Child malnutrition

ABSTRACT

Background: Child malnutrition remains a public health concern in developing countries, especially Sub Saharan Africa and South Asia. And major universal health disease burdens.

School-aged children Continue to be neglected category by Millennium Development Goal era

and rarely involved in nutritional assessment despite the effect of malnutrition on their cognitive and physical abilities. Undernutrition is highly associated with poverty and conflicts affected areas. In South Sudan, prevalence of malnutrition among school-aged children was found to be 73%, which highlights the need to understand the current nutritional status among primary school in as well as the underlying determinants.

Objectives: To determine the prevalence and nutritional status of school children aged six to fourteen years in Bor town using anthropometric measures.

Methods: The study will be cross-sectional design. Random sampling technique will be used to select a sample of 303 students in seven primary schools in Bor Town. A semi-structured questionnaire will be used to collect the data. A semi-structured questionnaire will be used to collect the data. Using the World Health Organization Standards for detecting child nutritional status, the data be transformed into Z-scores using SPSSv26 that the cut off of -2SD can be used in grading children’s nutritional status as either underweight, stunted or wasted. The prevalence of malnutrition will be expressed as a proportion in percentage. Descriptive statistics will be used to describe the socio-demographic characteristics of the sample population. Chi-squaree test for the association will be used to determine the association between categorical variables included in the study. The hypothesis will be tested at 95% confidence level.

Significance: The findings from the study will ensure that there is knowledge of the current nutritional status among primary school children between 6- 14 years. The findings will also help understand the extent of malnutrition in South Sudan, which will help in policy development.

CHAPTER 1: INTRODUCTION

1.1.Definition and background

The world health organization (WHO) defines Malnutrition as inadequate, excess, or irregular intake of calories or nutrients as well as micronutrient deficiencies. This involves both undernutrition and overnutrition (1). Malnutrition in children is still a primary public health concern in developing countries and a major cause of global disease burden, especially among children (2). The prevalence of Malnutrition in the under-five age group has remained influential for years. However, in 2002 the UN Standing Committee on Nutrition (SCN) began to promote researches and Intervention plans to the category of school-aged children because this particular age group potentially experience “catch up growth” (3). The school children aged 5-14 years have not been adequately engaged concerning the development of better interventions in managing their needs based on sustainable Developmental goals (SDG), which have replaced the millennium development goal era (MDGs). This subpopulation is rarely involved in nutritional assessment despite the effect of nutritional Deprivation on their mental, physical, and cognitive skills (4). Malnutrition among school-aged children has been associated with multiple factors, which include morbidity, poor sanitation, food insufficiency, and families with low incomes, especially in Africa. Undernutrition is a common cause of low school enrolment, high absenteeism, early dropout, and poor school performance (5). Malnutrition needs to be viewed as an indication of inadequate provision of some of the most basic human rights. It also a reflection of insufficient investment and progress concerning social capital development and a positive influence on the future economic growth of a nation (6).

CHAPTER 2: LITERATURE REVIEW

2.1.Epidemiology

Global

In 2019 The UNICEF-WHO-WB joint child malnutrition estimated that 149 million under five are stunted 49 Million are wasted while 40 million are overweight mainly in sub-Saharan Africa

And south-central Asia (7).

2.1.2. Regionally

The Sub Saharan Africa (SSA) has some of the highest numbers of malnourished children According to study conducted in 32 SSA countries. The findings revealed that stunting was highest in Burundi at 57%, Malawi had 47%, Niger 44%, Mali 38%, Sierra Leone had 38%, Nigeria had 37%, DRC with 42% stunting. Wasting was highest in Niger 18%, Burkina Faso 15%, and 9% in Ethiopia. Underweight was highest in Burundi at 29%, and Ethiopia, 25% (8) In another study in Kilifi, Kenya, Prevalence of malnutrition estimated to be 27.5% of the study population, the most common form of malnutrition was stunting 16.6% while wasting was 2.7 and underweight was 8.3% (2).

2.1.3. Malnutrition in South Sudan

In 2017 the UNICEF reported that almost 1.1 million children in South Sudan are acutely malnourished out of these 280,000 children are severely acutely malnourished. In the 2019 UNICEF division of data research and policy. Estimated that under-five children as following 48.6% not malnourished,21.3% only stunted,17.6% only wasted,2,5 % only overweight 6.7% stunted and wasted 3.3% stunted and overweight. No official data is present about children aged 6-17 yrs.

2.2.Determinants of malnutrition among primary school children

Children are most vulnerable to undernutrition due to their low dietary intake, less access to food, unequal distribution of food within households and schools, improper food storage and preparation, dietary taboos, and infections (9). The economic cost of under-nutrition is highly substantial. According to the WHO, underweight is the single largest risk factor contributing to the global burden of disease in the developing world. It leads to nearly 15 % of the total disability-adjusted life years (DALY) losses in countries with high children mortality (10). It is also proved that 1% loss in adult height occurred due to childhood stunting, which in return associate with a 1.4% loss in productivity (11).

2.2.1. Maternal factors

In a study conducted in Nepal showed that there was a significant association between child malnutrition in school and maternal literacy, occupation, dietary knowledge, and monthly income of the mother (12). Another study conducted in Kenya revealed that the findings from the study highlight that household food insecurity, low maternal education, and infection with Trichuris trichura were some of the main risk factors to under-nutrition in the study (13).

2.2.2. Infection

Infection is one of the most important risk factor for malnutrition .it has a significant impact on child growth. Chronic Diarrheal diseases have been linked to wasting (2). Malnutrition has been a primary cause of immunodeficiency globally. There are five infectious diseases that account for more than half of all deaths in children, with most of them being undernourished. Micronutrient deficiencies have negative outcomes such as poor growth, impaired intelligence, and increased susceptibility to infection(14).

2.2.3. Food insecurity and feeding programs

Feeding programs in schools have been associated with improved nutritional status among school children. In a cross-sectional study conducted in Kenya, showed that having no father have a direct impact on child health and that the higher the mother’s education, the more wasting was seen despite participation in the programme. The programme reduced anemia and malnutrition and has improved child growth in our study group greatly, but we found that the education level of the mother, family size, and absence of a father overruled the effect of the school feeding programme (15).

In a cross-sectional study conducted in Madagascar school Aged children between 5 -14 years in ten primary schools that had implemented a school feeding program, the study revealed that older children had a high chance of being stunted and thin. The greater the number of members a household had, the higher the likelihood of being stunted and wasted. Children having lower Household Dietary Diversity Score were more likely to be underweight. Although, “Had lunch at school yesterday “was associated neither with being stunted nor with being underweight and thin. This implies room for improvement of the current school feeding program(4).

2.2.4. Socio-demographic factors

The older age group among school-age children was an independent determinant of stunting. Children within 10 -14 years age group were more likely to become stunted. The study also identified that children whose mothers completed primary education were less likely to be stunted (16). Having a larger family size, inadequate intake of carbohydrates were independent factors that predict wasting. Children who live in food-insecure households are more likely to be stunted, under-weight, and wasted than children live in food-secure households.

In Primary school in Pakistan, children were also assessed in determining the socio-demographic factors that predict stunting and wasting. The results revealed that older age, urban areas with low SES, and low-income neighborhoods were associated with stunting. The findings also indicate that low-income neighborhoods and older age were associated with lower HFA z-score while the rural area with low SES was associated with lower BMI-for-age Z score (17). Therefore, based on the findings in the study, the low prevalence of stunting and thinness depicted an improvement in the nutritional status of SAC in Pakistan.

However, the inequities between the poorest and the richest population groups were marked with a significantly higher prevalence of stunting and thinness among the rural and the urban poor, the least educated, the residents of low-income neighborhoods and those having crowded houses. An increasing trend with age was observed in the prevalence of stunting and thinness. Smoking in the living place was associated with stunting. According to a cross-sectional study in Ghana, Sub-district, sex, age of the pupil, area of residence, and community type were significantly associated with stunting (9).

2.3.Classification of Malnutrition

According to the WHO, the term malnutrition address three broad categories the first one is Undernutrition which includes wasting (low weight for height), stunting (low stature for age) and underweight (low weight for age). The second is micronutrients malnutrition, which includes micronutrient deficiencies (essential vitamins like A, C, B, and minerals. The third and the last one is overnutrition, which includes overweight, obesity, and diet-related diseases (CHD, cancers, and diabetes Mellitus (1).

According to a study conducted in South Africa School, Aged Children 10- 12 years were as follows 66%n underweight, 28% normal weight while 5% were overweight. The findings from the study indicate that the majority of primary school children from the selected schools were underweight (18).

Developing countries have been significantly hit by undernutrition, with evidence showing nearly 52% of school-age children being stunted and underweight (19). The study further highlights that if no major interventions are put in place, it is estimated that one billion children will be physically and mentally impaired.

A cross-sectional study conducted in Chennai India, targeting children between 6 -10 years showed that the overall prevalence of underweight was 54.3%. It was higher among girls (65%) than boys. The prevalence of underweight was high despite the presence of a mid-day meal scheme and regular school health services in the state. (20).

2.3.1. Stunting

Stunted growth is a primary manifestation of malnutrition in early childhood, more than 90% of the world’s stunted children live in Africa (36%) and Asia (27%) (3). A key to success against stunting is focusing attention on pregnancy and the first two years of a child’s life. Stunting in a child is not only about physical appearance but also the stunted development of the brain and cognitive capacity (21).

A recent study conducted in Kibera Kenya aimed at assessing the effects of a school feeding program on the nutritional status of children in urban slums. The findings from the analysis showed that children who participated in the feeding program were less stunted and wasted.

In another study conducted in Pakistan among SAC between 5-12 years, found 8% of the children who were investigated were stunted. The results also identified that stunting and wasting were significantly associated with gender. Stunting in primary school children increased in the older age group compared (17).

2.3.2. Wasting

Wasting is an increasing malnutrition issue among school-age children in low-income countries. The findings obtained from a study in Madagascar among school-age children identified that 11% of them were wasting while 5% of the respondents suffered from all of the three forms of undernutrition, which include wasting, underweight, and stunting (4). In another study cross-sectional study conducted in Western Nepal, the finding showed that 12% of the primary school learners were found to be wasted while only 1% were found to be both stunted and wasted (12).

Kwabla et al. conducted a study in school children between 5 and 12 years in Ghana. The Government of Ghana, with the Dutch Government, introduced the school feeding programme (SFP) to boost the nutritional status of SAC in the country. The purpose of the study was to compare the nutritional status of SAC enrolled in schools with the SFP and school children without the SFP. The findings showed that the prevalence of wasting was 9.6% in schools without a feeding program compared to 4.6% in schools with a feeding program (22).

2.4.Consequences of Malnutrition in school-aged children

2.4.1. Physical and cognitive development

A study conducted in western Kenya suggests that school-aged children in developing countries do not experience catch up growth type A (accelerated growth velocity following an insult to growth) but continue to accrue greater height deficits with age if they remain in the same environment (6). Developing countries have been significantly hit by undernutrition, with evidence showing nearly 52% of school-age children being stunted and underweight (19). The study further highlights that if no major interventions are put in place, it is estimated that one billion children will be physically and mentally impaired.

2.5.Study Justification

The prevalence of malnutrition in under-five age groups has remained important for years, although in 2002, the UN -SCN began to promote researches and intervention plans to the of SAC because this particular age group potentially experience “catch up growth” (3). In the 2019 UNICEF division of data research and policy. Focused on under-five children in South Sudan. But No official data were present about school children aged 6-16 yrs (7). There has been an increase in poverty levels due to natural disasters like droughts as well as conflict-affected area, putting children at risk of malnutrition. More than 60 million children go to school hungry every day 40% of them are African, including South Sudanese (2). This study will provide essential information on nutritional status among SAC in Bor town, South Sudan. This will lay a foundation for further studies about the malnutrition. In other parts of the country. This will assist in early identification on whom at risk of malnutrition and put interventions plans to improve the nutritional status of SAC in Bor town and the overall economy of the area.

2.6.Research question

What is the prevalence and risk factors associated with malnutrition among school-aged children in Bor town, South Sudan?

2.7.Study objective

2.7.1. Primary objectives

To Assess the nutritional status of children aged 6-14 yrs. in public schools. In Bor town, using anthropometric methods.

2.7.2. Secondary objective.

To evaluate the socio-demographic factors associated with poor nutritional status among these school-aged children in Bor town.

CHAPTER 3: RESEARCH METHODOLOGY

3.1.Study Design

This be will be a descriptive cross-sectional study.

3.2.Study Area

The study will be conducted in public primary schools in Bor town of Jonglei state located at 200 km northern east of Juba, the capital of South Sudan. The total population of Bor town was estimated to 61,716 as projected from the 5^th Sudan population and housing census 2010. The town has eight public schools and six private primary schools.

3.3.Study population

The study will include primary school children attending public primary school in Bor Town between the age of 6 and 14 years. Bor Town has eight public primary schools that will be targeted in this study.

3.4.Inclusion criteria

Public primary school children aged between 6 – 14 years.
Enrolled in public primary school in Bor county.
Children for whom informed written consent was obtained from the headteachers to participate in the study.

3.5.Exclusion criteria.

All private primary school children
Children under 6 years and above 14
Children for whom there is no consent obtained.

3.6.Sample Size

Based on the prior information obtained in a study cross-sectional study conducted in South Sudan, the prevalence of underweight was 73%, which was higher than stunting and wasting; hence was used as the proportion to estimate the sample population (23). Fischer’s formulae will be used. Thus,

N=Z²*P(1-P)

e²

N is the desired sample size

Z is the value representing a 95% confidence interval

e is the precision with which to measure the prevalence of the study ±5%

P is the estimated prevalence (based on a study by Charchuk et al. (2015), the value used is 73%.

N=1.96²*0.73*0.27

0.05²

The sample size is 303

The study will select the three most populous public schools in Bor Town based on proportionate sampling.

3.7.Data Collection Procedures

The questionnaire will be developed from the ministry of health, RSS. The questionnaire will be in English and Dinka language for data collection. The questionnaire will include socioeconomic and demographic factors such as child feeding, hygienic practices at home, and anthropometric measurements.

A structured questionnaire in a face-to-face manner will be used to collect the data from children 6–14yr. Two nutritionists and six public health workers, including the principal investigator, will be involved in the data collection process.

Prior to the interview, verbal informed consent will be obtained from all participants after explaining the objective of the study, and it will be confirmed that the information will be kept confidential

3.8.Measurements

Anthropometric measurements such as weight and height of children will be taken using the standard measurement procedures outlined in the measurement guide prepared by WHO. Bodyweight will be measured using a weighing scale in light clothing with no jackets, shoes, or other additional items on a new portable scale.

Height of children will be measured using a portable stadiometer with no shoes; the shoulders, buttocks, and the heels touched the vertical stand with the head in Frankfurt’s position to the nearest 0.1 cm. or measuring tape For children 6-14 yrs. of age, standing height to the nearest 0.1 cm will be measured.

2006 WHO Anthro 3.2.1 software will be used to convert weight, height, and age of the child into height-for-age (HAZ), weight-for-age (WAZ), and weight-for-height (WHZ) Z-scores to assess malnutrition taking sex into consideration. Anthropometric classifications were based on global standards: <−3 SD, <−2 SD, and ≥−2 SD. Children with HAZ, WAZ, and WHZ below −2 SD of the median of reference population will be considered as stunted, underweight, and wasted, respectively. Children with HAZ, WAZ, and WHZ below −3 SD were also considered as severely stunted, wasted, and underweight, respectively.

The respondents will be asked about the amount and variety of meal consumed and the occurrence of food shortage at home, causing them not to eat the entire day or eat at night only, in the one week before the survey. Then, food-secure students were coded “1” and food-insecure ones “0” for further analysis.

3.9.Data Quality Control

To ensure data quality, the English version questionnaire will be translated into the local language (Dinka) and will be translated back to English to maintain its consistency. Three -day training will be given to the data collectors and supervisors before the actual date of data collection. Continuous monitoring will be done by the principal investigator on a daily bases.

3.10. Statistical Analysis

Data entry and analysis will be done using the EPI info package SPSS version 26, respectively. Anthropometric indices will be calculated using 2006 WHO Anthro 3.2.1 Software. Descriptive analysis will be used to describe the percentages and frequency of sociodemographic characteristics and other relevant variables in the study.

3.11. Ethical Considerations

Ethical clearance will be obtained from Kenyatta national hospital scientific Research and Ethics Committee in collaboration with the ministry of education RSS. Then, officials at different levels in the study area will be informed through letters from the University of Nairobi and the ministry of health RSS. Letters of permission were obtained from Jonglei state authority. Verbal consent will be obtained from the Parent’s participant or participant’s closest guardian before the interview after explaining the purpose of the study.

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