitation that might affect the accuracy of the data.
Conclusion
The present study’s findings reveal a concerning prevalence of under-nutrition, including underweight, wasting, and stunting, within the study area. The research has identified several key factors associated with under-nutrition among children in this context. Specifically, birth weight, dietary feeding practices, and vaccine status were found to be correlated with underweight, while family size, meal frequency, and birth interval were linked to wasting. Additionally, stunting was significantly associated with the child’s age, diet diversity score, duration of breastfeeding, and maternal body mass index.
In light of these findings, it is evident that a multi-faceted approach is needed to address the issue of under-nutrition among children aged 6–59 months in the study area. The study recommends promoting healthier child feeding practices, encouraging optimal dietary diversification and meal frequency, prioritizing optimal breastfeeding, ensuring complete vaccination of children, advocating for wider birth intervals, and improving maternal nutritional status as crucial steps to mitigate under-nutrition among this vulnerable population.
By implementing these recommended measures, there is potential to make a significant impact on reducing the prevalence of under-nutrition and improving the overall health and well-being of children in the study area.
Acknowledgements
Authors would like to thank the Gedio zone health office and all selected study area health offices for their cooperation and for providing relevant information. Authors also would also like to thank all the staff of our field office for their incredible support throughout the study. Finally, authors thanked data collectors, supervisor, data clerks, and head of health institutions.
Abbreviations
ANC | Antenatal Care |
AOR | Adjusted Odds Ratio |
ARI | Acute Respiratory Infection |
BMI | Body Mass Index |
COR | Crude Odds Ratio |
CSA | Central Statistical Agency |
EDHS | Ethiopia Demographic and Health Survey |
NNP | National Nutrition Program |
SD | Standard Deviations |
TT | Tetanus Toxoid |
UNICEF | United Nations International Children’s Fund |
WFA | Weight-For-Age |
WFH | Weight-For-Height |
WFL | Weight-For- Length |
WHO | World Health Organization |
Author contributions
Conceptualization: M.Y., T.Z., T.D., H.M., T.W., M.H., N.K. Data curation: T.Z., T.D., H.M., T.W. Formal Analysis: T.Z., H.M., M.H., N.K. Investigation: M.Y., T.Z., T.D., H.M., T.W. Methodology: M.Y., T.D., H.M., M.H., N.K. Project Administration: T.Z., T.D., H.M., T.W. Resources: M.Y., T.Z., T.D., H.M., T.W., M.H., N.K. Software: M.Y., T.Z., T.D., N.K. Supervision: M.Y., T.Z., T.W., M.H., N.K. Validation: T.Z., T.D., H.M., T.W., N.K. Visualization: M.Y., T.D., T.W., M.H., N.K. Writing-original draft: M.Y. Writing-review and editing: T.Z., M.Y., T.D., H.M., T.W., M.H., N.K.
Data availability
The data used to support the findings of this study are available from the corresponding author upon request.
Declarations
All information used in this study was collected with the consent of all participants of the study and all the authors have prepared the manuscript and have agreed to publish it in this journal.
The authors declare no competing interests.
In order to conduct this research, the authors tried to address the Declaration of Helsinki Ethical principles for medical research. First, ethical clearance was obtained from Rift Valley University, Hawassa campus Institutional Review Board (IRB) with IRB protocol number of RVU-IRB-068/2021. A formal letter for permission and support was gained from the Gedio zone and selected district health offices and submitted to respective kebele offices and health posts in which the study was conducted. Written informed consent was obtained from all participant to insure willingness after brief clarification of the study’s purpose. Information was gathered anonymously by assuring confidentiality during the study period.
Footnotes
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References
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