Determinants of Malnutrition in Children Under Five Years at Soroti Regional Referral Hospital: A Comprehensive Analysis
Acen Brenda
Faculty of Clinical Medicine and Dentistry Kampala International University Western Campus Uganda.
ABSTRACT
This cross-sectional study aimed to examine the factors associated with malnutrition among children under five years attending Soroti Regional Referral Hospital (SRRH). Conducted over six months, anthropometric measurements and caregiver interviews were collected from 204 children aged 3 to 59 months. Z-scores for height-for-age (H/A) and weight-for-height (W/H) indices were employed for analysis, supplemented by qualitative insights from two focus group discussions. Statistical analysis using Epi Data version 3.1, EPI-INFO version 7.0, and SPSS version 25.0 unveiled striking figures: global stunting due to chronic malnutrition stood at 55.4%, with severe stunting reaching 25.8%. Age groups 6-12 months and 13-24 months exhibited higher prevalence of acute malnutrition. Malaria and male gender emerged as significant predictors of acute and chronic malnutrition, respectively. Logistic regression highlighted the age group 3-24 months as a significant risk factor for acute malnutrition, while recent deworming served as a protective factor. This study underscores the alarming prevalence of childhood malnutrition at SRRH, delineating crucial predictors and age-related vulnerabilities demanding targeted interventions.
Keywords: Acute malnutrition, Children under five years, Stunting, Chronic malnutrition, Malaria.
INTRODUCTION
Nearly half of all deaths in children under 5 are attributable to undernutrition. Undernutrition puts children at greater risk of dying from common infections, increases the frequency and severity of such infections, and delays recovery [1-3]. In 2019, 21.3 percent, or more than one in five children under age 5 worldwide had stunted growth. That said, overall trends are positive. Between 2000 and 2019, stunting prevalence globally declined from 32.4 percent to 21.3 percent, and the number of children affected fell from 199.5 million to 144.0 million [4]. In the African region, there has been some progress towards achieving global nutrition targets [5, 6]. The global targets for under-five overweight and infant exclusive breastfeeding each have 20 countries on course to meet them, under-five wasting has 12 countries on the course, while under-five stunting has eight countries on course. However, not a single country in the region is on course to meet the targets for anemia in women of reproductive age, low birth weight, male diabetes, female diabetes, male obesity, and female obesity. 35 countries in the region have insufficient data to comprehensively assess their progress towards these global targets [7]. In 2019, nearly two out of five stunted children lived in South Asia while another two out of five lived in sub-Saharan Africa [1, 7]. Malnutrition contributes to high levels of stunting and threatens the lives and potential of millions of children in Uganda [8]. Malnutrition threatens to destroy a generation of children in Uganda. More than one-third of all young children – 2.4 million – are stunted. The damage caused by stunting is irreversible. Half of children under five and one-quarter of child-bearing-age women are anaemic. The problem persists despite a drop in stunting and anaemia rates in recent years [1]. Anemia in children and women of child-bearing age is one of the aftermaths of malnutrition [9-12]. Other key contributors to malnutrion are malaria [13-15], intestinal disturbances due to poor hygiene [16-18] and other underlying ailments like HIV/AIDs [19-21]. Malnutrition in children is among the major contributors of morbidity and mortality especially among those aged five years and below. Malnutrition has been implicated in about 45% of deaths caused by other conditions such as malaria, pneumonia, and diarrhoea in this age group [1]. Malnutrition is a wholly preventable African, and other low- and middle-income countries’ problem [22]. Despite the abundance of natural resources that could prevent undernutrition in Africa, this monster still persists. Plants and plant-based materials like fruits and vegetables are common diets that can palliate against undernutrition. This is because plants and plant-based resources especially fruits and vegetables have ample quantities of nutrients inherent in them. Adequate intake of these natural resources could mitigate against undernutrition in Africa [23-25]. Malnutrition contributes to high levels of stunting and threatens the lives and potential of millions of children in Uganda, threatening to destroy a generation of children in Uganda. More than one-third of all young children – 2.4 million – are stunted with the damage caused by stunting being irreversible [1]. Due to the very fast rate of changing trends of factors that are associated with malnutrition of children, there is a need for constant updates of scientific information about the topic through regular empirical research. However even with the changing dynamics, there is very limited information on the evolved trends about the topic and Soroti Regional Referral Hospital is one of the spots without up-to-date information on the same, hence the need for this study. This study was designed to assess the factors associated with malnutrition among children under five years attending Soroti Regional Referral Hospital.
METHODOLOGY
Study design
The study used a cross-sectional descriptive design where both qualitative and quantitative approaches were applied to obtain data that suited the objectives of the study.
Area of Study
The study was conducted at Soroti Regional Referral Hospital (SRRH) – commonly known as Soroti Hospital located in the city of Soroti, in Soroti District, in Eastern Uganda. SRRH is a public hospital, funded by the Uganda Ministry of Health and general care in the hospital is. It is the referral hospital for the districts of Amuria, Bukedea, Kaberamaido, Kapelebyong, Katakwi, Kumi, Ngora, Serere and Soroti. The coordinates of Soroti Regional Referral Hospital are: 1°42’58.0″N, 33°36’47.0″ E (Latitude: 1.716111; Longitude: 33.613056)
Study population
The study subjects were children under 5 years (3 – 59 months) attending SRRH in the months of November 2020 to March 2021. Their caretakers were interviewed for associated data needed for the study.
Inclusion criteria
All children aged 3 – 59 months (under 5 yrs) attending the outpatient department of SRRH between November 2020 to March 2021.
Exclusion criteria
All children under-fives attending SRRH OPD whose caregivers denied consent.
- All children under-fives who were admitted to wards of SRRH.
- All under-fives attending SRRH were perceived to be very sick at the time of data collection.
Sample size determination
The prevalence of malnutrition in children under 5 years in Eastern Uganda is estimated at 5.6% by the latest Uganda demographic and health survey of 2017 (Uganda Bureau of Statistics [8]). Therefore, the sample size necessary to reach the study objective was estimated on the assumption of this estimated malnutrition prevalence of 5.6% in the region.
Therefore, using n= Z2 P (100-P)/d2
n=required sample size
Z=1.96 (at 95% confidence interval)
P=Prevalence of self-medication (5.8%)
d2 =Margin of error (5%)
n = 1.962 x 5.6 (100 – 5.6)/52 = 84
After adding non-response correction of 20%; n= [42+ (20% of 86)] = 103
However, with the availability of more subjects that met the study criteria, 186 subjects were recruited for the study
Sampling procedures
The study populations comprised children aged 3-59 months and their caretakers. Consecutive sampling technique was used whereby study subjects were recruited as they met the inclusion criteria.
Data Collection Methods
The study relied chiefly on the anthropometric measurements of the children such as weight for height, height for age, mid-upper arm circumference (MUAC) and weight for age that was recorded in a specially tailored collection list.
Anthropometric measurements
Anthropometric measurements of a total of 55 eligible children including weight and height were taken. Weight was recorded in kilograms (kg) to the nearest 0.1kg. Children were weighed using electronic weighing scales and those who were unable to stand, had their weights obtained from the difference between the weights of the mother/caretaker as she/he held the child and the weight of the mother/caretaker alone. Heights/lengths measurements were carried out using measuring boards (stadiometers) and were recorded in centimeters (cm) to the nearest 0.1 cm. Children aged more than 24 months (more or equal to 85cm) heights were measured while standing, while those less than 24 months or less than 85cm, had theirs, lengths measured while lying down.
Clinical evaluation
Clinical evaluations of the malnourished children were undertaken to check for the presence of oedema. Oedema was recorded as present when a shallow imprint persisted on both feet when pressure was removed and absent when there was no pitting of the dorsum of both feet. Clinical evaluation was supported by information obtained from subject’s file records and registry files on admissions.
Qualitative data collection
Two focus group discussions were conducted. The FGDs consisted of 8 people each and comprised mothers, fathers and other caretakers who had not participated in the questionnaire interview. Each discussion took about one hour. The focus group discussions were recorded using a voice recording application on a phone. The FGDs where intended to obtain information on causes of protein energy malnutrition, and utilization of nutrition and health services offered by any known service provider either government or Non-government organizations (NGOs).
Data analysis
Quantitative data were checked for completeness, sorted, coded and entered into the computer using Epidata version 3.1. The data were analyzed using EPI INFO version 7.0 and SPSS version 25. Anthropometric measurement outcomes were defined in terms of wasting and stunting using weight for height and height for age indices respectively expressed in standard deviation (z-scores). Univariate and bivariate analyses were done to determine factors that were significantly associated with wasting and stunting. The chi-square test was used to ascertain the statistical significance of the variables at p-value <0.05. All variables with a p-value ≤ 0.2 were entered into a logistic regression to determine the risk factors for protein-energy malnutrition. Qualitative data were analyzed manually. Content analysis was based on condensation and abstraction of main themes focusing on causes of protein energy malnutrition.
Quality control
The designed questionnaire was pre-tested at KIU – Teaching Hospital and during data collection, completed questionnaires were checked for completeness. The weighing scales and measuring boards (stadiometers) were standardized to the nearest 0.1kg and 0.1cm respectively. The weighing scale was recalibrated to zero after every child was weighed. Taking of the various anthropometric measurements was done by the same person, at the same time of day using the same instruments that had been properly calibrated. Classification of malnutrition cases was done according to the prevailing WHO classifications with values being confirmed by checking in the relevant growth charts.
Ethical considerations
Approval to conduct this study was obtained from KIU – Western campus Faculty of Clinical Medicine & Dentistry and Hospital administration of SRRH. Participants’ caregivers participated upon informed consent and they were allowed the freedom to refuse to take part at any time. No services due to them were denied or delayed from their participation, or the lack of it thereof, in this study.
RESULTS
Table 1: Socio-demographic characteristics of caretakers
Characteristic | Category | Frequency (N=186) | Percentage (%) |
Age (in years) | <20 | 13 | 7.0 |
20 – 30 | 94 | 50.5 | |
31 – 40 | 55 | 29.6 | |
>40 | 24 | 12.9 | |
Sex | Female | 180 | 96.8 |
Male | 06 | 3.2 | |
Marital status | Married | 141 | 75.8 |
Not married | 45 | 24.2 | |
Level of education | None | 38 | 20.4 |
Primary | 124 | 66.7 | |
Secondary and above | 24 | 12.9 | |
Source of income | Peasant farmers | 121 | 65.1 |
Housewives | 35 | 18.8 | |
Others | 30 | 16.1 |
The majority of the children caretakers at SRRH were aged between 20 – 30 years (50.5%), married (75.8%), females (96.8%) and had a primary level of education (66.7%). The majority of their source of income is farming at a peasantry level (65.1%) (Table 1).
Table 2: Demographic characteristics of children under 5 years
Characteristic | Category | Frequency (N=186) | Percentage (%) |
Age (months) | 3 – 5 | 09 | 5.3 |
6 – 12 | 78 | 41.6 | |
13 – 24 | 41 | 22.0 | |
25 – 36 | 33 | 17.7 | |
37 – 48 | 19 | 10.2 | |
49 – 59 | 06 | 3.2 | |
Sex | Female | 97 | 52.1 |
Male | 89 | 47.9 |
Majority of the children attending SRRH outpatient department were female (52.1%) aged between 6 – 12 months (41.6%). (Table 2).
Table 3: Prevalence of acute and chronic malnutrition by age groups
Population
Age group (in months) |
Frequency | Acute malnutrition (W/H) | Chronic malnutrition (H/A) | ||||
Severe
n (%) |
Moderate
n (%) |
Global
n (%) |
Severe
n (%) |
Moderate
n (%) |
Global
n (%) |
||
3 – 5 | 09 | – | – | 1 (11.1) | 2 (22.2) | 3 (33.33) | 3 (33.33) |
6 – 12 | 78 | 1 (1.3) | 2 (2.7) | 3 (3.8) | 7 (9.0) | 20 (25.6) | 45 (57.6) |
13 – 24 | 41 | – | 2 (4.9) | 2 (4.9) | 5 (12.1) | 10(24.4) | 22 (53.7) |
25 – 36 | 33 | – | – | 1 (3.0) | 4 (12.1) | 9 (27.3) | 19 (57.6) |
37 – 48 | 19 | – | – | – | 5 (26.3) | 5 (26.3) | 9 (47.4) |
49 – 59 | 06 | – | – | – | – | 1 (16.7) | 5 (83.3) |
Total | 186 | 1 (0.5) | 4 (2.6) | 7 (3.8) | 23 (25.8) | 48 (26.53) | 103 (55.4) |
Keys: Severe refers to < -3SD and/or bilateral oedema; Moderate refers to a range from < -2SD to ≥ -3SD/ absence of oedema. Global refers to < -2SD. Global stunting attributed to chronic malnutrition was at 55.4% whereas severe stunting attributed to the same 25.8%. Age groups 6-12 months and 13-24 months exhibited a higher prevalence of global acute malnutrition than the rest of the age groups by number. The prevalence of global acute malnutrition (GAM) was 3.8%. (Table 3).
Table 4: Prevalence of communicable diseases in children by age group
Population
Age group (in months) |
Frequency | Diarrhea | Cough (RTI) | Fever (Malaria) | |||
n | % | n | % | n | % | ||
3 – 5 | 09 | 8 | 88.9 | – | – | 7 | 77.7 |
6 – 12 | 78 | 44 | 56.4 | 53 | 67.9 | 62 | 79.5 |
13 – 24 | 41 | 29 | 70.7 | 30 | 73.2 | 36 | 87.8 |
25 – 36 | 33 | 20 | 60.6 | 33 | 100.0 | 31 | 93.9 |
37 – 48 | 19 | 13 | 68.4 | 19 | 100.0 | 19 | 100.0 |
49 – 59 | 06 | 4 | 66.7 | 6 | 100.0 | 6 | 100.0 |
Total | 186 | 118 | 63.4 | 141 | 75.8 | 161 | 86.6 |
RTI=Respiratory tract infection
Of the three (3) clinical investigated, most prevalent disease condition that the children under 5 at SRRH had was fever attributed to malaria (86.6%), cough (75.8%) and diarrhea 63.4% (Table 4). Having fever as a clinical sign of malaria was significantly associated with global acute malnutrition OR 7.42 95% CI 1.01-54.61 (p value=0.009) and being a male child OR 1.52 95% CI 1.12-2.05 (p value=0.003) was significantly associated with chronic malnutrition (Table 5)
Logistical regression analysis
Logistical regression analysis into the causes of malnutrition was performed for variables with a p-value less or equal to 0.2. The selected variables for acute malnutrition included: household head, major age groups, gender of the child, evidence of deworming, diarrhea, and fever. While for stunting, the variables selected were major age group, gender, diarrhea, and cough. On logistic regression, age group 3 – 24 months Adjusted OR 2.78 95% CI 1.26-6.15 (p-value = 0.014) was significantly associated with acute malnutrition while deworming in the previous 3 months Adjusted OR 0.55 95% CI 0.22-0.87 (p-value = 0.020) was protective. A male child was nearly 2 times more likely to suffer chronic malnutrition compared to a female child Adjusted OR 1.56 95% CI 1.15-2.13 (p-value = 0. 0.002). (Table 6).
Table 5: Factors associated with acute and chronic malnutrition
Variable | N | n (%) | OR | 95% CI | P – Value |
Acute malnutrition | |||||
Age group | |||||
3 – 24 months | 128 | 35 (27.3) | 2.08 | 0.97 – 4.45 | 0.054 |
25 – 59 months | 58 | 12 (14.1) | |||
Sex | |||||
Male | 89 | 46 (51.7) | 1.85 | 0.95 – 3.60 | 0.069 |
Female | 97 | 27 (27.8) | |||
Feeding practices | |||||
Breastfeeding | 148 | 58 (39.2) | 0.94 | 0.45 – 1.97 | 0.863 |
Not breastfeeding | 38 | 11 (28.9) | |||
Age at complementary feeding | |||||
<6months | 91 | 61 (67.0) | 0.88 | 0.41 – 1.89 | 0.747 |
≥ 6months | 95 | 27 (28.4) | |||
Deworming last 3months | |||||
No | 104 | 80 (76.9) | 0.49 | 0.24 – 1.04 | 0.058 |
Yes | 82 | 49 (59.7) | |||
Diarrhea | |||||
Yes | 118 | 71 (60.2) | 1.67 | 0.82 – 3.40 | 0.155 |
No | 68 | 50 (73.5) | |||
Fever (Malaria) | |||||
Yes | 161 | 113 (70.2) | 7.42 | 1.01 – 54.61 | 0.009* |
No | 25 | 9 (36.0) | |||
Cough | |||||
Yes | 141 | 57(40.2) | 1.61 | 0.62 – 4.19 | 0.328 |
No | 45 | 17 (37.8) | |||
Chronic malnutrition | |||||
Age group | |||||
3 – 24 months | 128 | 53 (41.4) | 1.34 | 0.98 – 1.83 | 0.068 |
25 – 59 months | 58 | 21(36.2) | |||
Sex | |||||
Male | 89 | 71 (79.7) | 1.52 | 1.12 – 2.05 | 0.003* |
Female | 97 | 45 (46.4) | |||
Feeding practices | |||||
Breastfeeding | 148 | 62 (41.9) | 0.99 | 0.67 – 1.46 | 0.95 |
Not breastfeeding | 38 | 12 (31.6) | |||
Age at complementary feeding | |||||
<6months | 91 | 72 (34.9) | 0.93 | 0.62 – 1.39 | 0.710 |
≥ 6months | 95 | 49 (51.6) | |||
Deworming last 3months | |||||
No | 104 | 93 (89.4) | 0.96 | 0.67 – 1.38 | 0.834 |
Yes | 82 | 52 (63.4) | |||
Diarrhea | |||||
Yes | 118 | 107 (90.6) | 0.80 | 0.58 – 1.09 | 0.157 |
No | 68 | 47 (69.1) | |||
Fever (Malaria) | |||||
Yes | 161 | 120 (74.5) | 0.81 | 0.53 – 1.23 | 0.325 |
No | 25 | 12 (48.0) | |||
Cough | |||||
Yes | 141 | 89 (63.1) | 0.74 | 0.49 – 1.09 | 0.130 |
No | 45 | 17 (37.8) |
P-value is significant at ≤ 0.05
Table 6: Factors associated with acute and malnutrition on logistic regression analysis
Variable | AOR | 95% CI | P – Value |
Acute malnutrition | |||
Age group | |||
3 – 24 months | 2.78 | 1.26 – 6.15 | 0.014* |
25 – 59 months | |||
Sex | |||
Male/Female | 1.94 | 0.98 – 3.84 | 0.058 |
Household head | |||
Mother, other/father | 1.82 | 0.81 – 4.08 | 0.148 |
Relationship with child | |||
Other/father, mother | 1.58 | 0.55 – 4.56 | 0.400 |
Evidence of deworming | |||
No/Yes | 0.44 | 0.22 – 0.87 | 0.020* |
Diarrhea | |||
Yes/No | 1.28 | 0.61 – 2.68 | 0.507 |
Fever (Malaria) | |||
Yes/No | 6.51 | 0.87 – 48.87 | 0.068 |
Chronic malnutrition | |||
Age group | |||
3 – 24 months | 1.37 | 0.99 – 1.88 | 0.052 |
25 – 59 months | |||
Sex | |||
Male | 1.56 | 1.15 – 2.13 | 0.002* |
Female | |||
Diarrhea | |||
Yes | 0.81 | 0.58 – 1.12 | 0.193 |
No | |||
Cough | |||
Yes | 0.78 | 0.52 – 1.18 | 0.239 |
No |
* P-value is significant at ≤ 0.05
DISCUSSION
A total of 186 children under 5 years attending SRRH were investigated for factors that influence malnutrition in this category of children, adult caregivers were used to interrogate the associated information needed for the study. For the caregivers of the children that were recruited, the majority were aged between 20 – 30 years (50.5%), married (75.8%), females (96.8%), and had a primary level of education (66.7%). The majority of them their source of income is farming at a peasantry level (65.1%), whereas for the children attending the SRRH outpatient department, the majority were female (52.1%) aged between 6 – 12 months (41.6%) This study has been able to establish global stunting attributed to chronic malnutrition of 55.4% whereas severe stunting attributed to the same 25.8%. This finding at SRRH is higher than the prevalence reported by Olwedo et al. [26] but has no considerable difference from Bogere [27] for a study in the same category population but in Fortportal. In this study, we observed that children between 3 months to 2 years are at an increased risk of sliding into the malnutrition bracket compared to their elder grouping of 2 – 5 years. This is envisaged to be stemming from the inability to utilize many of the additional solid foods at their disposal like the older ones who can sufficiently take advantage of the available foods. In a similar study in Burundi, Yiga [28] explored similar objectives and his findings were consistent with what we have been able to establish at SRRH. An interesting highlight in this study is the average prevalence of malaria across all age groups of the children studied at 76.7% determined by the clinical sign (fever) but also confirmed by the accessed confirmed tests of the children, and on analysis having fever as a clinical sign of malaria was significantly associated with global acute malnutrition OR 7.42 95% CI 1.01-54.61 (p value=0.009). This can be attributed to the possible loss of appetite caused by malaria in children, so it is not a surprise that it’s associated with acute malnutrition, however, on logistic analysis, it ceased being significant. Consistent acute malnutrition conclusion attributed to malaria was reported by Ubesie et al. [29] in a study in a similar setting in Nigeria. During malaria, red blood cells are depleted culminating in anemia which is a prominent sign of malnutrition [30-32]. The majority of the caregivers of the children studied at SRRH where peasant farmers at 65.1%. Such a high statistic for income generation variable for the objectives we have studied has been explored before by other scholars, and it alone by its characteristics including poor socioeconomic status, mother’s absence from home (spending most of the time doing casual labor in order to get money buy foodstuff), poor weaning practices, leaving the infants with their siblings or their grandmothers may contribute to poor nutritional status of the younger children thus influencing chronic malnutrition [4, 26, 33]. Our findings at SRRH show that boys are twice at risk of being stunted than girls. This is consistent with Ubesie’s conclusion in Nigeria in 2012 [29]. Observations from the focus group conduction showed that 87% of the children feed with adults at the same time on the same plates. Nalwanga et al. [22] reported on the dangers of children feeding with adults; that most children were susceptible to underfeeding due to completion from the adults. The UDHS [8] has reported Soroti district as one of the near-starved districts. With such practices of communal feeding where very young children have to compete with adults for inadequate food rations, it’s very plausible that these practices influence the results we are seeing in this study [22]. The study has been able to demonstrate that the presence of co-morbidities–communicable disease infections such as fever (malaria) was associated with acute malnutrition in the settings. Many studies amongst children under 5 years in Uganda showed that the risk of malnutrition increased with increasing communicable disease burdens including malaria, diarrhea, and pneumonia [34, 35].
CONCLUSION
The prevalence of malnutrition in children under 5 years attending Soroti Regional Referral Hospital is 55.4% leading to global stunting attributed to chronic malnutrition whereas severe stunting attributed to the same is 25.8%. Children aged 3-24 months and male children are twice as at risk than girls of stunting and acute malnutrition. The study concludes that malaria is a predictor of severe acute malnutrition compared to other comorbidities.
Recommendations
Design strategies to curb the prevalence of malaria in children under 5 as close to 77% by an average of the children in the study had malaria and it was shown to be a predictor of severe acute malnutrition. We recommend designing an integrated protocol that factors in comorbidities with malnutrition, as the study was able to observe no protocol for such a problem, as it wasn’t part of the objectives of the study, we didn’t interrogate this suspect. We recommend that bigger studies based on districts that are serviced by SRRH on the same objectives be done to determine the regional burden of malnutrition in children under 5 years in the region. A scientific study on a bigger scale in the Soroti community to ascertain the same specific objectives is because it’s envisaged that the magnitude of malnutrition in the community is higher and can’t be ascertained wholly in only a hospital setting.
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CITE AS: Acen Brenda (2023). Determinants of Malnutrition in Children Under Five Years at Soroti Regional Referral Hospital: A Comprehensive Analysis. INOSR Experimental Sciences 12(3):52-62. https://doi.org/10.59298/INOSRES/2023/5.3.21322