Association between maternal level of education and the

treatment with antimalarial drugs in children under the

age of 5 in Nigeria A cross-sectional study

Julia Cederlund

____________________________________________ Master Degree Project in Global Heath, 30 credits. Spring 2020

International Maternal and Child Health (IMCH)

Department of Women’s and Children’s Health

Supervisor: Shirin Ziaei

Word Count: 10,386

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Abstract Background

Malaria is a major threat to global public health, with adverse health effects. Nigeria alone

accounts for 25% of the global burden of malaria. Children are especially vulnerable to

malaria, and if the disease is not treated it could have fatal consequences. Mothers have an

important role in ensuring that adequate and timely treatment is given to the child.

Aim

The aim of this study was to investigate whether there was an association between maternal

level of education and the treatment with antimalarial drugs in malaria positive children

under-5 in Nigeria.

Methods

This study was a cross-sectional study that utilized Demographic and Health Surveys (DHS)

data from the 2015 Nigeria Malaria Indicator Survey. Data on 2’622 malaria positive children

were used, and a logistic regression analysis was conducted to determine the association with

maternal level of education.

Results

The mothers with a higher level of education had two times higher odds (OR 2.31, CI 1.62-

3.32) of making sure their child received treatment with antimalarial drugs, compared to the

mothers with no education. With an increase of 38% (OR 1.38, CI 1.11-1.71) in the odds for

the child receiving treatment with antimalarial drugs if the mother has primary education and

an increase of 51% (OR 1.51, CI 1.24-1.84) if the mother has secondary education compared

to mothers with no education.

Conclusion

Mothers with a higher level of education waere more likely to make sure that their child

received treatment with antimalarial drugs, compared to the mothers with no education.

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Table of contents Abstract ...................................................................................................................................... 2

1. Introduction ............................................................................................................................ 5

1.1 Transmission of malaria ................................................................................................... 5

1.1.1 Determinants of transmission .................................................................................... 5

1.1.2 Preventing transmission ............................................................................................ 7

1.2 Malaria symptoms ............................................................................................................ 7

1.3 Malaria diagnosis ............................................................................................................. 8

1.4 Malaria treatment ............................................................................................................. 9

1.5 Factors that influence the malaria treatment .................................................................. 10

1.6 Malaria burden in Nigeria .............................................................................................. 11

1.6.1 Malaria in children under-5 in Nigeria .................................................................. 12

1.6.2 Education and knowledge about malaria in Nigeria .............................................. 13

1.7 Justification and research aim ........................................................................................ 14

2. Methods ................................................................................................................................ 15

2.1 Study design ................................................................................................................... 15

2.2 Study population ............................................................................................................ 15

2.3 Study setting ................................................................................................................... 15

2.4 Sample size/selection ..................................................................................................... 17

2.5 Data collection ................................................................................................................ 17

2.6 Methods and variables .................................................................................................... 18

2.7 Statistical analysis .......................................................................................................... 19

2.7.1 Descriptive analysis ................................................................................................ 19

2.7.2 Bivariate analysis .................................................................................................... 19

2.7.3 Multivariate analysis ............................................................................................... 19

2.8 Ethical consideration ...................................................................................................... 20

3. Results .................................................................................................................................. 21

3.1 Characteristics of the study population .......................................................................... 21

3.2 Bivariate analyses to evaluate association between the outcome and exposure variables

and the background characteristics ...................................................................................... 23

3.3 Regression analyses evaluating the association between maternal level of education and

antimalarial treatment in their children under-5 in Nigeria .................................................. 25

4. Discussion ............................................................................................................................ 28

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4.1 Main findings ................................................................................................................. 28

4.2 Impact of maternal level of education on the treatment with antimalarial drugs in

children under-5 ................................................................................................................... 28

4.3 Background characteristics role in the treatment with antimalarial drugs in children

under-5 ................................................................................................................................. 31

4.4 Strengths and limitations ................................................................................................ 33

4.4.1 Strengths .................................................................................................................. 33

4.4.2 Limitations ............................................................................................................... 33

5. Conclusion ............................................................................................................................ 35

6. Acknowledgement ................................................................................................................ 36

References ................................................................................................................................ 37

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1. Introduction Since 2000 the malaria incidence has declined globally. Despite that almost half of the

world’s population is currently at risk of being infected with malaria (1), and there is an

estimate of malaria related deaths between 0.7 and 2.7 million deaths per year (2). The highest

burden of malaria is in sub-Saharan Africa, which accounts for nearly 89 percent of the global

malaria cases (1). Children under the age of 5 are the most vulnerable group, and in 2018

children accounted for 67 percent of all malaria related deaths (3). Although malaria can be

fatal it is largely preventable and a highly treatable disease, and early diagnosis and adequate

treatment is key (4). The formal education plays a role in the knowledge about malaria and

ensures timely and adequate treatment. Therefore education of the caregivers helps decrease

the morbidity and mortality related to malaria in children under-5 (5–7).

1.1 Transmission of malaria

Malaria is caused by Plasmodium parasites, and is transmitted to humans by mosquito bites

from female Anopheles mosquitoes infected with Plasmodium parasites. There are over 100

different species of the Plasmodium parasites, but only 5 protozoa species that transmit

malaria, P. vivax, P. falciparum, P. ovale, P. Knowlesi and P. malariae. Of these species of

the Plasmodium parasites, P. falciparum accounts for most cases of malaria in the African

region (3,4,8).

A female Anopheles mosquito ingests the Plasmodium parasites during blood feeding, the

parasites then mates in the gut of the mosquito and starts to multiply. After 10 to 18 days the

parasite migrates to the mosquito’s salivary glands. When the mosquito then acquires a new

blood meal from another human the bite from the infected female Anopheles mosquito injects

saliva along with the Plasmodium parasites to the human. Within the human the Plasmodium

parasites first grow and multiply inside the liver and then inside the red cells of the blood.

Once in the blood, successive broods of parasites grow inside the red cells and destroy them,

also releasing daughter parasites (merozoites) that continue the cycle by invading other red

cells. The parasites destroying the red blood cells is what causes the symptoms of malaria (9).

1.1.1 Determinants of transmission

There are a few different factors that make it easier for the mosquitoes to survive or find

humans for blood meals. But also factors that affect the life span of the Plasmodium parasites,

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and thus increasing the transmission of malaria. For instance, climate is a key determinant for

the geographical distribution and abundance of mosquitoes, and therefore affects the

transmission (10). The temperature is critical for development of the mosquitoes in each

stage, and also affects the longevity of the mosquitoes (10,11). Higher temperatures also

affect the ability of the Plasmodium parasite to survive inside the mosquito. Since a longer

life span of the mosquito gives the parasite time to complete its development inside the

mosquito (3). The mosquitoes lay their eggs in water and therefore precipitation also becomes

an important determinant for mosquito abundance (10,11).

Behavioural factors of the humans can also affect the transmission of malaria. These

behavioural factors are often related to social and economic factors. For instance, human

activities can lead to breeding sites for the mosquitoes, people living in poor rural areas

usually cannot afford protective measures against mosquito bites and migration may expose

people to malaria transmission. Having domestic animals near the household can serve as a

protective factor, since it provides alternative sources for blood meals for the Anopheles

mosquitoes (9).

Additionally, there are biological determinants that can protect humans from transmission of

malaria. There are two genetic factors, both involving the red blood cells, which can serve as

a protective factor against malaria transmission. For instance one of the factors is the sickle

cell trait some people have, giving them protection against P. falciparum malaria (9).

Some people may also have acquired immunity to malaria over time. This happens after a

person has had repeated malaria infections, and requires continued exposure or the acquired

immunity is gradually lost. The person may still be able to get infected with malaria, but the

symptoms will not be as severe. The acquired immunity is important to how malaria affects a

person and the community (9).

In conclusion, warmer and humid climates give the mosquitoes better possibilities to survive

and increase the abundance. It also increases the chance of the Plasmodium parasite to

survive. People are also more likely to sleep unprotected outdoors in the warmer climates, and

quite possibly without any protection from the mosquitoes. Which increases the malaria

infections in those warmer areas. Behavioural factors of the humans can serve as both a factor

for increasing and decreasing the risk of malaria transmission. There are also people who

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biologically are protected from malaria transmission and people who have acquired immunity

to malaria, thus giving them a biological advantage (9,10).

1.1.2 Preventing transmission

There are several ways to prevent transmission and reduce the number of malaria cases and

malaria related deaths. For instance insecticide-treated nets (ITN), intermittent preventative

treatment in pregnant women and indoor residual spraying are some of the more common

measures globally (10). Due to the nocturnal habits of the Anopheles mosquitoes most bites

happens at night, and the most common prevention measure is sleeping under a ITN (4).

ITNs give not only a physical barrier to protect humans from mosquito bites, but also an

insecticide barrier since they are treated with an insecticide (3,10). The nets treated with

insecticide are much more efficient for protection than the untreated nets as the insecticide in

the ITNs kills and repels mosquitoes and other insects. There are only 2 insecticides that are

approved for usage on ITNs, pyrroles and pyrethroids. These 2 insecticides poses low risk to

humans and other mammals while being deadly to insects. The ITNs used to need to be

retreated with the insecticide every 6 to 12 months, depending on how often they are washed.

But Long-Lasting Insecticide Nets (LLIN) has been developed and maintains the insecticide

for 3 years even if being washed. LLINs provide good protection and have been associated

with a decrease in malaria cases worldwide as many LLINs have been distributed during

campaigns and programmes worldwide (10).

Sometimes vector-controlling measures are used to try and control the mosquito abundance,

and thereby limiting the transmission of malaria. Vector-controlling measures includes

chemical larviciding, sterilisation of male mosquitoes and removing breeding sites for the

mosquitoes. In some extreme cases mass drug administration of antimalarial drugs is used,

this is when every person living in a defined area receives treatment at the same time (10).

1.2 Malaria symptoms

Malaria is a febrile illness that causes flu-like symptoms such as fever, headache and chills,

and the symptoms usually start within 7 to 15 days after being infected (3,4). The incubation

period is usually shorter with malaria cause by P. falciparum (9). First symptoms might be

mild and the combination with a sometimes longer incubation period might make it difficult

to recognize the symptoms as malaria at first (3,10).

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There are uncomplicated and severe malaria infections. With the uncomplicated malaria the

patients usually present symptoms such as fever, chills, sweats, headache, nausea and body

aches (10). If the uncomplicated malaria infection is not detected and treated it can lead to

severe illness (3). Severe malaria occurs when there is organ failure or abnormalities in the

patient’s blood or metabolism. It presents itself with symptoms such as seizures, loss of

conscience, severe anaemia, acute respiratory distress, low blood pressure, acute kidney

injury or metabolic acidosis (10).

Children who develop a severe malaria infection often get symptoms such as severe anaemia,

respiratory distress, confusion and coma. Recurrent malaria infections in children under the

age of 5 caused by P. falciparum could lead to severe anaemia (9). Additionally, if the

infection is not treated it could lead to death. This is why early detection and diagnostic of

malaria is crucial, so that adequate treatment can be initiated (3).

1.3 Malaria diagnosis

All suspected cases of malaria should be confirmed using either microscopic diagnostic tests

or rapid parasite-based diagnostic tests (3). A malaria infection should be confirmed before

any type of treatment is initiated (10). Microscopy examination is the “gold standard” for

detecting malaria. The test is performed by collecting a blood specimen from the patient and

spreading it on a microscope slide. Visual criteria is then used to detect the Plasmodium

parasite infecting the patients red blood cells (12). Microscopic diagnosis makes it possible to

count each parasite and is therefore more effective for monitoring the effectiveness of malaria

treatment than Rapid diagnostic tests (RDT). But even if it is a method well known to

laboratorians worldwide, the microscopy requires a level of skills that usually is not available

in health care facilities in malaria-endemic areas. The transmission usually occurs in remote

rural areas. Additionally, the electricity to run the microscopes and high workload may affect

the quality of the results from the test in malaria-endemic areas (10).

In recent years, the usage of RDT has expanded around the world. RDT are useful in settings

or situations where reliable microscopic diagnostic tests are not available; this is the case for

most malaria-endemic places (3,4,10). The usage of RDT in malaria endemic places has

greatly increased the quality and management of malaria infections. RDT are simple to

perform, and require limited training of the staff performing the tests. A blood specimen is

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collected from the patient and is applied to the sample pad on the test card. The RDT for

malaria detect specific antigens produced by the Plasmodium parasites, which are present in

the infected individuals blood (13). Using RDT, malaria confirmation can be available in 30

minutes or less and treatment can be started early (3).

1.4 Malaria treatment

There are many different anti-malarial drugs available for use, such as chloroquine,

amodiaquine, quinine and artemisin derivatives which are often used in combination

treatment (4). The World Health Organization (WHO) recommends artemisinin-based

combination therapies (ACTs) as the first-line treatment for treating uncomplicated malaria

caused by the Plasmodium parasites. Severe malaria should according to WHO be treated

with intramuscular or intravenous injectable artesunate and that treatment should be followed

by a treatment with ACTs. Access to ACTs has increased over the years and is the first-line

treatment against malaria in 80 countries worldwide (14).

To ensure all patients have an equal chance of being cured from the malaria infection, the

antimalarial drugs given must be of quality and be given at correct dosages. The quality of the

antimalarial drugs should be ensured by national drug and regulatory authorities, and should

be assured in both private and public sectors. The dosage of the treatment with antimalarial

drugs is based on the patient’s weight and the duration of the treatment varies. ACTs should

for example be given during 3 days and intramuscular or intravenous injectable artesunate for

at least 24 hours. Additionally, in low-transmission areas a single dose of ACTs could be

given to patients in order to reduce transmission (14).

A major and recurring problem is the resistance to antimalarial drugs. Plasmodium parasites

developed resistance to several antimalarial drugs such as fansidar and chloroquine during the

1950s and 1960s (3). With few new antimalarial drugs being developed there are concerns

since resistance to the first-line treatment ACTs has been reported. This could have major

consequences to public health and fatality due to malaria (15). Antimalarial resistance is

defined by the ability of the Plasmodium parasites to survive or multiply even though an

antimalarial drug has been administered (16).

In order to prevent the Plasmodium parasites to develop resistance to the first-line treatment

timely diagnosis, correct treatment and also patient adherence is of key value. With main

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emphasis on the patient adherence (15,17). And in children under-5 the caregivers mainly

influence patient adherence. Since it is the caregivers job to ensure to early detect a malaria

infection in the children and make sure the correct treatment is given (18).

1.5 Factors that influence the malaria treatment

To be able to make sure that adequate treatment is given for malaria proper knowledge about

the disease is important. Education, as well as other factors such as socioeconomic status and

place of residence play an important role in promoting health overall but also to prevent

diseases like malaria (6). These factors does not only affect the knowledge about malaria but

they also affect each other (7).

For instance there are differences in the knowledge about malaria and the education

depending on if the person reside in a rural or urban area. With people in rural areas having

less knowledge about malaria (7). Due to the lack of access to health care facilities in rural

areas, home management of malaria has become an important strategy for targeting malaria

elimination in rural areas. As previously stated early diagnosis is important, and diagnosis of

malaria at home is done by caregivers. They do so by recognizing symptoms such as cough,

fever, headache and loss of appetite. Therefore, knowledge about malaria is important in order

to ensure symptoms are recognised and the children receive the correct treatment (19). But

with people in rural areas generally having less knowledge about malaria, less education and

having longer distances to health care facilities, they turn to drug vendors, self-medication

and herbalists for treatment if the child is sick (7). Most children who die of malaria at home

do so without receiving adequate treatment although symptoms are recognised by caregivers

(5).

The choice of treatment is affected by the knowledge of the caregiver, the access to health

care services and cost of treatment, but also the attitude towards the health care. The socio-

economic status is a major factor associated with delay in treatment with antimalarial drugs in

children under-5, and the delay in treatment causes an increased morbidity and mortality due

to malaria. The socio-economic status affects the access to health care by functioning as a

barrier. The people with low socio-economic status might be unable to pay for direct and

indirect costs of the treatment. With the antimalarial drugs being a direct cost and the

transportation to and from the health care clinics being a indirect cost (5). The people with

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low socio-economic status also have a lower formal education, and the formal education is

also a barrier to adequate and timely treatment of malaria in children (6,20).

Formal education is a good tool to gain knowledge about malaria. In a malaria endemic area,

with between 70 to 80 percent of the residents having formal education, most people report

having knowledge about malaria, the symptoms to look for and what antimalarial drugs are

available. But even if antimalarial drugs were given they were often not given in the correct

dosage, especially to children under-5 (21). Formal education is a good way of removing

some of the misconceptions surrounding malaria that affects the prevention and treatment of

malaria (6). But understanding who already has knowledge about malaria, malaria prevention

and the treatment is also important, in order to target interventions and education about

malaria correctly (22).

1.6 Malaria burden in Nigeria

Nigeria has a climate suitable for malaria transmission with a tropical climate of dry and wet

seasons. Approximately 30 percent of the population resides in an area of high to very high

transmission rates, and 67 percent resides in an area of moderate transmission rates. The

duration and intensity of the malaria transmission season depends on the weather and the

duration of wet and dry seasons. The northern parts of Nigeria has a shorter malaria

transmission season in general (20).

Efforts have been made to reduce the prevalence of malaria, but it remains endemic in Nigeria

and poses a major threat to public health (20). Nigeria contributes to 25 percent of the global

burden of malaria (3). With children under 5 years of age and pregnant women being the most

vulnerable and affected. Malaria puts stress on Nigeria’s already weakened health system and

poses a huge economic burden for the country (20,23).

Over the years Nigeria has implemented different policies and strategies to deal with the

burden malaria puts on the country. The Malaria Control Programme was established in 1948

for research purposes and was incorporated into the Department of Public Health. In 2013,

The Malaria Control Programme was renamed the National Malaria Elimination Programme

(NMEP). The NMEP has over the years implemented three National Malaria Strategic Plans

(NMSPs) to build and nurture partnerships to gain political will, and also targeting vulnerable

populations for interventions. The fourth NMSP was being developed in 2014, and have

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seven objectives to work towards a malaria-free Nigeria. These seven objectives address the

issues around preventing malaria with LLINs, the use of RDTs and providing information and

adequate treatment. The 2014 NMSP has objectives that ensure that timely diagnosis and

treatment should be provided, and everyone should have access to appropriate treatment. By

2020 the NMSPs aims to provide 80 percent of the population with preventive measures

against malaria and to treat all individuals with a diagnosed malaria with effective anti-

malarial drugs (20).

Additionally, the National Malaria Policy was launched in February 2015, and aims to

eliminate malaria in Nigeria. The policy expressed a desire for the Nigerian government to

commit on all levels to ensure the elimination of malaria. The policy addresses issues

regarding malaria prevention, diagnosis, treatment and regulations regarding antimalarial

drugs (20).

The most used preventive measures against malaria in Nigeria are ITNs, LLINs and indoors

residual spraying. The use of ITNs is also one of the most effective measures of protection

from malaria transmission. ITN and LLIN are mostly used in the rural areas of Nigeria. With

more people sleeping outdoors in these areas compared to the urban areas, there is a greater

need for the ITNs and LLINs in the rural areas. Many prevention programmes in the country

emphasises the importance of awareness to the public in order to increase the usage of

mosquito nets, which has led to an increased demand for the mosquito nets. The Nigerian

government have distributed almost 52 million mosquito nets across the country, and during

replacement campaigns almost 46 million mosquito nets were distributed (20).

1.6.1 Malaria in children under-5 in Nigeria

Incidence of malaria in children under-5 in Nigeria is 27 percent, and malaria contributes to

30 percent of the under-5 mortality in Nigeria. The percentage of children using preventive

measures in form of LLINs is 29 percent. With almost half of the mothers knowing that

children are in fact a vulnerable group to malaria. Also the percentages of malaria incidence

in children are much higher in rural areas in Nigeria than in urban areas. Which ties into what

has already been discussed about the importance of education to achieve knowledge about

malaria and the access to health care (20).

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In 2015, out of all the children who displayed symptoms of malaria in the form of fever,

treatment was sought the same or next day for 35 percent of the children. With the least of the

children being brought in for treatment living in the rural areas of Nigeria (20). But overall

the treatment is not timely in children, despite living in rural or urban areas (5,20).

1.6.2 Education and knowledge about malaria in Nigeria

In Nigeria knowledge about malaria is high, with 87 percent of the women interviewed for the

Nigeria Malaria Indicator Survey (NMIS) 2015 having heard of the illness and 97 percent of

those women knowing one or more symptoms of malaria. And 23 percent of women in

Nigeria know malaria can be treated with ACTs. A majority of the women knew mosquitoes

caused malaria, but that knowledge varied depending on the woman’s level of education.

With a higher level of education of the women came more knowledge about malaria (20).

Showing that formal education contributes to a higher knowledge about malaria. Also formal

education could lead to earlier detection and better treatment of malaria infections (5,19).

Knowledge about treatment of malaria varied and increased with the level of education and

level of household wealth. The wealthier the household is the more educated the women

generally are (20). Although, studies have shown that most begin treatment at home with anti-

malarial drugs that were purchased at drug vendors without any prescription. And these drugs

are often the given at the wrong dosage and are not the recommended first-line treatment for

malaria (18).

A caretaker training programme was carried out in a south-east rural area in Nigeria in 2002,

and aimed at providing caretakers with education. The education provided the information

needed to detect and provide adequate treatment for malaria in their children but highlight the

importance of taking their sick child to a health care facility. The overall result of this

programme was an increased knowledge in the caregivers and a decreased number of severe

cases of malaria in children under-5 and decreased the number of children who received

treatment (20).

But there are still problems to tackle regarding the issue of malaria incidence in children

under-5 in Nigeria (18). And the 2014 NMSPs do not have an objective that directly addresses

the issue with education and how that is linked to increased treatment with antimalarial drugs.

The formal education has been shown by this caretaker programme and by previous studies to

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be an effective way to educate the caretakers and hence decrease the malaria incidence in

children under-5. But education is also necessary for adequate treatment to be given (5,19,20).

1.7 Justification and research aim

Malaria is a major problem in Nigeria today, and a threat to the public health of the residents

(20). Children are an especially vulnerable group, and they are dependent on their caregivers

to receive timely diagnosis and adequate treatment (3,5,18). The mothers, and their

knowledge, play an important role in whether or not the child receives treatment with

antimalarial drugs (5,18,23). Knowledge can be acquired from formal education (21).

Previous studies have not looked at education and how that is associated to treatment with

antimalarial drugs in children under the age of 5. The overall aim of this study is to explore

whether the level of maternal education is associated with the treatment for malaria in

children under-5, who have been tested positive with malaria, in Nigeria and if the level of

maternal education plays a role in the child receiving treatment or not.

Research Question: Is there an association between maternal level of education and the

treatment with antimalarial drugs in malaria positive children under the age of 5 in Nigeria?

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2. Methods 2.1 Study design

This study has a cross-sectional design and utilizes secondary data from the NMIS 2015 (20).

The Demographic and Health Surveys (DHS) programme conducted the NMIS 2015. The

DHS programme collects data nationally that provides a more in-depth understanding of

health issues. They provide decision makers with this information making it possible for them

to plan, monitor and evaluate population health and nutrition programmes (24).

2.2 Study population

The 2015 NMIS was conducted on a national level in Nigeria, and 8’148 households were

selected as eligible to be included in the survey, out of those 7’745 households were

interviewed for the survey. Making the household response rate 98.8 percent. All women in

these households aged 15 to 49 were eligible for individual interviews. Out of the 8’106

eligible women, 8’034 women were interviewed for the survey. Making the eligible women’s

response rate 99.1 percent. Respondents were asked about malaria prevention and treatment

of fever among their children during these interviews. Children aged 6 to 59 months were

offered testing for anaemia and malaria using finger- or heel-prick blood samples (20).

2.3 Study setting

Nigeria is a country located in sub-Saharan Africa, and has the largest population in Africa

and the seventh largest in the world, with an estimated population of 177.1 million people and

with an estimated annual growth of 3.2 percent. The fertility rate in the country has declined

from 6.0 in 1990, to 5.5 in 2013. Nigeria has a young population, with people between the age

of 0 and 24 accounting for more than 60 percent of the country’s residents and children under

the age of 5 alone contributes to 16 percent of the country’s residents (20).

It is bordered to Niger republic in the north, the Republic of Chad in the northeast, Republic

of Cameroon in the east, and the Republic of Benin to the West. The country is divided into 6

geopolitical zones: North Central, North East, North West, South East, South South and South

West and is also divided into 36 states and a Federal Capital Territory. Politically Nigeria is a

democratic country that has had a stable government since 1999. There are approximately 374

ethic groups, of which the 3 major ones are Igbo, Hausa and Yoruba (20).

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Nigeria is considered a lower middle-income country and since 2015 Nigeria’s economic

growth is muted. Nigeria is Africa’s biggest oil exporter, and the oil price collapse in 2014-

2016 hit the country’s economy hard. Before the oil price collapse the country had an average

gross domestic product (GDP) increase of 7 percent per year (25). The three southern zones

have a greater proportion of their population in the higher wealth quintiles than the northern

zones. The southern zones are more urbanised than the northern zones (20).

Nigeria has a diverse climate with dry and wet seasons. The dry season usually occurs from

October to March, and the wet season occurs from April to September. The temperature

usually lies between 25°C and 40°C, and the rainfall ranges from 2’650 millimetres in the

south-eastern parts of Nigeria to less than 600 millimetres in the northern parts. Nigeria has a

wide range of climatic-, vegetation- and soil conditions that allows for the possibility of a

wide range of agricultural production (20).

The physical characteristics of a household are an important determinant for the health of the

people living there, especially for children. For instance, about half of the Nigerian

households do not have electricity and use non-improved latrine facilities. Poor water quality

and inadequate sanitation have a negative impact on health, food security and livelihood. And

every year people die due to the lack of access to clean water and proper sanitation, most

vulnerable are children. The urban population are more likely than the rural population to

have access to these determinants for health (20).

Nigeria’s health system includes private and public health sectors. The private health sector

includes not-for-profit and for-profit organizations, traditional medicine providers, medicine

vendors, drug shops and alternative practitioners. The public health sector includes large

referral hospitals, tertiary health facilities and primary health facilities. The primary health

centres provide basic preventive, promotive, rehabilitative and curative health care services

for most of the rural population. Included in the primary health care system are also the

community-oriented resource persons (CORPS), who treat children under-5 for diseases such

as malaria, pneumonia and diarrhoea at a community level (20).

The first National Health Policy was implemented in 1988, and its target is to achieve health

for all Nigerians. The National Health Policy aims to support implementations of health-

related programmes and interventions, and support regulations of the health care system. It

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has since been revised due to issues, trends and realities, and the revised version was launched

in 2004. The long-term goal of the revised policy is to provide adequate access to primary,

secondary and tertiary care services to the Nigerian population (20).

Between 2003 and 2013 the under-5 mortality rates decreased from 201 deaths per 1’000 live

births to 128 deaths per 1’000 live births. The maternal mortality ratio was 545 deaths per

100’00 live births in 2008, and in 2013 it had increased to 576 deaths per 100’000 live births.

There has been a decline in the fertility rates in Nigeria, from 6.0 in 1990 to 5.5 in 2013. The

Integrated Maternal, Newborn and Child Health Strategy was developed by the Federal

Ministry of Health in 2007 to achieve the Millennium Development Goals that aimed to

reduce the child mortality and improve maternal health (20).

2.4 Sample size/selection

The women’s questionnaire and the household questionnaires were used to find the data

necessary for this study. In the women’s questionnaire a total of 6’524 of children aged 6 to

59 months were documented from the 8’034 women who participated in the survey. Only the

last-born child of the woman was included in the survey. Out of the total 6’524 children aged

6 to 59 months, 3’902 were excluded on the basis that they were not malaria positive or that

there was no information on the child receiving treatment with antimalarial drugs (See Figure

1). The remaining 2’622 malaria positive children aged 6 to 59 months that were included in

this study for analysis. 1’100 children were treated with antimalarial drugs and 1’522 children

did not receive any treatment with antimalarial drugs.

2.5 Data collection

For the sampling method, the NMIS 2015 used a two-stage stratified cluster sampling based

on Enumeration areas (EAs) and households. In the first stage 333 EAs were selected, 138 in

urban areas and 195 in rural areas. A household listing operation was carried out in all

selected EAs, with the resulting lists of households serving as the sampling frame for

selecting households in the second stage. In the second stage, a fixed number of 25

households were selected on each cluster by an equal probability systematic sampling method

(20).

For this study the NMIS 2015 was obtained from the DHS website after access to it had been

granted. A team from the DHS collected the data for this survey between September 2015 and

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November 2015. Three questionnaires were used for this survey: the household questionnaire,

the woman’s questionnaire and the biomarker questionnaire. The Survey Implementation

Committee was responsible for implementation of the 2015 NMIS and ICF International

provided the technical support team consisting of survey coordinator, sampling specialist,

survey manager, data processing specialist and biomarker laboratory science specialist. There

were 37 interviewing teams each consisting of one supervisor, two interviewers, a laboratory

scientist and one driver. In addition to English the questionnaires were translated into three

major Nigerian languages: Hausa, Igbo and Yoruba (20).

2.6 Methods and variables

The exposure variable for this study was the maternal level of education level and the

outcome variable was if the child aged 6 to 59 months positive for malaria received any

treatment with antimalarial drugs or not.

Exposure variable

Maternal level of education was divided into six categories in the survey: No education,

incomplete primary education, complete primary education, incomplete secondary education,

complete secondary education and higher education. For this study the categories incomplete

primary education and complete primary education were merged into the category primary

education. The categories incomplete secondary education and complete secondary education

were merged into the category secondary education. The final categories used for this study

were: No education, primary education, secondary education and higher education of the

mothers. With no education being the reference category.

Outcome of interest

In the survey mothers responded yes or no to the question if the child aged 6 to 59 months

received any treatment with any of the following antimalarial drugs if they had tested positive

for malaria: SP/Fansidar, Chloroquine, Amodiaquine, Quinine, combination with artemisinin,

country specific antimalarial or other antimalarial drug. For this question about treatment it

was preselected in the DHS MIS survey as the youngest child of the mothers. So this study

will be looking at only one of the children in a family, even if the mothers have more

children. For this study children who received any treatment with 1 antimalarial drug or more

were coded as 1, and children who did not receive any treatment was coded as 0.

19

Confounding variables

Variables used in this study are based of previous studies (26–28). Confounding factors

included are the household wealth index, place of residence being rural or urban, maternal age

and number of children of the mother. For the wealth index the five categories were: poorest,

poorer, middle, richer and richest, and the category poorest was chosen as reference category.

For place of residence urban was chosen as the reference category. Maternal age and number

of children of the mother were used as continuous variables.

2.7 Statistical analysis

2.7.1 Descriptive analysis

A descriptive analysis was conducted to be able to present the frequency distribution and

percentages of the categorical variables, and mean and standard deviation of the continuous

variables included in this study.

2.7.2 Bivariate analysis

All variables were tested against both the exposure variable and outcome variable. For the

analysis R version 3.6.3 was used.

Chi-squared tests were carried out on all categorical variables to look for associations. The

variables wealth index of the household and place of residence were tested against both the

exposure and outcome. Independent t-tests were carried out when looking for associations

between the numerical variables mother’s age and number of children against both the

exposure and outcome. If the variables were associated with both the exposure and outcome,

with a p-value of <0.2, they were included as confounders in the logistic regression.

2.7.3 Multivariate analysis

For the multivariate analysis logistic regression was carried out in three different models. The

first model was the unadjusted logistic regression containing the exposure variable and

outcome variable alone. The second model included the exposure, outcome and confounders

wealth index of the household and place of residence. Wealth index and place of residence

were the two variables with an association in the bivariate analysis and therefore included as

confounders in the logistic regression. The third model included all variables in this study.

Maternal age and number of children did not show an association with the outcome in the

bivariate analysis. But since they have been shown from previous studies to have an impact

20

on both the maternal level of education and odds of the child to receive treatment, they were

included in a third separate model to see the impact they had on the outcome. The level of

significance was set at p-value <0.05 and with a confidence interval of 95% in the logistic

regression. .

2.8 Ethical consideration

The Nigeria Health Research Ethics Committee of the Federal Ministry of Health (NHREC)

approved the 2015 NMIS survey protocol. Confidentiality for each of the participants was

ensured. Participation in the survey was completely voluntary and written consent was

collected from each participant beforehand. Children were asked to take a malaria diagnostics

test. If the malaria test was positive the child was offered treatment with antimalarial drugs

(20).

21

3. Results A total of 8’034 women participated in the 2015 DHS NMIS Survey. There was information

that these women had 6’624 children combined. After excluding the children who were

malaria negative and the children there were no information on whether they received

treatment or not, a total of 2’622 children were used for this analysis (figure 1).

Figure 1 – Flowchart of the participants’ chosen for this study based on the DHS MIS Survey

in Nigeria 2015.

3.1 Characteristics of the study population

With most of the mothers having no education (49.8%) and the fewest mothers had a higher

level of education (5.4%), the distribution of the maternal level of education being shown in

table 1.

The variables place of residence showed that 62.3% (n=1’634) of the children resided in a

rural area in Nigeria, and 37.7% (n=988) resided in an urban area. The wealth index of the

household in which the children resided in were evenly distributed, and divided into the

groups poorest, poorer, middle, richer and richest (Table 1). The mean age of the mothers was

27.88 ± 8.72 years. The mean number of children in the household was 3.72 ± 2.13 (Table 1).

All children aged 0-69m

(n=6’524)

All children positive for malaria with information

on treatment (n=2’622)

Children that were malaria negative or no information

on treatment with antimalarial drugs

(n=3’902)

Children not treated with antimalarial drugs

(n=1’522)

Children treated with antimalarial drugs

(n=1’100)

Women included in the study (n=8’034)

Women with no information on any

children (n=1’510)

22

The different antimalarial drugs and the distribution of the treatment with them are shown in

Table 1, with most children receiving combination treatment with artemisinin (14.9%). The

overall treatment with antimalarial drugs in children under-5 that were malaria positive was

42%.

Table 1 – Descriptive table showing the characteristics of the study population included in

this study, including frequency distribution, mean and standard deviation for the variables

(total n=2’622). Variables Frequency (%)/Mean ± SD

Maternal level of education

No education 1’305 (49.8)

Primary 484 (18.5)

Secondary 690 (26.3)

Higher 143 (5.4)

Place of residence

Rural 1’634 (62.3)

Urban 988 (37.7)

Wealth index

Poorest 516 (19.7)

Poorer 529 (20.2)

Middle 579 (22.1)

Richer 551 (21.0)

Richest 447 (17.0)

Number of children 3.72 ± 2.13

Maternal age 27.88 ± 8.72

Treatment with antimalarial drugs

SP/Fansidar 168 (6.4)

Chloroquine 302 (11.5)

Amodiaquine 68 (2.6)

Quinine 74 (2.9)

Combination with artemisinin 392 (14.9)

Country specific antimalarial 55 (2.1)

Country specific antimalarial 66 (2.5)

Other antimalarial 115 (4.4)

Overall treatment with antimalarial drugs

Yes 1’100 (42)

No 1’522 (58)

SD – Standard deviation

23

3.2 Bivariate analyses to evaluate association between the outcome and exposure

variables and the background characteristics

Table 2 displays the bivariate analysis between the treatment with antimalarial drugs in

children under-5 positive for malaria and the background characteristics. As seen in Table 2,

maternal level of education showed significant association with the treatment with

antimalarial drugs in children under-5 (p-value <0.001). For the children who received

treatment with antimalarial drugs 44% had mothers who had no education, compared to the

children who did not receive treatment 53.9% had mothers with no education. Out of the

children who received treatment with antimalarial drugs 7.4% had mothers with a higher level

of education, compared to children who did not receive any treatment with antimalarial drugs

4.1% had mothers with a higher level of education.

Additionally in Table 2, looking at the percentages for all of the children who received

treatment, the percentages are higher for the children where the mothers have primary

education (19.5%) and secondary education (29.1%). Compared to the group of children who

did not receive any treatment with mothers who have primary education (17.7%) and

secondary education (24.3%).

Even though the wealth index was not significant associated to the treatment with antimalarial

drugs in children under-5 (p-value 0.1077), Table 2 shows that the children who received

treatment the majority (22.8%) belonged to the richer category of the wealth index. Compared

to the children who did not receive any treatment with the majority (22.5%) belonging to the

middle category of the wealth index.

The place of residence was not significant either (p-value 0.0661), but the children were more

likely to receive treatment if they resided in an urban area in Nigeria. Maternal age and

number of children showed no significant association (p-value 0.4612 and 0.5243

respectively) to the treatment with antimalarial drugs in children under-5 that were malaria

positive (Table 2).

Table 2 – A bivariate analysis of the background characteristics and the treatment of children

under-5 with antimalarial drugs using the Chi-squared test and the independent t-test (total

n=2’622).

24

Factors Treatment No treatment P-value

Maternal level of education (Frequency (%)) (Frequency (%)) <0.001

No education 484 (44.0) 821 (53.9)

Primary 215 (19.5) 269 (17.7)

Secondary 320 (29.1) 370 (24.3)

Higher 81 (7.4) 62 (4.1)

Wealth index 0.1077

Poorest 200 (18.2) 316 (20.8)

Poorer 235 (21.4) 294 (19.3)

Middle 236 (21.5) 343 (22.5)

Richer 251 (22.8) 300 (19.7)

Richest 178 (16.2) 269 (17.7)

Place of residence 0.0661

Rural 663 (60.3) 971 (63.8)

Urban 437 (39.7) 551 (36.2)

Maternal age

(Mean ± SD)

28.03 ± 8.77 27.77 ± 8.72 0.4612

Number of children (Mean ± SD) 3.76 ± 2.14 3.70 ± 2.11 0.5243

SD = Standard deviation

Table 3 displays the bivariate analysis between the maternal level of education and the

background characteristics. There was a significant association between the maternal level of

education and the wealth index of the household (p-value <0.001). As shown in Table 3, the

majority (29.3%) of the women who had no education belonged to the poorest category of the

wealth index and the least (11.3%) of the women who had no education belonged to the

richest category. In comparison out of the women whom had a higher level of education the

majority (29.4%) belonged to the richer category of the wealth index, and the least (6.3%) of

the women who had a higher level of education belonged to the poorest category.

The place of residence showed significant association with the maternal level of education (p-

value <0.001). Out of the women whom had no education 71.4% resided in the rural areas of

Nigeria, compared to the women with a higher level of education out of which 44.8% resided

in the rural areas. Out of the women with no education 28.6% resided in the urban areas,

compared to the women with a higher level of education out of which 55.2% resided in the

urban areas.

25

The mean age of the mothers did not show any significant association. But Table 3 shows that

the mean age of the mothers increased as the education level did although it was not

significant. As mothers with no education had a mean age of 27,57 compared to mothers with

a higher level of education that had a mean age of 28.97.

The number of children of the women showed significant association to the maternal level of

education. The number of children of the women decreased as the education level increased.

Mothers with no education had a mean number of children of 4.04 compared to the mothers

with a higher level of education who had a mean number of children of 2.97 (Table 3).

Table 3 – A bivariate analysis of the background characteristics and the maternal level of

education using the Chi-squared test and the independent t-test (total n=2’622). Factors No education Primary Secondary Higher P-value

Wealth index (Frequency (%)) (Frequency (%)) (Frequency (%)) (Frequency (%)) <0.001

Poorest 383 (29.3) 70 (14.5) 54 (7.8) 9 (6.3)

Poorer 334 (25.6) 94 (19.4) 88 (12.8) 13 (9.1)

Middle 252 (19.3) 110 (22.7) 179 (25.9) 38 (26.6)

Richer 189 (14.5) 109 (22.5) 211 (30.6) 42 (29.4)

Richest 147 (11.3) 101 (20.9) 158 (22.9) 41 (28.7)

Place of residence <0.001

Rural 932 (71.4) 281 (58.1) 357 (51.7) 64 (44.8)

Urban 373 (28.6) 203 (41.9) 333 (48.3) 79 (55.2)

Mother age

(Mean ± SD)

27.57 ± 8.76 27.46 ± 8.82 28.52 ± 8.72 28.97 ± 8.05 0.0342

Number of

children (Mean ±

SD)

4.04 ± 2.19 3.96 ± 2.22 3.12 ± 1.84 2.97 ± 1.69 <0.001

SD = Standard deviation

3.3 Regression analyses evaluating the association between maternal level of education

and antimalarial treatment in their children under-5 in Nigeria

From the unadjusted logistic regression analysis in Model 1 conclusions can be drawn that

compared to the mothers with no education, mothers who have primary education have an

increased odds of 35% (OR 1.35, CI 1.09-1.67) of making sure their child receive treatment

with antimalarial drugs. Mothers with secondary education have increased odds of 46% (OR

1.46, CI 1.21-1.76) of making sure their child receives treatment with antimalarial drugs,

26

compared to mothers with no education. Additionally, mothers with a higher level of

education have more than two times higher odds (OR 2.21, CI 1.56-3.15) compared to

mothers with no education of making sure their child receives treatment with antimalarial

drugs (Table 4).

When adjusting for the variables wealth index and place of residence in model 2 all categories

of maternal level of education stayed associated with the outcome. With an increase to 38%

(OR 1.38, CI 1.11-1.71) in the odds for the child receiving treatment with antimalarial drugs

if the mother has primary education and an increase to 51% (OR 1.51, CI 1.24-1.84) if the

mother has secondary education compared to mothers with no education. The mothers with a

higher level of education still have two times higher odds of making sure their child receives

treatment with antimalarial drugs compared to the mothers with no education, but with an

increase in the odds ratio from 2.21 (CI 1.56-3.15) to 2.31 (CI 1.62-3.32).

In the adjusted regression in model 2 the category richest in the wealth index was show to be

associated with the treatment of the child. Showing that children belonging to a household in

the richest category, compared to the poorest category, had decreased odds of 27% (OR 0.73,

CI 0.53-0.99) of the child receiving treatment with antimalarial drugs (Table 4). Additional

findings in model 2 show that place of residence was associated with treatment of the child.

Living in a rural area in Nigeria decreases the odds of the child receiving treatment with

antimalarial drugs with 19% (OR 0.81, CI 0.66-0.99), compared to living in an urban area.

In the adjusted logistic regression in model 3 the variables maternal age and number of

children of the mothers were added. There was a small change in the odds ratio for the

maternal level of education categories, and they remained associated to the outcome. For

wealth index richest remained the only category that showed association with small changes

in the odds ratio (add odds ratio). Living in a rural area still showed a 19% (OR 0.81, CI 0.66-

0.99) decrease in odds in treatment with antimalarial drugs in children compared to living in

an urban area. Maternal age and number of children was not associated with the treatment

with antimalarial drugs in children under 5 (Table 4).

Table 4 – Evaluating the association between maternal level of education and the treatment

with antimalarial drugs in children under-5 that were malaria positive in Nigeria (total

n=2’622).

27

Model 1 Model 2 Model 3

Factors OR (95% CI) P-value OR (95% CI) P-value OR (95% CI) P-value

Maternal

level of

education

No education (Ref) (Ref) (Ref)

Primary 1.35 (1.09-1.67) 0.004 1.38 (1.11-1.71) 0.003 1.38 (1.11-1.72) 0.002

Secondary 1.46 (1.21-1.76) <0.001 1.51 (1.24-1.84) <0.001 1.55 (1.27-1.90) <0.001

Higher 2.21 (1.56-3.15) <0.001 2.31 (1.62-3.32) <0.001 2.38 (1.66-3.43) <0.001

Wealth index

Poorest (Ref) (Ref)

Poorer 1.20 (0.93-1.53) 0.150 1.19 (0.93-1.53) 0.162

Middle 0.89 (0.69-1.15) 0.399 0.89 (0.69-1.15) 0.397

Richer 0.98 (0.74-1.30) 0.926 0.98 (0.74-1.29) 0.901

Richest 0.73 (0.53-0.99) 0.049 0.72 (0.52-0.99) 0.046

Place of

residence

Urban (Ref) (Ref)

Rural 0.81 (0.66-0.99) 0.046 0.81 (0.66-0.99) 0.048

Maternal age 1.00 (0.99-1.01) 0.604

Number of

children

1.03 (0.99-1.07) 0.114

OR = Odds ratio, CI = Confidence interval, Ref = the reference group

Model 1 = the unadjusted logistic regression.

Model 2 = the adjusted logistic regression using the variables wealth index and place of residence.

Model 3 = the adjusted logistic regression using the variables wealth index, place of residence, maternal age and

number of children.

28

4. Discussion 4.1 Main findings

The aim of this study was to investigate whether maternal level of education had an impact on

the treatment of children under-5 with antimalarial drugs in Nigeria. The main finding of this

study concludes that maternal level of education plays a role in whether a child receives any

treatment with antimalarial drugs or not. There is also a difference in treatment depending on

the level of education of the mother. For example, mothers who had a higher level of

education compared to mothers who have no education are more than two times more likely

to make sure their child receives treatment with antimalarial drugs.

4.2 Impact of maternal level of education on the treatment with antimalarial drugs in

children under-5

Knowledge has previously been established as an important tool in the prevention of malaria.

The knowledge plays a role in people’s perception of the problem and their practices in order

to control malaria infections (6). The knowledge about malaria and how to treat it has been

shown to increase with formal education (21). In this study the higher level of education the

mothers had, in comparison to the mothers who did not have any education, the more likely

the mothers were to make sure their child received treatment with antimalarial drugs. The

mothers with a higher level of education were more than two times more likely to give their

child treatment with antimalarial drugs compared to the mothers without any education. The

mothers with secondary education were 51 percent more likely to give their child treatment

with antimalarial drugs compared to the mothers without education. And the mothers with

primary education were 38 percent more likely to give their child treatment with antimalarial

drugs compared to the mothers with no education. This indicates that higher level of maternal

education might be associated with higher knowledge about malaria and malaria treatment.

Thus, the mother’s formal education helps ensure treatment with antimalarial drugs is given to

children under-5, and might reduce the possibility of under-5 morbidity and mortality due to

malaria.

Another study conducted in Nigeria in 2014 also concluded that the education of the mothers

was a factor for adequate and timely treatment with antimalarial drugs in children under-5.

With a higher level of education in the mothers being associated with more timely and

adequate treatment for the children under-5 (5).

29

Additionally, a study conducted in India in 2017 concluded that the higher level of formal

education the better knowledge on malaria diagnosis and preventive measures the people had.

The study from India was investigating the determinants for seeking treatment for malaria.

But it also showed that the higher level of education the less delay there was in seeking

treatment and self-medication or less preference for using traditional healers compared to the

less educated people (29). This is conclusive with the main result of this study, which also

showed an association between level of maternal education and the likelihood of their

children who were malaria positive receiving treatment in Nigeria. Indicating that the formal

education provides the mothers with some kind of knowledge that leads to them to the

decision to seek treatment for their sick child.

While the knowledge about malaria has been shown to be associated with the level of

education in some studies, a previous study conducted in South-Eastern Nigeria in 2005

concluded that formal education is an important tool to acquire information about malaria and

how it should be treated, but it is not the only tool since higher level of education is not

always associated with better knowledge about malaria. Therefore interventions targeting

malaria treatment cannot solely focus on formal education. Although it is an important tool

for people to gain knowledge about the malaria treatment (6).

A study conducted in Uganda also indicates that the formal education of the mothers is an

important tool, but also that the content of the formal education is important. This study was

conducted in an urban setting during the malaria season, and 88 percent of the mothers had

formal education. Despite having formal education the mothers did not make the association

between fever in their children and that it could be malaria. It was concluded that the mothers

had an overall poor knowledge about malaria. Their failure to recognize a malaria infection in

their children could have adverse health consequences. Since the treatment could be delayed

or not given if care is not sought. Indicating that the content in the formal education matters as

well (30). What kind of knowledge the mothers had gained from their formal education that

lead to the decision to give their children treatment was not looked at in this study. That topic

requires further research as it has been shown to be an important topic.

It is important to look at how knowledge is acquired. Education interventions could for

instance be hard to assimilate for mothers without any formal education. Formal education

30

could provide the mothers with the skills necessary to obtain knowledge and process

information. But it is not necessarily from formal education the knowledge about malaria is

provided.

For instance, a study was carried out in rural refugee villages in Belize with the objective to

increase the mother’s health seeking behaviour for their children under-5 with malaria. To

achieve the study’s objective, health education interventions were used with the interventions

targeting the mothers. There was only a small increase in the health seeking behaviours of the

mothers regarding their children following this intervention. The increase in health seeking

behaviour was mostly due to the inter-personal communication between the mothers. With a

majority of the mothers having no formal education, the results indicating that formal

education provides the mothers with knowledge to understand health messages overall (31).

Overall, the people in Nigeria have a good knowledge about the cause of malaria and the most

common symptoms of a malaria infection (28). The biggest knowledge gap is prevention and

treatment of malaria. With most mothers actually giving their children treatment with

antimalarial drugs, but the problem being that they do not know which drugs to give or what

dosages to give. Or they do not ensure the child completes the full course of the treatment

with the adequate antimalarial drug (21).

This study did not explore the question of compliance or the timeliness of the antimalarial

treatment given to the children. In the children under the age of 5, it is the mothers or

caregivers task to ensure the child receives the adequate treatment and complies with it. Thus,

further studies are needed to explore the topic of maternal level of education and the

association with timeliness and compliance with treatment with antimalarial drugs in children

under-5.

Knowledge is not the only aspect of formal education of the mothers, previous studies

indicate that the education also provides the mothers with higher autonomy. A study

conducted in Ethiopia concluded that the maternal education was associated with more

autonomy of the mothers. The mothers who had a higher education were more likely to make

their own decisions regarding not only their own health, but also their children’s health (32).

In addition, a study conducted in Kenya that investigated the association between maternal

education and the immunization of their children concluded that maternal education is

31

important for acquiring health knowledge. That the mothers were able to make better

decisions regarding their children’s health, which ultimately leads to improvements in child

health (33).

To conclude this study is conclusive with previous studies (21,29,31), that formal education

was associated with treatment with antimalarial drugs in children under-5. Since this study

concludes that the higher level of education of the mother, compared to no education at all,

the higher the odds of the child receiving treatment with antimalarial drugs. The previous

studies explore the reasons for why formal education is a great tool for improving child health

(5,21,29,32,33). But it is also important to remember that formal education is not the only

factor to take into consideration when looking at the reasons for treatment with antimalarial

drugs in children under-5.

4.3 Background characteristics role in the treatment with antimalarial drugs in children

under-5

The result from this study indicates that the richest households had a 27 percent decreased

odds, compared to the poorest households, of the children under-5 receiving treatment with

antimalarial drugs. This result does not conclude with some previous studies (5,27). A

previous study, which was conducted in rural areas of Tanzania, concluding that the overall

coverage of treatment with antimalarial drugs was low. But particularly disadvantaged was

the population living in the poorer households. And that the poorest population were less

likely to benefit and gain access to antimalarial drugs for treating malaria, in comparison to

the richer population. Notable from this study was also that people living in wealthier

households were not only more likely to gain access to antimalarial drugs, but also to obtain

effective and safe antimalarial drugs than those living in poorer households (27).

Another study conducted in Nigeria in 2014, which looked at the determinants for delay in

treatment in children under-5, concluded that the economic status of the household served as a

barrier for timely and appropriate antimalarial treatment in children under-5. With poorer

households having less access to adequate treatment, and thus the children from richer

households were more likely to receive treatment (5). Not conclusive with the findings from

this study.

32

Furthermore, preventive measures such as whether the child slept under an ITN is different

depending on the household wealth and the place of residence. The wealthier households

usually have more access to ITNs, but the poorest household are more likely to use them. This

can be due to the fact that the poorest households often are considered a vulnerable group that

is targeted with interventions regarding ITN usage (34). In Nigeria the ITN and LLIN usage

was 29 percent in children under-5, with most of those using them belonging to the wealthier

households (20). Another study shows that less fever in children under-5 is reported from

households with ITN usage (35). Which could explain why the incidence of malaria is higher

in children under-5 belonging to the poorest households. But does not explain why children in

richer households are less likely to receive treatment compared to children in poorer

households in this study.

In this study, results showed that living in a rural area in Nigeria decreases the odds of the

child under-5 receiving treatment with antimalarial drugs with 19 percent, compared to

children living in an urban area. Which is cohesive with the study conducted in India in 2017,

which indicates that there was a delay in treatment with antimalarial drugs for people living in

rural areas. This might be due to of the distance to health care facilities (29). In line with the

findings of this study, a study conducted in Tanzania reported the results that the children

from the urban areas are less likely to contract a malaria infection overall, and additionally

they are also more likely to receive proper and adequate treatment with antimalarial drugs

(27).

This study indicates that when investigating the topic of treatment with antimalarial drugs in

children under the age of 5, determinants such as place of residence and the wealth of the

household the child lives are two important background characteristics that were associated

with the treatment with antimalarial drugs in children under-5 in Nigeria. When adjusted for

these background characteristics of the children in this study, the formal level of education of

the mothers still showed a significant association with the treatment with antimalarial drugs in

the children. With mothers with a higher level of education, compared to no education, had

increased odds of making sure their child received treatment.

This study showed no association between the maternal age and the treatment with

antimalarial drugs in children under-5, which is not conclusive with some previous studies. A

study conducted in Nigeria in 2014 concluded that the age of the mothers was associated with

33

the treatment with antimalarial drugs in children under-5. The mothers who were older did not

wait for the father’s approval to seek care and sought care for their child sooner than the

younger mothers. The older mothers were also less prone to economic related issues which

could possibly affect the access to treatment (5).

The study conducted in Nigeria in 2014, also concluded that the number of children of the

mothers served as a delaying factor for seeking care for their children. The mothers with a

higher number of children did not take the symptoms in their children as serious as mothers

with fewer children did. Resulting in children who’s mothers had more children were less

likely to receive adequate or timely treatment with antimalarial drugs than children who’s

mothers had fewer children (5). This was not conclusive with the results of this study, as this

study concluded no association between the number of children and the treatment with

antimalarial drugs in children under-5.

4.4 Strengths and limitations

4.4.1 Strengths

The main strength of this study was using data from the DHS, which is an internationally

recognized and population-based dataset. The DHS datasets offers a nationally representative

sample with high quality. It obtains the high quality by the fact that trained and experienced

field workers collected and analysed the data provided in the datasets. By using DHS data this

study was conducted at a low cost. The large sample size used in this study serves as an

additional strength. It helps provide reliability and ensures a more precise and accurate dataset

and values.

An additional strength is that studying the topic of malaria makes this study generalizable

other sub-Saharan African countries, or possibly other countries, with malaria transmission at

the same level as Nigeria and similar access to treatment and health care.

4.4.2 Limitations

Studying malaria and the many reasons why treatment with antimalarial drugs is provided or

not can be complex. Looking at those reasons on a national level could possibly mask some of

the reasons for treatment on an individual level. But since this study is taking advantage of the

DHS data, which is large and nationally representative, it will bring to light the overall trends

34

on decisions for treatment, which could not have been brought to light by looking at a smaller

sample size on an individual level.

This study relies on the use of RDTs and microscopy for malaria diagnosis in the children

under-5. So there is always a chance with diagnoses that some patients were missed, and

therefore making it likely that the malaria prevalence figures is an underestimate in the DHS

dataset used for this study.

Since a complex cluster sample design was used in the DHS data collection, a limitation of

this study is that it is not adjusted for that. This makes it a possibility that reported p-values

are at risk of a type 1 error. Meaning that some of the associations could have been reported

as significant while it was in fact not significant.

Additionally, as this study was of cross-sectional design it did not allow an assumption on

causality to be drawn from the findings. Rather just analysing the association of the outcome

and exposure variables.

35

5. Conclusion In conclusion, the results of this study indicate that the maternal level of education was

associated with the likelihood of the child positive for malaria being treated with antimalarial

drugs or not. The mothers with a higher level of education was more than 2 times more likely

to ensure their child receives treatment with antimalarial drugs, compared to the mothers with

no education. The wealth of the household and the place of residence are background

characteristics that need to be taken into consideration when exploring this issue. And future

interventions targeting the treatment in children under-5 with antimalarial drugs need to be

aware of the impact of maternal level of education and also the background characteristics

and target the interventions accordingly.

Most interventions in Nigeria seemed to have focused on the prevention of malaria using

ITNs (20). And most previous studies focused on treatment with antimalarial drugs in relation

to factors such as knowledge of the caregivers and place of residence, but also the infection

rate of malaria in children under-5 and the association to maternal level of education

(21,22,28,36,37). But the interventions and studies have not focused on the association

between treatment with antimalarial drugs in children-5 and the educational level of the

mothers.

Following this study, more research is needed to look at how the maternal level of education

affects the compliance and timeliness of the treatment with antimalarial drugs in children

under the age of 5. But also what type of knowledge the formal education provides the mother

with in order to make the decision regarding treatment with antimalarial drugs for their

children.

36

6. Acknowledgement I wish to acknowledge the Demographic and Health Surveys Program for providing free

access to the data needed for this study.

A special thanks to my supervisor Shirin Ziaei for all the help and support throughout this

study. The feedback provided was essential and deeply appreciated, and without it and your

guidance this study would not have been made.

Lastly, I would like to thank my family and my partner, for always believing in me and

supporting me no matter what.

37

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