Contribution to the Study of the Determinants of Malnutrition in Children Aged 6 - 59 Months in the Case of Buhiga Commune, Karusi Province ()
1. Introduction
Malnutrition plays a large role in half of all child deaths worldwide, which is more than any infectious disease and yet it is not an infection. It leaves lasting after-effects in millions of survivors in the form of infirmity, chronic vulnerability to disease, and intellectual disability. A threat to women, families and entire societies, it is a clear violation of human rights (Minisante, 2010).
An individual’s health depends largely on how well they eat. There is an old saying that you have to eat to live, but still, you have to be able and “know” how to eat, because an unbalanced diet due to excess or lack of intake can be as harmful as a lack of food.
This imbalance is a real public health problem throughout the world. On the one hand, it can be overeating with its consequences on health such as obesity, diabetes, heart disease, and on the other hand, undernutrition which leads to malnutrition through deficiency commonly known as undernourishment or undernutrition.
As a result, our study will especially help food insecurity programs to identify the determinants of malnutrition in children aged 6 months to 59 months as well as the socio-economic and cultural constraints related to malnutrition and to act in accordance with the results obtained in order to achieve food security in the community.
This work will contribute to and enrich the database on the determinants of malnutrition among children aged 6 months to 59 months in the community in order to promote child health.
Malnutrition increases the risk of death in this population by combining with other diseases that it often facilitates the occurrence of, such as: measles, ARI, diarrhoea, malaria, etc. (WHO, 2008).
The 2010 Demographic and Health Survey in Burundi showed that 58% of children under five were chronically malnourished, 28.8% were underweight and 5.8% were acutely malnourished. Indeed, chronic malnutrition has lasting consequences on children’s cognitive abilities and consequently on the nation’s vital forces (Minisante, 2011).
In accordance with the orientations of the Burundi 2025 Vision, the Second Generation Strategic Framework for Growth and Poverty Reduction (PRSP II) for the period 2012-2016, recalled that malnutrition is due to the poor performance of agricultural production and the dietary practices of the population, 67% of whom live below the national poverty line, according to the conclusions of the survey carried out in 2006 on the basic indicators of the well-being of the population. By the Government in collaboration with the University Research Centre for Economic and Social Development (CURDES) of the University of Burundi. Several activities are envisaged in the PRSP-II to address the immediate causes of malnutrition related to health and food security (Minisante, 2007).
Improving infant nutrition therefore seems to be a necessary condition for reducing the prevalence of chronic malnutrition. The choice of the Buhiga commune was motivated by the results of the SAMART 2022 survey which showed that the Buhiga commune is among the communes with a high rate of children under 5 years of age suffering from global acute malnutrition, i.e. 6.4% which is higher than the WHO standards of 5%.
This is why, aware of this public health problem affecting this population characterized by its vulnerability, we are motivated to undertake a study whose aim is to identify the factors at the origin of the frequency of malnutrition among children under five years of age in the Buhiga commune of the Karusi province in order to formulate appropriate suggestions.
The Malnutrition Analysis of Children under Five in Burundi is an important tool for refining our approaches to nutrition and improving the country’s development outcomes (Minisante, 2012).
2. Study Method
2.1. The Framework of the study
Burundi is a country in East Africa. It borders Rwanda to the north, Tanzania to the south and east and the Democratic Republic of Congo (DRC) to the west. It is part of the Great Lakes region. Its surface area is 27,834 km2, including 2700 km² of lakes and 23,500 km2 of potentially agricultural land. The total population, according to the RGPH 2008 projections, is estimated at 11,215,578 inhabitants, of whom 5,500,949 are men and 5,714,629 are women. This population is distributed in 18 provinces, 119 communes and 2911 hills.
The commune of Buhiga, on which our study focused, is made up of three zones spread over 30 hills and 132 sub-hills.
The population of children aged 6 months to 59 months is 12,764 inhabitants in 2024 according to ISTEEBU’s 2010-2050 municipal projections.
2.2. The Type, Period, Location and Population of the Study
This is a cross-sectional study with an analytical purpose that was carried out in the different households of the commune of Buhiga. The study covered a 4-month period from March 1 to June 31, 2024. A survey questionnaire was sent to each survey and completed by the interviewer during data collection.
The choice of the Buhiga commune was motivated by the results of the SAMART 2022 survey which showed that the Buhiga commune is among the communes with a high rate of children under 5 years of age suffering from global acute malnutrition, i.e. 6.4% which is higher than the WHO standards of 5%.
The study population consisted of children aged 6 to 59 months at the time of the survey who were in different households in the hills of the Buhiga commune (Figure 1).
Figure 1. Political map of the commune of Buhiga Karusi Province.
2.3. Sampling Method
2.3.1. Sample Size
The prevalence of children aged 6 to 59 months with Global Acute Malnutrition assessed by weight-for-height and/or MUAC ratio is known and is 6.4% according to data reported in the 2022 SMART survey. This proportion was used to calculate the sample size.
The sample size was determined using the following Schwartz formula.
(Schwartz, 1969)
n = sample size;
Z = 95% z-score (1.96);
p = prevalence of acute malnutrition (0.064);
e = margin of error (4.3%);
n = 124.
Applying the 5% non-response, the sample size becomes 130, i.e. 130 households with children aged 6 to 59 months.
The sample size of our study was 130 mothers or their guardians with children aged 6 to 59 months, i.e. 130 households in the commune of Buhiga.
2.3.2. Inclusion and Exclusion Criteria
1) Inclusion criteria
2) Non-inclusion criteria
2.3.3. Sampling Technique
Our study took place in all the areas of responsibility of the health centers located in the commune Buhiga using the technique of proportional allocation stratification, each area of responsibility being a stratum. To determine the number of children to be surveyed in each stratum, the 130 children in our sample were allocated proportionately based on the average number of children aged 6 to 59 months in each area of responsibility (Table 1).
Table 1. Distribution of the sample of children aged 6 - 59 months by size in each area of responsibility.
Area of responsibility |
Number of children aged 6 to 59 months in each area of responsibility (Ni) |
Sample by Area of Responsibility (ni) |
Karusi Area of Responsibility |
3032 |
31 |
Buhiga Area of Responsibility |
2681 |
27 |
RUDARAZA Area of Responsibility |
2321 |
24 |
KANYANGE Area of Responsibility |
1618 |
17 |
RUKAMBA Area of Responsibility |
1209 |
12 |
RUTONGANIKWA Area of
Responsibility |
1903 |
19 |
Total |
12,764 (N) |
130 |
The sample by area of responsibility was identified using the following formula:
(York House et al., 2024)
With:
Ni: number of children to be included in the sample for each area of responsibility;
n: sample size to be drawn in all areas of responsibility of the Buhiga Health District;
N: Total number of children aged 6 - 59 months who are in the Buhiga community;
Ni: Total number of children aged 6 to 59 months in each area of responsibility of the Buhiga Health District.
2.4. Data Collection Tools and Techniques
The information was collected through a questionnaire that was sent to the children’s mothers or their guardians. It is a structured questionnaire comprising 4 dimensions: a dimension related to sociodemographic factors, a dimension related to environmental and behavioral factors, and a dimension related to the child’s morbidity.
The questionnaire has been translated into the national language to facilitate the respondent’s understanding. Before completing the questionnaire, the interviewer began to explain the purpose of the survey and assured the respondent of the confidentiality of the information provided.
Prior to the interview, informed and written consent was obtained from the mothers who consented on behalf of their children. In cases where the mother was illiterate, verbal consent was obtained from the mother according to a detailed description of the protocol and written consent was obtained from her husband who consented in writing on behalf of the mother and child.
The questionnaires have been coded to maintain anonymity and confidentiality. Data collection was carried out from Monday to Friday (8 a.m. to 3 p.m.) on the identified hills until the required sample was obtained. After collection, data entry was performed in Excel version 2016.
2.5. Pre-Test
To test the understanding of the questionnaire (pre-test), the questionnaire was first sent to some households with children aged 6 to 59 months in the Bugenyuzi commune, then some questions were adapted and reformulated. The pre-test also made it possible to estimate the time needed to investigate a person.
2.6. Definition of Variables
2.6.1. Dependent Variable
The dependent variable for this study is global acute malnutrition which is a dichotomous variable that was determined using the mid-upper arm circumference using a tape measure coded by red, yellow, green colors, so we retained those with a MUAC < 115 mm, we also assessed the presence or absence of bilateral edema.
2.6.2. Independent Variables (Table 2, Figure 2)
The independent variables which has been tested and have significantly influenced the dependent variable on the one hand and other independent variables which have been associated with the dependent variable on the other hand are grouped in 3 headings, namely:
1) Socio-economic Characteristics;
2) Factors related to child morbidity;
3) Behavioral and environmental factors.
Table 2. Description of independent variables.
Variables |
Description |
Operational definition/
Terms and conditions |
Socio-economic characteristics |
1. |
Marital status |
Qualitative variable that designates the marital status of parents with five modalities |
• Single = 1 • Divorced = 2 • Widower = 3 • Married = 4 • Common-law union = 5 |
2. |
Mother’s level of education |
Qualitative variable that shows the mother’s level of education with 4 modalities |
• Without = 1 • Primary = 2 • Secondary = 3 • University = 4 |
3. |
Father’s level of education |
Qualitative variable that shows the father’s level of education with 4 modalities |
• Without = 1 • Primary = 2 • Secondary = 3 • University = 4 |
4. |
Guardian of the child |
Qualitative variable with six
modalities |
• His mother = 1 • His father = 2 • His grandmother = 3 • His grandfather = 4 • One person in the family = 5 • One person outside the
family = 6 |
5. |
History of the first birth |
Qualitative variable with three
modalities |
• <18 years = 1 • Between 18 and 30 years old = 2 • 30 years and older = 3 |
6. |
Sex of the child |
Qualitative variable with two
modalities |
• Male = 1 • Female = 2 |
7. |
Age of the child |
Qualitative variable with three
modalities |
• Between 6 and 12 months = 1 • 12 and 36 months = 2 • 37 and 59 months = 3 |
8. |
Respect for the birth interval |
Qualitative variable with three
modalities |
• 1 - 2 years = 1 • 3 - 7 years old = 2 • Over 7 years = 3 years old |
9. |
Religion |
Qualitative variable with four
modalities |
• Catholic = 1 • Prostitute = 2 • Muslim = 3 • Anglican = 4 |
10 |
Household size |
Qualitative variable that shows the size of the family with three
modalities |
• 1 - 2 = 1 • 3 - 7 = 2 • Plus 7 = 3 |
Factors related to child morbidity |
11. |
Appetite at L’
Enfant |
Qualitative variable that shows whether the child has difficulties with eating meals with two
modalities |
• Yes = 1 • No = 2 |
12. |
Digestive
disorders |
Qualitative variable that shows whether the child has been
confronted with digestive
disorders in relation to eating meals with two modalities |
• Yes = 1 • No = 2 |
13. |
Access to
treatment |
Qualitative variable that shows whether the child has easy
access to health care with two
modalities |
• Yes = 1 • No = 2 |
14. |
Episode of recurrent diarrhea |
Qualitative variable with 2
modalities that refer to the
notion of diarrhoea that is
recurrent in children |
• Yes = 1 • No = 2 |
15. |
Presence of
febrile peak
(fever) |
Qualitative variable with 2
modalities |
• Yes = 1 • No = 2 |
16. |
Presence of a chronic disease |
Qualitative variable that shows whether the child is living with a chronic disease with 2
modalities |
• Yes = 1 • No = 2 |
17. |
Repeated
malaria |
Qualitative variable with 2
modalities that refer to the
notion of malaria which is
recurrent in children |
• Yes = 1 • No = 2 |
18. |
Repeated
infection |
Qualitative variable with 2
modalities that refer to the
notion of repetitive infection in children |
• Yes = 1 • No = 2 |
Behavioural and environmental factors |
19. |
Knowledge of the child’s weaning
period |
Qualitative variable with three
modalities that indicates when the child started to eat the
family dish |
• Before 6 months = 1 • 6 months = 2 • After 6 months = 3 |
20. |
Type of care
facility
attended |
Qualitative variable with three modalities that refers to knowledge of the place where one is being treated |
• Known health training = 1 • Community Health Workers = 2 • Traditional practitioners or self-medication = 3 |
21. |
Type of meal
consumed |
Qualitative variable with two
modalities that indicate the type of food the child takes |
• Family dish = 1 • Dish of its own = 2 |
22. |
Frequency of meals in
children |
Qualitative variable that shows how the child feeds with three modalities |
• 2 meals per day = 1 • 3 meals per day = 2 • More than 3 meals per day = 3 |
23. |
Compliance with the
vaccination schedule |
Qualitative variable with two
modalities that show whether the child has had all the
recommended vaccines. |
• Yes = 1 • No = 2 |
24. |
Primary
decision-maker in the household |
A qualitative variable with three
modalities that show whether the mothers of the children have a say in decision-making at the household level, especially in the management of household income, since they are the ones who are responsible for the
nutrition of the children |
• The husband decides
alone = 1 • The woman decides
alone = 2 • Husband and wife decide together = 3 |
25. |
Source of
income |
Qualitative variable that shows the level of wealth of the
household with four modalities |
• Agriculture = 1 • Agriculture and
livestock = 2 • Civil servants’ salaries = 3 • Others = 4 |
26. |
Intimate
partner
violence |
Qualitative variable with two
modalities that show whether the household is confronted with difficulties related to the
disagreement between the
husband and the mother |
• Yes = 1 • No = 2 |
27. |
Well-
appointed
latrine |
Qualitative variable with two
modalities that show whether there is a clean latrine that meets all the sanitary conditions in the household |
• Yes = 1 • No = 2 |
28. |
Compliance with Good Hand Hygiene Practices |
Qualitative variable that shows whether hygiene conditions are well met to prevent dirty hand diseases with 2 modalities |
• Respected = 1 • Not met = 2 |
29. |
Knowledge of the number of times the child is breastfed per day |
Qualitative variable that
indicates the frequency of breastfeeding per day in
number with 2 modalities |
• Who = 1 • No = 2 |
![]()
Figure 2. Conceptual framework of malnutrition among children aged 6 - 59 months in Buhiga commune.
2.7. The Results Analysis Plan
A database was built using Excel 2016 and the data was exported to STATA for analysis. After the data was entered, the data was pre-processed to assess the quality of the information entered, including checking the normality of the data. If quantitative data were missing, they were replaced by the mean or median for variables with a normal and abnormal distribution, respectively. For qualitative data, they have been replaced by a frequent modality. Outliers were also corrected prior to the actual analysis.
Subsequently, the data analysis was carried out as follows:
For descriptive analysis (univariate analysis), the following measures were calculated: proportion for qualitative variables, mean and standard deviation for quantitative variables following a normal distribution; median and interquartile range for quantitative variables that do not follow a normal distribution
In bivariate analysis, each independent variable was cross-referenced with the dependent variable. The exact Fisher test was used to test the significance of associations when at least one of the theoretical values was less than 5, elsewhere the chi2 test was used. The odds ratio, p-value and 95% confidence interval were also calculated to test the statistical significance, meaning and strength of the associations of the observed differences between the proportions of the different modalities with respect to the dependent variable;
Logistic regression was applied and eliminated confounding factors. Variables with a significant p-value (<5%) and those with a p-value of less than 20% were integrated into the initial model with top-down elimination of variables with p > 0.05.
After modelling, the best model with a low CSA was selected as containing variables considered to be factors influencing the occurrence of acute malnutrition in children aged 6 to 59 months in the commune of Buhiga. Only variables of which p < 0.05, at this stage, have been taken as the determinants of acute malnutrition.
Finally, a ROC curve was used to discriminate between children aged 6 to 59 months with acute malnutrition and those without acute malnutrition.
2.8. Internal and External Validity
2.8.1. Internal Validity
Different strategies have been set to minimize or avoid possible biases:
The list of health centers and areas of responsibility was found in the commune of Buhiga.
A 95% confidence interval was used with a margin of error set at least 5%.
Bivariate analysis and multivariate analysis were done to study the influence of the different independent variables on the dependent variable.
2.8.2. External Validity
The results of the study were extrapolated to all children aged 6 to 59 months in the Buhiga commune.
3. Presentation and Discussion of Results
The frequency of global acute malnutrition among children aged 6 - 59 months in the Buhiga commune of the Karusi province is 12 children out of the total of 130 children sampled, which makes a prevalence rate of 9.23% of acute malnutrition among children aged 6 - 59 months in the commune Buhiga (Figure 3).
The presentation of the results of this study is based on the following 3 points:
I. Descriptive analysis (univariate analysis).
II. Bivariate analysis.
III. Multivariate analysis.
Figure 3. Prevalence of acute malnutrition among children aged 6 - 59 months in Buhiga commune.
3.1. Descriptive Analysis of the Sample (Univariate Analysis)
Table 3 shows that the variables Father’s Education Level (p = 0.023), Mother’s Education Level (p = 0.000), Child Age (p = 0.008) and Household Size (p = 0.000) are associated with acute malnutrition.
Table 3. Characteristics of the sample (n = 130) according to sociodemographic factors of children aged 6 to 59 months in the commune of Buhiga.
|
|
Acute malnutrition |
|
|
Variable |
n (%) |
Yes |
No |
Chi2 |
p-value |
Marital Status |
|
|
|
6.9074 |
0.141 |
Bachelor |
1 (0.77) |
0 (0) |
1 (0.85) |
|
|
Married |
118 (90.77) |
9 (75.00) |
109 (92.37) |
|
|
Divorced |
1 (0.77) |
0 (0) |
1 (0.85) |
|
|
Cohabitation |
5 (3.85) |
2 (16.67) |
3 (2.54) |
|
|
Widower |
5 (3.85) |
1 (8.33) |
4 (3.39) |
|
|
Mother’s level of education |
|
|
|
9.5127 |
0.023 |
Without |
37 (28.46) |
8 (66.67) |
29 (24.58) |
|
|
Primary |
72 (55.38) |
3 (25.00) |
69 (58.47) |
|
|
Secondary |
20 (15.38) |
1 (8.33) |
19 (16.1) |
|
|
University |
1 (0.77) |
0 |
1 (0.85) |
|
|
Father’s level of education |
|
|
|
41.5377 |
0.000 |
Without |
22 (16.92) |
10 (83.33) |
12 (10.17) |
|
|
primary |
94 (72.31) |
2 (16.67) |
92 (77.97) |
|
|
Secondary |
14 (10.77) |
0 (0.00) |
14 (11.86) |
|
|
History of the first birth |
|
|
|
60.6500 |
0.564 |
<18 years old |
9 (6.92) |
7 (58.33) |
2 (1.69) |
|
|
Between 18 and 30 years old |
115 (88.46) |
3 (25.00) |
112 (94.92) |
|
|
30 years and older |
6 (4.62) |
2 (16.67) |
4 (3.39) |
|
|
Sex of the child |
|
|
|
0.1136 |
0.736 |
Boy |
71 (54.62) |
6 (50.00) |
65 (55.08) |
|
|
Daughter |
59 (45.38) |
6 (50.00) |
53 (44.92) |
|
|
Age of the child |
|
|
|
9.6230 |
0.008 |
Between 6 and 12 months |
31 (23.85) |
7 (58.33) |
24 (20.34) |
|
|
12 and 36 months |
18 (13.85) |
2 (16.67) |
16 (13.56) |
|
|
37 and 59 months |
81 (62.31) |
3 (25.00) |
78 (66.10) |
|
|
Birth interval respected |
|
|
|
16.4259 |
0.765 |
No |
41 (31.54) |
10 (83.33) |
31 (26.27) |
|
|
Yes |
89 (68.46) |
2 (16.67) |
87 (73.73) |
|
|
Household size |
|
|
|
21.3823 |
0.000 |
1 - 2 |
0 (0.00) |
0 (0.00) |
0 (0.00) |
|
|
3 - 7 |
95 (73.08) |
2 (16.67) |
93 (78.81) |
|
|
More than 7 |
35 (26.92) |
10 (83.33) |
25 (21.19) |
|
|
Religion |
|
|
|
1.8733 |
0.759 |
Catholic |
90 (69.23) |
7 (58.33) |
83 (70.34) |
|
|
Protestant |
22 (16.92) |
3 (25.00) |
19 (16.10) |
|
|
Anglican |
5 (3.85) |
1 (8.33) |
4 (3.39) |
|
|
Muslim |
4 (3.08) |
0 (0.00) |
4 (3.39) |
|
|
Other |
9 (6.92) |
1 (8.33) |
8 (6.78) |
|
|
Birth order |
|
|
|
0.0446 |
0.833 |
First child |
19 (14.62) |
2 (16.67) |
17 (14.41) |
|
|
Other Rank |
111 (85.38) |
10 (83.33) |
101 (85.59) |
|
|
Table 4 above shows that the variables Digestive disorders (p = 0.008) and Recurrent malaria (p = 0.001) are associated with acute malnutrition.
Table 4. Characteristics of the sample (n = 130) according to the morbidity factors of the child aged 6 to 59 months in the commune of Buhiga.
|
|
Acute malnutrition |
|
|
Variable |
n (%) |
Yes |
No |
Chi2 |
p-value |
Digestive disorders |
|
|
|
7.0950 |
0.008 |
Yes |
79 (60.77) |
3 (25.00) |
76 (64.41) |
|
|
No |
51 (39.23) |
9 (75.00) |
42 (35.59) |
|
|
Access to treatment |
|
|
|
0.6161 |
0.432 |
Yes |
96 (73.85) |
10 (83.33) |
86 (72.88) |
|
|
No |
34 (26.15) |
2 (16.67) |
32 (27.12) |
|
|
Episode of diarrhea |
|
|
|
0.0147 |
0.904 |
Yes |
88 (68.22) |
8 (66.67) |
80 (68.38) |
|
|
No |
41 (31.78) |
4 (33.33) |
37 (31.62) |
|
|
Presence of febril-spike |
|
|
|
0.0731 |
0.787 |
Yes |
82 (63.08) |
8 (66.67) |
74 (62.71) |
|
|
No |
48 (36.92) |
4 (33.33) |
44 (37.29) |
|
|
Presence of chronic disease |
|
|
|
0.8669 |
0.352 |
Yes |
122 (93.85) |
12 (100.00) |
110 (93.22) |
|
|
No |
8 (6.15) |
0 (0.00) |
8 (6.78) |
|
|
Repeated malaria |
|
|
|
11.7262 |
0.001 |
Yes |
81 (62.31) |
2 (16.67) |
79 (66.95) |
|
|
No |
49 (37.69) |
10 (83.33) |
39 (33.05) |
|
|
Repeated infection |
|
|
|
0.0147 |
0.904 |
Yes |
41 (31.78) |
4 (33.33) |
37 (31.62) |
|
|
No |
88 (68.22) |
8 (66.67) |
80 (68.38) |
|
|
Table 5 above shows that only the variable Meal frequency (p = 0.000) is associated with acute malnutrition.
Table 5. Characteristics of the sample (n = 130) according to behavioural and environmental factors of children aged 6 - 59 months in the commune of Buhiga.
|
|
Acute malnutrition |
|
|
Variable |
n (%) |
Yes |
No |
Chi2 |
p-value |
Knowledge of the number of times breastfed per day |
|
|
|
0.2617 |
0.609 |
Yes |
113 (86.92) |
11 (91.67) |
102 (86.44) |
|
|
No |
17 (13.08) |
1 (8.33) |
16 (13.56) |
|
|
Types of care facilities attended |
|
|
|
0.0025 |
0.960 |
Known health facilities |
106 (82.81) |
10 (83.33) |
96 (82.76) |
|
|
Use of community health
workers |
22 (17.19) |
2 (16.67) |
20 (17.24) |
|
|
Frequency of meals consumed |
|
|
|
49.8861 |
0.000 |
1 meal per day |
16 (12.31) |
9 (75.00) |
7 (5.93) |
|
|
2 meals a day |
40 (30.77) |
3 (25.00) |
37 (31.36) |
|
|
3 meals a day |
64 (49.23) |
0 (0.00) |
64 (54.24) |
|
|
4 meals a day |
10 (7.69) |
0 (0.00) |
10 (8.47) |
|
|
Weaning age |
|
|
|
0.4279 |
0.807 |
Before 6 months |
11 (8.46) |
1 (8.33) |
10 (8.47) |
|
|
6 months |
100 (76.92) |
10 (83.33) |
90 (76.27) |
|
|
After 6 months |
19 (14.62) |
1 (8.33) |
18 (15.25) |
|
|
Compliance with the
vaccination schedule |
|
|
|
0.0127 |
0.910 |
Yes |
118 (90.77) |
11 (91.67) |
107 (90.68) |
|
|
No |
12 (9.23) |
1 (8.33) |
11 (9.32) |
|
|
Primary Household Decision Maker |
|
|
|
3.3051 |
0.192 |
Husband and wife decide
together |
104 (80.00) |
12 (100.00) |
92 (77.97) |
|
|
The husband decides alone |
13 (10.00) |
0 (0.00) |
13 (11.02) |
|
|
The woman decides alone |
13 (10.00) |
0 (0.00) |
13 (11.02) |
|
|
Sources of income |
|
|
|
2.4145 |
0.491 |
Agriculture |
100 (76.92) |
9 (75.00) |
91 (77.12) |
|
|
Agriculture and livestock
farming |
18 (13.85) |
3 (25.00) |
15 (12.71) |
|
|
Civil servants’ salaries |
11 (8.46) |
0 (0.00) |
11 (9.32) |
|
|
Other |
1 (0.77) |
0 (0.00) |
1 (0.85) |
|
|
Domestic violence |
|
|
|
0.3752 |
0.540 |
Yes |
31 (23.85) |
2 (16.67) |
29 (24.58) |
|
|
No |
99 (76.15) |
10 (83.33) |
89 (75.42) |
|
|
Fitted latrine |
|
|
|
0.1438 |
0.705 |
Yes |
103 (79.23) |
9 (75) |
94 (79.66) |
|
|
No |
27 (20.77) |
3 (25) |
24 (20.34) |
|
|
Compliance with Good
Handwashing Practices |
|
|
|
2.5470 |
0.111 |
Yes |
21 (16.15) |
0 (0.00) |
21 (17.80) |
|
|
No |
109 (83.85) |
12 (100.00) |
97 (82.20) |
|
|
3.2. Bivariate Analysis
In Tables 6-8 below, the variables significantly associated (p < 0.05) with acute malnutrition in children aged 6 to 59 months in the commune of Buhiga are: digestive disorders, compliance with the vaccination schedule, the father’s level of education, the mother’s level of education, the age of the child, the adapted latrine system, domestic violence, marital status, household size and frequency of meals eaten.
Table 6. Analysis of the association between acute malnutrition and sociodemographic factors of children aged 6 to 59 months in Buhiga commune of Karusi province.
|
|
Acute malnutrition |
|
|
|
Variable |
n (%) |
Yes |
No |
GOLD Raw |
95% CI |
p-value |
Marital Status |
|
|
|
|
|
|
Bachelor |
1 (0.77) |
0 (0) |
1 (0.85) |
- |
- |
- |
Married |
118 (90.77) |
9 (75.00) |
109 (92.37) |
1 (Ref) |
|
|
Divorced |
1 (0.77) |
0 (0) |
1 (0.85) |
- |
- |
- |
Cohabitation |
5 (3.85) |
2 (16.67) |
3 (2.54) |
8.07 |
[1.1; 54.7] |
0.032 |
Widower |
5 (3.85) |
1 (8.33) |
4 (3.39) |
3.02 |
[0.30; 30] |
0.344 |
Mother’s level of
education |
|
|
|
|
|
|
Without |
37 (28.46) |
8 (66.67) |
29 (24.58) |
1 (Ref) |
|
|
Primary |
72 (55.38) |
3 (25.00) |
69 (58.47) |
0.15 |
[0.03; 0.63] |
0.009 |
Secondary |
20 (15.38) |
1 (8.33) |
19 (16.1) |
0.19 |
[0.02; 1.65] |
0.132 |
University |
1 (0.77) |
0 |
1 (0.85) |
- |
- |
- |
Father’s level of
education |
|
|
|
|
|
|
Without |
22 (16.92) |
10 (83.33) |
12 (10.17) |
1 (Ref) |
|
|
primary |
94 (72.31) |
2 (16.67) |
92 (77.97) |
0.02 |
[0.005; 0.13] |
0.000 |
Secondary |
14 (10.77) |
0 (0.00) |
14 (11.86) |
- |
- |
- |
History of the first birth |
|
|
|
|
|
|
<18 years old |
9 (6.92) |
7 (58.33) |
2 (1.69) |
1 (Ref) |
|
|
Between 18 and 30 years old |
115 (88.46) |
3 (25.00) |
112 (94.92) |
0.007 |
[0.001; 0.05] |
0.432 |
30 years and older |
6 (4.62) |
2 (16.67) |
4 (3.39) |
0.142 |
[0.01; 1.4] |
0.675 |
Sex of the child |
|
|
|
|
|
|
Boy |
71 (54.62) |
6 (50.00) |
65 (55.08) |
1 (Ref) |
|
|
Daughter |
59 (45.38) |
6 (50.00) |
53 (44.92) |
1.22 |
[0.37; 4.02] |
0.736 |
Age of the child |
|
|
|
|
|
|
Between 6 and 12 months |
31 (23.85) |
7 (58.33) |
24 (20.34) |
1 (Ref) |
|
|
12 and 36 months |
18 (13.85) |
2 (16.67) |
16 (13.56) |
0.42 |
[0.07; 2.3] |
0.327 |
37 and 59 months |
81 (62.31) |
3 (25.00) |
78 (66.10) |
0.13 |
[0.03; 0.54] |
0.005 |
Reproductive interval respected |
|
|
|
|
|
|
No |
41 (31.54) |
10 (83.33) |
31 (26.27) |
1 (Ref) |
|
|
Yes |
89 (68.46) |
2 (16.67) |
87 (73.73) |
0.0712 |
[0.014; 0.34] |
0.322 |
Household size |
|
|
|
|
|
|
1 - 2 |
0 (0.00) |
0 (0.00) |
0 (0.00) |
- |
- |
- |
3 - 7 |
95 (73.08) |
2 (16.67) |
93 (78.81) |
1 (Ref) |
|
|
Over, from 7 |
35 (26.92) |
10 (83.33) |
25 (21.19) |
18.6 |
[3.8; 90.4] |
0.000 |
Religion |
|
|
|
|
|
|
Catholic |
90 (69.23) |
7 (58.33) |
83 (70.34) |
1 (Ref) |
|
|
Protestant |
22 (16.92) |
3 (25.00) |
19 (16.10) |
1.87 |
[0.44; 7.9] |
0.394 |
Anglican |
5 (3.85) |
1 (8.33) |
4 (3.39) |
- |
- |
- |
Muslim |
4 (3.08) |
0 (0.00) |
4 (3.39) |
2.96 |
[0.29; 30.2] |
0.359 |
Other |
9 (6.92) |
1 (8.33) |
8 (6.78) |
1.48 |
[0.16; 13.6] |
0.728 |
Birth order |
|
|
|
|
|
|
First child |
19 (14.62) |
2 (16.67) |
17 (14.41) |
1 (Ref) |
|
|
Other Rank |
111 (85.38) |
10 (83.33) |
101 (85.59) |
0.84 |
[0.16; 4.1] |
0.833 |
Table 7. Analysis of the association between acute malnutrition and morbidity factors in children aged 6 to 59 months in Buhiga commune of Karusi province.
|
|
Acute malnutrition |
|
|
|
Variable |
n (%) |
Yes |
No |
GOLD Raw |
95% CI |
p-value |
Digestive disorders |
|
|
|
|
|
|
Yes |
79 (60.77) |
3 (25.00) |
76 (64.41) |
1.18 |
[1.39; 21.14] |
0.01 |
No |
51 (39.23) |
9 (75.00) |
42 (35.59) |
1 |
|
|
Access to treatment |
|
|
|
|
|
|
Yes |
96 (73.85) |
10 (83.33) |
86 (72.88) |
1.86 |
[0.38; 8.95] |
0.43 |
No |
34 (26.15) |
2 (16.67) |
32 (27.12) |
1 |
|
|
Episode of diarrhea |
|
|
|
|
|
|
Yes |
88 (68.22) |
8 (66.67) |
80 (68.38) |
0.93 |
[0.3; 3.81] |
0.90 |
No |
41 (31.78) |
4 (33.33) |
37 (31.62) |
1 |
|
|
Presence of feverish peak |
|
|
|
|
|
|
Yes |
82 (63.08) |
8 (66.67) |
74 (62.71) |
0.84 |
[0.23; 2.95] |
0.78 |
No |
48 (36.92) |
4 (33.33) |
44 (37.29) |
1 |
|
|
Presence of chronic disease |
|
|
|
|
|
|
Yes |
122 (93.85) |
12 (100.00) |
110 (93.22) |
- |
- |
- |
No |
8 (6.15) |
0 (0.00) |
8 (6.78) |
1 |
|
|
Repeated pludism |
|
|
|
|
|
|
Yes |
81 (62.31) |
2 (16.67) |
79 (66.95) |
10.1 |
[2.1; 48] |
0.224 |
No |
49 (37.69) |
10 (83.33) |
39 (33.05) |
1 |
|
|
Repeated infection |
|
|
|
|
|
|
Yes |
41 (31.78) |
4 (33.33) |
37 (31.62) |
0.92 |
[0.26; 3.26] |
0.904 |
No |
88 (68.22) |
8 (66.67) |
80 (68.38) |
1 |
|
|
Table 8. Analysis of the association between acute malnutrition and behavioural and environmental factors.
|
|
Acute malnutrition |
|
|
|
Variable |
n (%) |
Yes |
No |
GOLD Raw |
95% CI |
p-value |
Knowledge of the
number of times
breastfed |
|
|
|
|
|
|
Yes |
113 (86.92) |
11 (91.67) |
102 (86.44) |
0.57 |
[0.06; 4.79] |
0.613 |
No |
17 (13.08) |
1 (8.33) |
16 (13.56) |
1 |
|
|
Types of care facilities attended |
|
|
|
|
|
|
Known health facilities |
106 (82.81) |
10 (83.33) |
96 (82.76) |
1 |
|
|
Use of community health workers |
22 (17.19) |
2 (16.67) |
20 (17.24) |
0.96 |
[0.19; 4.72] |
0.960 |
Frequency of meals
consumed |
|
|
|
|
|
|
1 meal per day |
16 (12.31) |
9 (75.00) |
7 (5.93) |
1 |
|
|
2 meals a day |
40 (30.77) |
3 (25.00) |
37 (31.36) |
0.06 |
[0.01; 0.29] |
0.000 |
3 meals a day |
64 (49.23) |
0 (0.00) |
64 (54.24) |
- |
- |
- |
4 meals a day |
10 (7.69) |
0 (0.00) |
10 (8.47) |
- |
- |
- |
Weaning age |
|
|
|
|
|
|
Before 6 months |
11 (8.46) |
1 (8.33) |
10 (8.47) |
1 |
|
|
6 months |
100 (76.92) |
10 (83.33) |
90 (76.27) |
1.11 |
[0.12; 9.60] |
0.924 |
After 6 months |
19 (14.62) |
1 (8.33) |
18 (15.25) |
0.55 |
[0.03; 9.87] |
0.689 |
Compliance with the vaccination schedule |
|
|
|
|
|
|
Yes |
14 (10.94) |
8 (66.67) |
6 (5.17) |
0.027 |
[0.006; 0.11] |
0.000 |
Name |
114 (89.06) |
4 (33.33) |
110 (94.83) |
1 |
|
|
Primary Household
Decision Maker |
|
|
|
|
|
|
Husband and wife
decide together |
104 (80.00) |
12 (100.00) |
92 (77.97) |
1 |
|
|
The husband
decides alone |
13 (10.00) |
0 (0.00) |
13 (11.02) |
- |
- |
- |
The woman decides alone |
13 (10.00) |
0 (0.00) |
13 (11.02) |
- |
- |
- |
Sources of income |
|
|
|
|
|
|
Agriculture |
100 (76.92) |
9 (75.00) |
91 (77.12) |
1 |
|
|
Agriculture and
livestock farming |
18 (13.85) |
3 (25.00) |
15 (12.71) |
2.02 |
[0.49; 8.33] |
0.330 |
Civil servants’ salaries |
11 (8.46) |
0 (0.00) |
11 (9.32) |
- |
- |
- |
Other |
1 (0.77) |
0 (0.00) |
1 (0.85) |
- |
- |
- |
Domestic violence |
|
|
|
|
|
|
Yes |
87 (66.92) |
5 (41.67) |
82 (69.49) |
3.18 |
[0.9; 10] |
0.061 |
No |
43 (33.08) |
7 (58.33) |
36 (30.51) |
1 |
|
|
Fitted latrine |
|
|
|
|
|
|
Yes |
17 (13.08) |
10 (83.33) |
7 (5.93) |
0.01 |
[0.002; 0.06] |
0.000 |
No |
113 (86.92) |
2 (16.67) |
111 (94.07) |
1 |
|
|
Compliance with Good Handwashing Practices |
|
|
|
|
|
|
Yes |
21 (16.15) |
0 (0.00) |
21 (17.80) |
- |
- |
- |
Name |
109 (83.85) |
12 (100.00) |
97 (82.20) |
1 |
|
|
Indeed
Children whose mothers are in common-law unions are 8.07 times more likely to develop acute malnutrition compared to children whose mothers have partners and are legally married.
Children whose mothers have at least a primary level of education are 85% less likely to develop acute malnutrition compared to children whose mothers’ level of education is not.
Children whose fathers have at least a primary level of education are 98% less likely to develop acute malnutrition compared to children whose fathers’ level of education is not.
Children aged between 37 and 59 months have an 87% lower risk of developing acute malnutrition compared to children aged between 6 and 12 months.
Children whose households have more than 7 members are 18.6 times more likely to develop acute malnutrition compared to children whose household members are between 1 and 2.
Children with digestive disorders are 5.42 times more likely to be attacked by acute malnutrition compared to children without digestive disorders.
Children who eat two meals a day are 94% less likely to develop acute malnutrition compared to children who eat one meal a day.
Children who have adhered to the immunization schedule are 99% less likely to develop acute malnutrition compared to children who do not adhere to the immunization schedule.
Children whose parents argue are 3.18 times more likely to develop acute malnutrition compared to children whose families are calm.
Children who belong to households with well-equipped latrines are less likely to develop acute malnutrition compared to children whose household latrines are in poor condition.
3.3. Multivariate Analysis
The following Table 9 shows the explanatory variables retained in a multivariate logistic regression model as significantly associated with acute malnutrition in the Buhiga commune.
All independent variables tested that had a significant influence on the rate of acute malnutrition in the bivariate analysis with a p < 5% (Marital status of the mother in a common-law union, mother’s level of education, father’s level of education, age of the child, household size, digestive disorders, frequency of meals consumed, adherence to the vaccination schedule, modified latrine) were taken and their association with the dependent variable (global acute malnutrition) was tested and eliminated confounding factors with p value > 5% (Mother’s level of education, father’s level of education, child’s age, digestive disorders, adherence to the vaccination schedule, adapted latrine) and remained with the variables significantly associated with acute malnutrition in children aged 6 - 59 months in the Buhiga commune of the Karusi Province with a p < 5% (frequency of meals consumed, household size, marital status of the mother in common-law union) which constitute the determinants of acute malnutrition in children aged 6 - 59 months in the Buhiga commune of the Karusi Province.
Table 9. Analysis of the association between acute malnutrition and the factors influencing it among children aged 6 to 59 months in the commune of Buhiga.
|
|
Acute malnutrition |
|
|
|
Variable |
n (%) |
Yes |
No |
Adjusted GOLD |
95% CI |
p-value |
Digestive disorders |
|
|
|
|
|
|
Yes |
79 (60.77) |
3 (25.00) |
76 (64.41) |
0.86 |
[0.029; 25] |
0.935 |
No |
51 (39.23) |
9 (75.00) |
42 (35.59) |
1 (Ref) |
|
|
Compliance with the vaccination schedule |
|
|
|
|
|
|
Yes |
14 (10.94) |
8 (66.67) |
6 (5.17) |
0.21 |
[0.001; 41] |
0.570 |
Name |
114 (89.06) |
4 (33.33) |
110 (94.83) |
1 (Ref) |
|
|
Father’s level of
education |
|
|
|
|
|
|
Without |
22 (16.92) |
10 (83.33) |
12 (10.17) |
1 (Ref) |
|
|
Primary |
94 (72.31) |
2 (16.67) |
92 (77.97) |
0.27 |
[0.017; 4.55] |
0.371 |
Secondary |
14 (10.77) |
0 (0.00) |
14 (11.86) |
- |
- |
- |
|
|
Acute malnutrition |
|
|
|
Variable |
n (%) |
Yes |
No |
Adjusted GOLD |
95% CI |
p-value |
Age of the child |
|
|
|
|
|
|
Between 6 and 12 months |
31 (23.85) |
7 (58.33) |
24 (20.34) |
1 (Ref) |
|
|
12 and 36 months |
18 (13.85) |
2 (16.67) |
16 (13.56) |
0.091 |
[0.0; 12] |
0.339 |
37 and 59 months |
81 (62.31) |
3 (25.00) |
78 (66.10) |
0.05 |
[0.001; 2] |
0.115 |
Well-appointed latrine |
|
|
|
|
|
|
Yes |
17 (13.08) |
10 (83.33) |
7 (5.93) |
0.038 |
[0.001; 1.15] |
0.061 |
No |
113 (86.92) |
2 (16.67) |
111 (94.07) |
1 (Ref) |
|
|
Marital Status |
|
|
|
|
|
|
Bachelor |
1 (0.77) |
0 (0) |
1 (0.85) |
- |
- |
- |
Married |
118 (90.77) |
9 (75.00) |
109 (92.37) |
1 (Ref) |
|
|
Divorced |
1 (0.77) |
0 (0) |
1 (0.85) |
- |
- |
- |
Cohabitation |
5 (3.85) |
2 (16.67) |
3 (2.54) |
34.9 |
[1.111; 1092] |
0.043 |
Widower |
5 (3.85) |
1 (8.33) |
4 (3.39) |
3.07 |
[0.002; 3779] |
0.757 |
Mother’s level of
education |
|
|
|
|
|
|
Without |
37 (28.46) |
8 (66.67) |
29 (24.58) |
1 (Ref) |
|
|
Primary |
72 (55.38) |
3 (25.00) |
69 (58.47) |
0.18 |
[0.02; 1.41] |
0.104 |
Secondary |
20 (15.38) |
1 (8.33) |
19 (16,1) |
0.09 |
[0.004; 1.9] |
0.126 |
University |
1 (0.77) |
0 |
1 (0.85) |
- |
- |
- |
Household size |
|
|
|
|
|
|
3 - 7 |
95 (73.08) |
2 (16.67) |
93 (78.81) |
1 (Ref) |
|
|
More than 7 |
35 (26.92) |
10 (83.33) |
25 (21.19) |
10.4 |
[1.72; 64] |
0.011 |
|
|
Acute malnutrition |
|
|
|
Variable |
n (%) |
Yes |
No |
Adjusted GOLD |
95% CI |
p-value |
Frequency of meals consumed |
|
|
|
|
|
|
1 meal per day |
16 (12.31) |
9 (75.00) |
7 (5.93) |
1 (Ref) |
|
|
2 meals a day |
40 (30.77) |
3 (25.00) |
37 (31.36) |
0.12 |
[0.02; 0.69] |
0.017 |
3 meals a day |
64 (49.23) |
0 (0.00) |
64 (54.24) |
- |
- |
- |
4 meals a day |
10 (7.69) |
0 (0.00) |
10 (8.47) |
- |
- |
- |
At the end of the analysis, logistic regression eliminated confounding factors. Variables with a significant p-value (<5%) and those with a p-value of less than 20% were integrated into the initial model with top-down elimination of variables with p > 0.05.
Thus, the variables with p < 0.05 at this stage are then significantly associated with acute malnutrition in children aged 6 to 59 months in the commune Buhiga and therefore constitute the determinants of acute malnutrition in children aged 6 - 59 months in the commune Buhiga, and it is the frequency of meals consumed (p = 0.017), household size (p = 0.011) and marital status (p = 0.043).
3.4. Statistical Analysis
During our study, 3 types of data analysis were performed:
Univariate analysis: This was a descriptive analysis of the independent variables in our sample: Descriptive analysis of socio-demographic factors, descriptive analysis of factors related to child morbidity, and descriptive analysis of behavioural and environmental factors.
Bivariate analysis: Each independent variable was cross-referenced with the dependent variable to see the factors (independent variables) that influenced the dependent variable.
Multivariate analysis: All independent variables tested that had a significant influence on the rate of acute malnutrition in the bivariate analysis with a p value < 5% (Marital status of the mother in a common-law union, Mother’s level of education, father’s level of education, Age of the child, household size, digestive disorders, frequency of meals consumed, adherence to the vaccination schedule, adapted latrine) were taken and their association with the dependent variable (global acute malnutrition) was tested and eliminated confounding factors with p value > 5% (mother’s level of education, father’s level of education, age of the child, digestive disorders, adherence to the vaccination schedule, adapted latrine) and remained with the variables significantly associated with acute malnutrition in children aged 6 - 59 months in the Buhiga commune of Karusi Province with a p value < 5% (frequency of meals consumed, household size, marital status of the mother in common-law union) which constitute the determinants of acute malnutrition in children aged 6 - 59 months in Buhiga commune of Karusi Province.
A database was built using Excel 2016 and the data was exported to STATA 15.1 for analysis. After the data was entered, the data was pre-processed to assess the quality of the information entered, including checking the normality of the data. If quantitative data were missing, they were replaced by the mean or median for variables with a normal and abnormal distribution, respectively. For qualitative data, they have been replaced by a frequent modality. Outliers were also corrected prior to the actual analysis.
Subsequently, the data analysis was carried out as follows:
For univariate (descriptive) analysis, the following measures were calculated: proportion for qualitative variables, mean and standard deviation for quantitative variables following a normal distribution; median and interquartile range for quantitative variables that do not follow a normal distribution.
In bivariate analysis, each independent variable was cross-referenced with the dependent variable. The exact Fisher test was used to test the significance of associations when at least one of the theoretical values was less than 5%, elsewhere the chi2 test was used. The odds ratio, p-value and 95% confidence interval were also calculated to test the statistical significance, meaning and strength of the associations of the observed differences between the proportions of the different modalities with respect to the dependent variable.
Multivariate analysis: Logistic regression was applied and eliminated confounding factors. Variables with a significant p-value (<5%) and those with a p-value of less than 20% were integrated into the initial model with top-down elimination of variables with p > 0.05.
After modelling, the best model with a low CSA was selected as containing variables considered to be factors influencing the occurrence of acute malnutrition in children aged 6 to 59 months in the commune of Buhiga. Only variables of which p < 0.05, at this stage, have been taken as the determinants of acute malnutrition.
Finally, a ROC curve was used to discriminate between children aged 6 to 59 months with acute malnutrition and those without acute malnutrition.
At the end of the analysis, the variables significantly associated (p < 0.05) with acute malnutrition among children aged 6 to 59 months in the commune of Buhiga were the frequency of meals consumed, household size and marital status (Figure 4).
Figure 4. ROC curve.
The graph above shows the ROC curve obtained from the results of the final model. The area under the ROC curve is 0.8627. The model’s ability to correctly classify observations is 86.2%. We can conclude that this model has predictive power, with very good discrimination.
4. Discussion of the Results
The objective of our study was to contribute to the identification of the determinants of acute malnutrition in children aged 6 to 59 months in the Buhiga commune of the Karusi Province in Burundi.
In our study, the prevalence of malnutrition in children aged 6 - 59 months is 9.23%. This prevalence is higher than the national prevalence obtained in the SMART 2022 survey, which is 6.4%.
It is much lower than that found in Libela Town (Yalew, 2014) which is 30.9%, lower than that found in Cameroon which is 26.8% (p = 0.000) (Tchuente et al., 2024), Close to that found in Ethiopia 14.89% (95% CI, p = 13.9 - 15.9) (Daniel et al., 2019), too close to that found in GASOGWE which is 7.3% (Favina, 2024).
In this study, 3 factors were recognized as predictors of acute malnutrition in children aged 6 to 59 months in the commune of Buhiga: The frequency of meals consumed (p = 0.017), the size of the household (p = 0.011) and the marital status (p = 0.043).
In our study, marital status was identified as a factor associated with acute malnutrition. The results show that children born to common-law mothers are 34.9% more likely to develop acute malnutrition than those born to married mothers.
In addition, meal frequency has also been found to be associated with acute malnutrition. The results of the study show that children who eat two meals a day are 88% less likely to develop acute malnutrition compared to children who eat one meal a day.
Finally, household size has also been identified as a factor associated with acute malnutrition. The more people there are to feed, the more difficult it can be to provide enough food for everyone. The results show that children who are raised in a multiple family with a high sibling group (>7 members) are 10.4% more likely to develop acute malnutrition than those raised in a smaller family with few people (between 3 and 7).
These findings are consistent with previous research on acute malnutrition. For example, a study conducted in several developing countries showed that lack of access to adequate food was a significant risk factor for acute malnutrition (Ivers & Neufeld, 2017). Another study showed that marital status (common-law union) is a significant risk factor for malnutrition in children aged 6 - 59 months (Olivier et al., 2018).
In addition, other studies have highlighted the importance of meal frequency in preventing acute malnutrition in children.
In addition, a study conducted in Niger showed that household size was an important factor in acute malnutrition among children (Alisha et al., 2017).
Finally, this study highlights several factors associated with acute malnutrition, including marital status, frequency of meals, and household size. These findings are consistent with previous research on acute malnutrition and highlight the importance of considering these factors when developing nutrition programs to better target those at risk and implement effective interventions.
5. Conclusion
The issues of health in general and nutrition in particular are nowadays inseparable from the global choices made within the framework of the development programs initiated and implemented by international organizations and public authorities in sub-Saharan Africa. These issues are mainly based on improving the quality of life of the population. A healthy population in adulthood necessarily requires better nutrition in childhood.
Most previous studies have shown the impact of a number of factors that combine to act on nutritional status. Prevention and awareness-raising actions in communities are hampered by a context marked by poverty, problems of poor health, hygiene and sanitation coverage and low literacy rates in rural areas.
In view of the above, the objective of this study is to research the determinants of malnutrition among children aged 6 to 59 months in Buhiga commune of the Karusi Province.
1) To show the prevalence of acute malnutrition among children aged 6 to 59 months in the commune of Buhiga.
2) To analyze the link between sociodemographic factors, factors related to child morbidity, behavioral and environmental factors and the occurrence of acute malnutrition in children aged 6 to 59 months in the commune of Buhiga.
3) Identify the factors associated with acute malnutrition in children aged 6 to 59 months in the Buhiga commune.
4) Propose exit routes to fight against acute malnutrition among children aged 6 to 59 months in the commune of Buhiga.
The frequency of meals consumed per day, household size and marital status (common-law union) are the predictive factors of malnutrition among children aged 6 - 59 months in the Buhiga commune of the province of Karusi.
Most malnourished children are born to young mothers in common-law unions who do not have stable partners and are therefore unable to contribute to their daily household expenses or to support themselves in relation to feeding their children. The quality and frequency of food consumed per day is a crucial problem, as the diet is not varied and often insufficient due to the overcrowding of people to feed in the household. The affordability of food products also remains a concern. It is linked to high production costs vis-à-vis a population whose purchasing power is increasingly eroded over time. In rural areas in particular, it is recognized that poverty has a direct influence on food insecurity and in turn on the nutritional status of the youngest.
6. Suggestions
The prevalence of malnutrition is still a concern that requires a continuous and large-scale mobilization of the State and its partners, who must consequently adopt new strategies to better manage the nutritional situation of children.
We suggest the following recommendations:
At the political and programmatic level:
Every health facility throughout the country should be equipped with a service that provides nutritional assistance.
Strengthen nutrition education in formal primary education and develop a policy to ensure that girls have at least one level of education that would improve the nutritional status of children in the long term.
In the implementation of IEC activities, improve household nutrition behaviours. To promote education for the health of families on the nutritional value of food and on a balanced diet of sufficient quality and quantity.
Improve the geographical coverage of poverty reduction actions and strengthen activities in rural areas. Promote income-generating activities in families so that they can have enough to eat by grouping them in associations and granting them collective credits.
Provide additional meals per day for children under 5 years of age in families (more than 3 meals per day) if possible.
Promote family planning.
Integrate sexual health sex education sessions for young people into health care settings.
Advise free women with multiple sexual partners to always practice safe sex.
Educate girls of childbearing age on the need for sexual abstinence before marriage in order to avoid unwanted pregnancies.
At the scientific level:
Promote biodemographic research based on child growth aimed at establishing a standard for measuring the nutritional status of children in each health care setting.
This reference will make it possible to take into account purely national specificities in the construction of anthropometric indicators for future studies on child malnutrition.
It would be interesting for future studies to collect information on the duration of breastfeeding, the birth interval, the use of health centres (prenatal visits by the mother for all births under five years of age), and the birth order of the child.