The aim of study is to compare the risk factors of malaria in children under the age of five years old in Uganda and Kenya. Secondary data from the Uganda Malaria Indicator Survey 2014–2015 and Kenya Malaria Indicator Survey 2015 was used. A descriptive summary, Pearson chi-square test and logistic regression were used as methods of analysis. In Uganda, Children below five years old aged between 48 and 59 months were more likely to test positive for Malaria compared to those aged between 0 and 11 months (OR = 3.26; CI = 2.420–4.389). Similarly, in Kenya with (OR = 6.77; CI = 2.782–16.458). Also, in Uganda, the category of residence of the child had a significant association with the risk of malaria (OR = 2.25; CI = 1.453–3.498). In relation to region, in Uganda, children from East central region of Uganda (OR = 4.13; CI = 2.579–6.627), North east region of Uganda (OR = 2.15; CI = 1.364–3.387) and West Nile region (OR = 2.48; CI = 1.451–4.235) were more likely to have malaria compared to children from Central 1 while in Kenya, children from North Eastern (OR = 0.06; CI = 0.008–0.487) and Eastern (OR = 0.03; CI = 0.004–0.249) regions were less likely to experience malaria compared to children from Coast region. The study recommends that both Governments of Uganda and of Kenya through their respective Ministries of Health should intensify the health education programs specifically targeting pregnant women and mothers with children under five years of age to educate them on the measures for preventing malaria in children under five years
Research Article
A comparative analysis of the risk factors of Malaria in Children under age of five years in Uganda and Kenya
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Children
Malaria
Risk factors
Uganda
Kenya
Malaria is a life-threatening disease caused by protozoan parasites of the genus Plasmodium that are transmitted to humans through the bites of infected Anopheles mosquitoes [6]. UNICEF proclaimed malaria as the leading killer of children under five years worldwide, with malaria incidence estimated at 219 million and deaths reported at approximately 660,000 in 2010. Almost 90% of these deaths occur in Sub-Saharan Africa (SSA), of which 91% are children under five. Children between three months and five years of age are most susceptible to malaria due to waning of their natural immunity from maternal antibodies and an acquired immunity that has not fully developed. Among those who survive, many are left with persistent anemia, impaired brain function and/or paralysis hampering physiology and cognitive development [2, 19].
Considering the East African Community countries, Uganda has the large malaria burden compared to other [19]. Uganda’s health system comprises the public, private not-for-profit, and private for-profit sectors. The public sector has village health teams (VHTs) that treat children less than five years of age for malaria, pneumonia, and diarrhea. These VHTs also participate in all health promotion programs such as immunization, family planning, and long-lasting insecticidal mosquito net (LLIN) distribution campaigns [20].
In East Africa, malaria transmission has also been seen particularly in the highlands, there are areas of low and high transmission, with a potential for epidemics. Although transmission occurs year-round, there is seasonal variation in the transmission intensity. Peak transmission occurs at the end of the rainy seasons and approximately four weeks after the end of rains in different geographic areas of a given country [3].
Uganda has the sixth highest number of annual deaths from malaria in Africa [4]. In addition, malaria has an indirect impact on the economy and development in general. The socio-economic impact of malaria includes out-of-pocket expenditure for consultation fees, drugs, transport and subsistence at a distant health facility. These costs are estimated to be between USD 0.41 and USD 3.88 per person per month (equivalent to USD 1.88 and USD 26 per household). Household expenditure for malaria treatment is also a high burden to the Ugandan population, consuming a larger proportion of the incomes in the poorest households [17].
In Kenya, malaria remains a major cause of morbidity and mortality with more than 70 percent of the population at risk of the disease [4, 17]. The malaria burden in Kenya is not homogenous. The areas around Lake Victoria and on the coast present the highest risk, and children under age 5 and pregnant women are the most vulnerable to infection. Kenya’s 2014 population is estimated at 44.9 million people, with an estimated population growth of 2.6% per year; thus, Kenya’s 2017 population is projected to be 48.5 million. Of the total population, children under age 5 account for 16% and children under age 15 account for 42% [15,18].
Although both the Government of Uganda and Kenya remains committed to improving health service delivery and places a high priority on malaria prevention and control measures, there is still a notably high number of children under five dying from malaria daily [14, 2]. The main objective of the study was to compare the risk factors of malaria in children under the age of five years old in Uganda and Kenya, specifically, to examine the socio- demographic, economic, and environmental predictors of malaria status in children under the age of five years old in both countries
2.1 Data source
The data source was secondary data drawn from the Uganda Malaria Indicator Survey (UMIS) 2014-2015 and Kenya Malaria Indicator Survey (KMIS) 2015.
2.2 Scope of the study
For Uganda
All women age 15-49 Years who were either permanent residents of the households in the 2014-15 UMIS sample or visitors present in the households on the night before the survey were eligible to be interviewed and were included in the study. In addition, all children age 0-59 months that were either permanent residents of the households in the sample or visitors present in the households on the night before the survey were eligible to be tested for malaria. A sample of 4,939 children below the age of Five years old was tested for Malaria and was considered in this study.
For Kenya
The study considered women age 15-49 Years that were eligible for the individual interview and children age 6 months to 5 years who were eligible for Malaria testing. A sample of 3,442 children below the age of Five years old was tested for Malaria and was considered in this study
2.3 Study Variables:
Malaria status of children under the age of 5 years old was the dependent variable. The independent variables that were considered in this study comprised of a number of socio-demographic, economic, and environmental factors.
2.4 Data Analysis
This sub section provides a detailed narrative of how the univariate, bivariate and multivariate analysis was conducted. Under univariate analysis, a descriptive summary of the different socio-demographic, economic, and environmental factors was undertaken using frequency distributions and summary statistics in order to explain the data. Bivariate analysis showed the association/differentials between socio-demographic, economic, and environmental factors and malaria status. This was done using Pearson chi square test statistic. The test statistic was as follows
Oij is the observed frequency (the observed counts in the cells), Eij is the expected frequency if no relationship existed between the variables, r is the number of categories of the independent variable and i is the number of categories of the dependent variables. The association was established at 95% confidence level where 0.05 less or equal was considered to be significant. At multivariate analysis, a binary logistic regression model was used to establish the relationship between a binary dependent variable (a child’s malaria status) and a set of explanatory variables. The logistic regression is stated as
This section discusses the distribution of socio-demographic and economic factors of respondents both in Uganda and Kenya.
Socio-demographic, and economic factors of respondents in both Uganda and Kenya
The socio-demographic and economic factors considered in this study were: Sex of the child, Age of the child, Age of the head of household, Sex of the head of household, Category of Residence of the child, Mother’s level of Education, having a bicycle, television, radio, and a mosquito net. Type of roof and source of drinking water. Table 1 presents the distribution of children under the age of five years old by selected characteristics in the two malaria indicator surveys of Uganda and Kenya.
In Table 1, most of the children under the age of five years old in both countries live rural areas. Uganda has more children in rural areas compared to Kenya (an upward difference of 24 units) while Kenya has more children who live in urban areas than Uganda (a downward difference of 24 units). In relation to gender of the children, there is a -1.5% difference in male children implying that Kenya had more male children who were below the age of five years old compared to Uganda and there is an upward difference of 1.5 in female children implying that Uganda had more female children below the age of five years old compared to Kenya.
In terms of Age of the child, Table 1 shows that there were more children aged between 0-11 months and between 24-47 months in Uganda (both age groups have a positive % difference) compared to those aged between 0-11 months and between 24-47 months in Kenya. Furthermore, there were more children aged between 12-23 months and between 48-59 months in Kenya (both age groups have a negative % difference) compared those children who fall in those same age groups in Uganda.
With regards to age of the mother/ Care giver, Table 1 indicate a 0% difference implying that both countries Uganda and Kenya had the same Mothers / care givers whose age were equal or above 60 years old. A 1% difference for the age group 15-29 years and a 2% difference for the age group 45-29 imply that Uganda had more mothers /care givers in those age groups compared to Kenya while a -3% difference for the age group of 30-44 years indicate that Kenya had more mothers/ caregiver in that age group compared to Uganda
Table 1 further shows that more households of children under the age of five years old are headed by male in Uganda compared to Kenya (10% difference) while in Kenya, more females head the households compared to Uganda (-10% difference). With regards to the educational level of the mother/ Care giver, Table 1 indicates that Uganda had of 10% and 1% respectively compared to Kenya. On the other hand, Uganda had less mothers /caregivers who attained secondary level of education (-5%) and Tertiary level of education (-6%) compared more mothers / caregivers who had primary education and no education with a percentage difference to Kenya.
Furthermore, Table 1 indicates that children under the age of five years old whose households had a radio (-3%), Electricity (-12%) and a Television (-15%) where less in Uganda compared to Kenya while household which had a bicycle (21%), and a mosquito net (23%) where more in Uganda compared to Kenya. Also, Uganda had more improved sources of drinking water (11%) compared to Kenya. It also had more households with modernized roofing material (23%) compared to Kenya.
Environmental factors
Table 2: Environmental factors of respondents in both Uganda and Kenya
|
Uganda, n=4939 |
Kenya, n=3442 |
|||
|
Characteristic |
Percentage |
Characteristic |
Percentage |
% Difference |
|
|
|
|
||
|
Cluster Altitude |
Cluster Altitude |
|
||
|
<1000 Meters |
7 |
<1000 Meters |
29 |
-22 |
|
1000-1500 Meters |
80 |
1000-1500 Meters |
27 |
53 |
|
1501-2000 Meters |
11 |
1501-2000 Meters |
31 |
-20 |
|
<2500 Meters |
2 |
<2500 Meters |
13 |
-11 |
|
Region |
Region |
|
||
|
Central 1 |
7 |
Coast |
16 |
-9 |
|
Central 2 |
7 |
North Eastern |
8 |
-1 |
|
East Central |
9 |
Eastern |
12 |
-3 |
|
Kampala |
5 |
Central |
7 |
-2 |
|
Mid North |
16 |
Rift Valley |
31 |
-15 |
|
Mid-Western |
10 |
Western |
11 |
-1 |
|
Mid-Eastern |
10 |
Nyanza |
13 |
-3 |
|
North East |
19 |
Nairobi |
2 |
17 |
|
South Western |
9 |
|
|
|
|
West Nile |
8 |
|
|
|
Table 2 indicates that Uganda had less households of children below the age of five years old which were in clusters with altitude less than 1000 meters (-22%), between 1501 and 2000 meters (-20%) and less than 2500 meters (-11%) compared to Kenya. On the other hand, Uganda had more households of children below the age of five years old which were in clusters with altitude between 1000 and 1500 meters (53%) compared to Kenya
In terms of Regions, North East Uganda had the majority of children under the age of five years old (19%) and Kampala which is the capital city of Uganda had the least percentage of children under the age of five years old (5%) while in Kenya, The Rift Valley Region had the majority of children under the age of five years old (31%) and Nairobi which is the capital city of Kenya had the least percentage of children under the age of five years old (2%) as shown in Table 2
Prevalence of Malaria among children under 5 years old both in Uganda and Kenya
According to Table 3, in Uganda, the number of children less than five years of age tested for malaria in this study was 4939 children. Of these children, 974 (20%) tested positive for malaria, while in Kenya, the number of children less than five years of age tested for malaria in this study was 3442 children. Of these children, 180(5%) tested positive for malaria.
Table 3: Malaria status of children under 5 years old in both Uganda and Kenya
|
Country |
Total number of Children |
Prevalence of Malaria |
|
Uganda |
4939 |
974 (20%) |
|
Kenya |
3442 |
180 (5%) |
Association between socio-demographic, economic, environmental factors and malaria status of children under five years old
The association between each of the independent variable and malaria status of children below the age of five years was obtained. The p-values were compared with 0.05 and those variables that were found to be having less than 0.05 were considered to have significant association, otherwise insignificant as shown in Table 4 and 5.
From Table 4, the association between gender of the child, gender of head of household and malaria status were insignificant in both Uganda and Kenya with P- Value greater than 0.05 (P>0.05) while age of the child was significant in both Uganda and Kenya with Uganda having more children between the age of 0-11 months having malaria. In addition, Table 4 showed that age of the head of the household was associated with Malaria status only in Uganda while Ownership of Mosquito net was associated with Malaria status only in Kenya. The associations were statistically significant (P<0.05). The association between a mother’s education level and a Malaria status was significant in both Uganda and Kenya. Furthermore, Mother’s with primary, secondary and tertiary level of education in Uganda had fewer children under the age of five years old testing positive compared to Mothers in Kenya with the same educational level.
Furthermore, from Table 4, category of residence (P<0.05) was significantly associated malaria status where by children who reside in Rural areas in Uganda had more children testing positive for malaria compared to those children in Kenya who reside in rural areas. Household items such as Radio, Television and Electricity were significantly associated with malaria status both in Uganda and Kenya (P<0.05). Household with Radio, Television and Electricity in Uganda had less (Negative % difference) children testing positive for malaria compared to households in Kenya which had those same items.
According to Table 5, cluster altitude and region (P<0.05) were significantly associated malaria status of children in Uganda and Kenya. Children living in areas with cluster altitude below 1000 meters in Uganda had less cases of malaria compared to children who live in areas below 1000 meters in Kenya. In addition, children living in areas with cluster altitude above 2500 meters in Uganda had more cases of malaria compared to children below five years old in Kenya who live in areas below 2500 meters.
Determinants of malaria status of children under the age of five years in both Uganda and Kenya
Table 6 shows the determinants of malaria status in children under the age of five years old between Uganda and Kenya. Results in Table 6 indicate that malaria in children under the age of five years old increased with Age of the child in months whereby the older the child, the higher the odds of getting malaria. In Uganda, Children below five years old aged between 48 and 59 months were more likely to test positive for Malaria compared to those aged between 0 and 11 months (OR=3.26; CI =2.420-4.389). Similarly, in Kenya, children aged between 48 and 59 months were more likely to test positive for Malaria compared to those aged between 0 and 11 months (OR= 6.77; CI=2.782-16.458)
Again, from Table 6, in Uganda, the category of residence of the child had a significant association with the risk of malaria where by a child who resides in a rural area was more likely to be at risk of getting malaria compared to a child who resides in an urban area (OR=2.25; CI=1.453-3.498). Mother's Educational Level/ caregiver educational level predicted malaria Status only in Uganda where by, children below five years old whose caregivers/ mothers attended secondary education and Tertiary education were less likely to experience malaria compared to children below five years old whose caregivers/mothers have never gone to school (Had no education). (OR=0.71; CI=0.584 - 0.860).
In addition, results in Table 6, also indicated that children below the age of five years old from households which had a radio in Uganda were 2.25 times more likely to experience malaria compared to those children who were from households without a radio. In addition, children below the age of five years old from households with electricity in Uganda were 0.61 times less likely to experience malaria compared to those children who were from households without electricity. In Kenya, children below the age of five years old from households which had a television set were 0.32 times less likely to experience malaria compared to those children who were from households without a Television.
Furthermore, Table 7 shows region as a determinant of malaria status of children under the age of five years both in Uganda and Kenya.
Table 7: Region as a determinant of malaria status of children under the age of five years in both Uganda and Kenya
|
Characteristic |
OR |
p-value |
95% CI |
|
|
Region in Uganda, n=4939 |
|
|
|
|
|
Central 1* |
|
|
|
|
|
Central 2 |
1.67 |
0.052 |
0.995 |
2.804 |
|
East Central |
4.13 |
0.000 |
2.579 |
6.627 |
|
Kampala |
0.14 |
0.060 |
0.018 |
1.087 |
|
Mid North |
1.05 |
0.849 |
0.651 |
1.686 |
|
Mid-Western |
1.37 |
0.206 |
0.841 |
2.231 |
|
Mid-Eastern |
1.13 |
0.632 |
0.677 |
1.899 |
|
North East |
2.15 |
0.001 |
1.364 |
3.387 |
|
South Western |
0.43 |
0.012 |
0.219 |
0.827 |
|
West Nile |
2.48 |
0.001 |
1.451 |
4.235 |
|
Region in Kenya, n=3443 |
|
|
|
|
|
Coast* |
|
|
|
|
|
North Eastern |
0.06 |
0.008 |
0.008 |
0.487 |
|
Eastern |
0.03 |
0.001 |
0.004 |
0.249 |
|
Central |
1.00 |
|
|
|
|
Rift Valley |
0.48 |
0.185 |
0.161 |
1.423 |
|
Western |
1.50 |
0.467 |
0.500 |
4.524 |
|
Nyanza |
1.95 |
0.222 |
0.668 |
5.711 |
|
Nairobi |
1.00 |
|
|
|
Notes: The symbol * denotes the reference category and the level of significance was determined at P<0.05
In relation to region, in Uganda, children below five years old from East central region of Uganda (OR=4.13; CI=2.579 - 6.627), North east region of Uganda (OR=2.15; CI=1.364 -3.387) and West Nile region of Uganda (OR=2.48; CI=1.451 - 4.235) were more likely to have malaria compared to children below five years old who from Central 1 region of Uganda. Furthermore, children below five years old from South western region of Uganda (OR=0.43; CI=0.219 – 0.827) were less likely to have malaria compared to children below five years old who from Central 1 region of Uganda. On the other hand, in Kenya, children below five years old coming from North Eastern (OR=0.06; CI= 0.008 – 0.487) and Eastern (OR=0.03; CI=0.004 – 0.249) regions of Kenya were less likely to experience malaria compared to children below five years old who were from Coast region Kenya.
The study results show that age of the child had a significant effect on malaria status of children under the age of five years old. This finding is in line with a study conducted in north-east Tanzania by Winskill et al., 2011 which highlighted that the age of the child had a significant risk factor of malaria in children. The study result is also in agreement with the study conducted by [8] which concluded that older children aged 24-35, 36-47 and 48 months and above were more likely to have malaria as compared to the younger age group 6-11 months respectively. Furthermore, the study has revealed that the older the child, the higher the risk of getting malaria. This is in agreement with the study done by [7].
However, Gender was found to be insignificant in this study, with the distribution of malaria prevalence being almost the same for both male and females, which is consistent with the study carried out by [2] which found out that Gender was not a significant variable for explaining the prevalence of malaria infection. This is also in agreement with the study carried out by [1].
Adequate knowledge of malaria prevention and control can help in reducing the growing burden of malaria among vulnerable groups, particularly pregnant women and children aged under 5 years living in malaria endemic settings. The findings of the study done by [5] indicated that socio-demographic factor such as educational status greatly influence knowledge on malaria prevention and control measures. This finding is in agreement with the results of this study which found out that mother’s educational level had a significant effect on malaria status of children under the age of five years old
The Ownership of a mosquito net in the household, whether or not the bed net was treated, was insignificantly associated with a child’s malaria status. These results are in agreement with those found by [4]. However, they conflict the study conducted in Ghana by [15] which found out that ownership of mosquito net was a key determinant or predictor of malaria cases among under-five children. They also conflict with the study conducted by [14] which demonstrated that ownership of mosquito net is strongly associated with risk of malaria. This observed lack of association could possibly be attributed to an inconsistent or inappropriate use of the nets or perhaps a child was exposed to mosquito bites during other times of the day or evening when the net was not in use.
The type of place of residence (urban versus rural) had a significant association with the risk of malaria, in agreement with the study conducted by [12,16] which found out that that residing in rural areas (versus urban) increased malaria incidence rates by over three-fold and mean indoor female A. gambiae and funestus numbers by nearly two-fold. Compared to those residing in the lowest quality houses, children residing in the highest quality houses had one-third lower malaria incidence rates, even when wealth and rural residence were controlled for. Living in the highest quality houses reduced vector numbers while having cattle near the house significantly increased them. This was also in line with the study conducted in Ghana by [15] which highlighted that Variation in the rural-urban dichotomy showed that the proportion of children with malaria from the rural areas was 21 percent and that for children from the urban areas was 19 percent.
Furthermore, availability of a radio, electricity, television had a significant effect on malaria status of children under the age of five years old. This is in line with the findings from the study done by [13] which noted the important role poverty may play as a risk factor for malaria infection. It is also in agreement with the work done by [9] which found out that malaria is indeed a cause of poverty among different communities and countries.
The study results show that region of the child had a significant effect on malaria status of children under the age of five years old. This finding is in line with a study conducted in Ghana by [12] which revealed that region was a key predictor of malaria cases among under-five children. In addition, cluster attitude was found to be insignificant, which is inconsistent with the findings of the study by [10, 11] which revealed that altitude remained significantly associated with incidence of Anopheles thus the incidence of malaria.
The study explored the risk factors of malaria infections in children under the age of five years old and found out that Age of a child in months and region had an effect on Malaria risk of children under the age of five years old in both Uganda and Kenya. Residence of a child, having Radio, having electricity and mother’s educational level had an effect on Malaria risk of a child under the age of five years old in only Uganda while having a Television had an effect on malaria risk of a child under the age of five years old in only Kenya. Age of the household head had no effect on Malaria risk of a child under the age of five years old in both Uganda and Kenya. Based on the findings of the study, the researcher recommends that:
The Government of Uganda and the Kenyan government through their respective Ministries of Health should intensify the health education programs specifically targeting pregnant women and mothers with children under five years of age to educate them on the measures for preventing malaria in children under five years since mothers/care givers have a vital role to play in prevention of malaria and as such, they should be given adequate knowledge particularly knowledge of practicing safe living habits, such as reducing outdoor activities during peak biting hours of a mosquito, can go a long way in aiding the reduction of the burden of malaria in children under the age of five years old
The National Malaria Control Program in the ministry of health should liaise with the Uganda Communications Commission (UCC) to ensure that forums such as the mass media are used to educate communities especially in rural areas about the measures of preventing Malaria in children under the age of five years old. In addition, local community radios should be rejuvenated as they are a key communication tool.
Ethics approval and consent to participate
One of the researchers on the team, applied for Demographic and Health Surveys (DHS) dataset. Authorization was given, and reference to complete terms of use was obtained from https://dhsprogram.com/Data/terms-of-use.cfm. Then, the researcher used the username, email address, and password used during registration to access the requested dataset. Attached is the authorization letter from DHS. Any person interested in using this same dataset can easily request it from [email protected]
Consent for publication
Not Applicable
Availability of data and materials
The dataset is available upon request from the DHS program using this email [email protected]
Competing interests
The authors declare that they have no competing interests.
Funding
The author(s) reported there is no funding associated with the work featured in this article.
Authors' contributions
Hellen Namawejje, Kato Richard, and Leonard K. Atuhaire designed and implemented the study. Hellen Namawejje and Kato Richard performed the data analysis, developing tables, data summarization. Leonard K. Atuhaire supervised the work and supported in writing of the article plus the rest of the team.
Acknowledgements
Not Applicable
Authors’ information
Hellen Namawejje is a lecturer in the Department of Statistical Methods and Actuarial Science, School of Statistics and Planning, Makerere University.
Kato Richard is a master’s student of Master of Statistics in the Department of Statistical Methods and Actuarial Science, School of Statistics and Planning, Makerere University.
Leonard K. Atuhaire is an associate professor in the Department of Applied Statistics and Planning, School of Statistics and Planning, Makerere University.
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- USAID, Malaria Control in Complex Emergencies - An Inter-Agency Field Handbook, 2015. https://doi.org/http://helid.digicollection.org/en/d/Js13424e/1.html
Table 1,4,5, and 6 are available in the Supplementary Files section.
No competing interests reported.