CHRISMED Journal of Health and Research

REVIEW ARTICLE
Year
: 2021  |  Volume : 8  |  Issue : 2  |  Page : 67--75

Factors influencing prevention and control of malaria among pregnant teenagers in rural parts of Delta State, Nigeria


Rolle Remi Ahuru, Clement Atewe Ighodaro 
 Department of Economics, Faculty of Social Sciences; Center of Excellence in Reproductive Health Innovation, University of Benin, Benin City, Nigeria

Correspondence Address:
Rolle Remi Ahuru
Department of Economics, Faculty of Social Sciences, University of Benin, Benin City; Center of Excellence in Reproductive Health Innovation, University of Benin, Benin City
Nigeria

Abstract

This study was conducted to assess the factors associated with malaria prevention and control among pregnant teenagers in four Primary Healthcare Centers in rural Delta State. A facility-based cross-sectional study was conducted among 427 pregnant teenagers in the rural part of Delta State, and data were collected using a self-administered questionnaire prepared in English and analyzed using STATA 13.0. Descriptive statistics and binary logistic regression analysis were conducted to determine the prevalence of malaria adherence and its predictors among pregnant teenagers. The results revealed that 50.1% reported sleeping under insecticide-treated nets (ITNs), 49.2% reported using indoor residual spray (IRS), and 38.4% intermittently treat malaria in pregnancy (IPTp). Women who reported secondary educational qualification were approximately three times (adjusted odd ratio [aOR]: 2.72, P =0.01), five times (aOR: 5.27, P <0.001) and nine times (aOR: 9.23, P <0.001) significantly and respectively more likely to sleep under ITNs, use IRS and IPTp. Those who reported tertiary education (aOR: 6.16, P =0.04) were approximately six times significantly more likely to IPTp. Unemployed women (aOR: 0.46, P =0.02) were 54% significantly less likely to intermittently treating malaria in pregnancy. The findings suggest that malaria prevention programs and intervention strategists should consider the socioeconomic conditions of poor rural teenagers, promote female literacy, and target women with several births.



How to cite this article:
Ahuru RR, Ighodaro CA. Factors influencing prevention and control of malaria among pregnant teenagers in rural parts of Delta State, Nigeria.CHRISMED J Health Res 2021;8:67-75


How to cite this URL:
Ahuru RR, Ighodaro CA. Factors influencing prevention and control of malaria among pregnant teenagers in rural parts of Delta State, Nigeria. CHRISMED J Health Res [serial online] 2021 [cited 2021 Dec 2 ];8:67-75
Available from: https://www.cjhr.org/text.asp?2021/8/2/67/329450


Full Text



 Introduction



Despite global concerted efforts to control malaria, it remains a major public health challenge in most endemic regions. As a devastating disease, it constitutes a drag to economic progress and development in highly endemic regions.[1],[2],[3],[4] The 2018 world malaria report revealed that there were 228 million cases of malaria and an estimated 405,000 deaths in 2018, with Africa accounting for 90% of the cases and 94% of death, respectively. Although malaria is both treatable and preventable, it accounts for several deaths in Africa annually. Malaria is the major cause of under-five and maternal mortalities in Nigeria.[5] The disease accounts for 25% of maternal death in Africa because pregnant women are four times more likely to get sick from its attack and two times more likely to die when compared to nonpregnant women.[6] This is because a pregnant woman's immunity declines due to increased levels of cortisol,[5] especially in the early stages of pregnancy, thereby weakening their response to malaria attacks. Malaria accounts for 15% anemia, 5%–14% low birth weight (LBW), 30% of preventable LBW and an estimate of 300 million cases (90%) in Africa.[7] Malaria in pregnancy poses a substantial risk to both pregnant women and their unborn babies, as it may result in spontaneous abortion, maternal anemia, underweight babies, intrauterine growth retardation, stillbirth, and LBW.[5],[8] Malaria control strategies in Nigeria include early diagnosis, case management and treatment of malaria and promotion of the use of Insecticides Treated Nets (ITNs).[9],[10]

In Africa, malaria poses a significant negative effect on economic growth and perpetuates vicious circles of poverty, as it results in the USA $ 12 billion loss in Gross Domestic Product per annum.[11] According to Gallup and Sachs,[12] malaria-endemic countries grow by 1.3% slower than nonmalarious economies. In Nigeria, malaria remains a major source of loss in economic productivity, as it negatively affects household income. Malaria-related illness accounts for 60% of outpatient visits, 30% of hospitalization among under-five children in Nigeria.[13]

The cost of malaria attack is divided into direct, indirect, and intangible cost.[6],[14],[15] The direct cost of malaria is a combination of personal expenses, public expenditure, and external finances (like donor) incurred in the prevention and treatment of malaria.[15] The indirect cost is foregone income due to malaria attack. Malaria has a direct impact on household's income, wealth, labor productivity, and labor market participation of both the sick and their caregivers.[16] Osakede and Lawanson[17] estimated that 50% of Nigerian adult population experienced loss in labor contribution due to malaria attack with the indirect cost of about N5, 532.59 ($37.16) and N4, 828.73 ($ 32.43) per person per day for patient and caregiver respectively.[4]

The direct cost of malaria accounts for over 50% of the total costs of malaria attack, and on average, each episode of malaria will result in between 6 and 9 days of loss in active, productive time.[6],[16] The huge indirect cost has implications on household's decisions on malaria treatment since most Nigerian households pay for malaria treatment out-of-pocket (OOP). There are reports on self-medication and suppression of health needs due to over-reliance on OOP health-care payment arrangements.[18],[19] Several persons in Nigeria treat malaria with herbal medicine because it is cheaper than pharmaceutical drugs, and the belief that it is more effective with no side effects.

To reduce the prevalent rate of malaria, many national and international arrangements were made. Prominent among these is the signing of the Abuja Declaration in 2001 on Roll Back Malaria (RBM), which aimed at increasing the coverage of ITNs among pregnant women to 60% in 2010.[20]

In response to the RBM, the Nigerian government set up the National Malaria Control Strategic Plan (NMCSP) (2009–2013) with the intent to address both national health and development priorities. It addressed malaria control through three core interventions: the use of Integrated Vector Management Strategy in preventing malaria transmission, encouraging prompt diagnostic tests of malaria and ensure adequate treatment of clinical cases at all levels and in the entire health sector and finally, prevention and treatment of malaria in pregnancy.

By the end of the NMCSP, the 2014–2020 national strategic plan for malaria control was developed and the plan emphasized massive scale-up of interventions to reduce the burden of malaria. While it was expected that such a massive scale of interventions will significantly alter the epidemiological profiles of malaria in Nigeria, evidence has shown the contrary.

For the last 5 years preceding the recent National Demographic and Health Survey,[10] only 58% of pregnant women slept under some type of mosquito nets and only 40% of women who had a live birth in the 5 years preceding the survey were administered with at least 2 or more doses of Sulfadoxine-Pyrimethamine (S-P)/fansidar during their pregnancies.[10]

In Nigeria, several studies have explored predictors of malaria prevention and control among pregnant women.[21],[22],[23],[24] However, there is a dearth of research on pregnant teenagers attending antenatal care (ANC) in Nigeria. Therefore, this study investigated the predictors of malaria prevention and control among pregnant teenagers (13–19 years) attending ANC in four Primary Healthcare Centres (PHCs) in the rural part of Delta State, Southern Nigeria. This study, therefore, attempts to bridge this existing gap.

 Methods



Study settings

This study was a facility-based cross-sectional study that employed a quantitative data collection method to assess the predictors of malaria prevention practices among pregnant women attending ANC in four communities in Ughelli North local government area (LGA) in Delta State. Ughelli North is one of the twenty-five LGAs in Delta state. It lies between 9° 45 'N and 8° 43'E. It has a landmass of 818 km2. The population census of 2006 puts the population figure at 321,028, with a population density of 460.1 people/km2. While females constitute 49.9% of the population, people within the age bracket 15–64 years constitute 57.6%. Administratively, the LGA comprises 11 wards with many communities situated in each ward. The primary source of maternity care in the LGA is PHCs, although several private hospitals exist in the LGA that renders various degrees of maternal health-care services. There are 30 public PHCs in the LGA, with 18 PHCs per 10,000 of the population.[25]

Study population, sampling techniques, and data source

The population of the study is all pregnant teenagers attending ANC in the selected four PHCs located in Ughelli North LGA in Nigeria. Women who were seen on the premises of the facilities at the time the research team visited those facilities were recruited in the survey. The sample size for the study was worked out using the formula for estimating sample size, that is for large population size for population is >10,000, [INSIDE:1] where n = estimated sample size; z = critical normal variate for 95% confidence interval = 1.96; P =percentage of pregnant women that used malaria prevention practices; q = the complementary probability of P (1 −p) that is, percentage of pregnant women not utilizing malaria prevention care and d = error margin at 5% = 0.05.

In light of the absence of a study that reported the rate of malaria prevention practices among pregnant women in the rural part of Nigeria, we assumed a 50% utilization rate.[26] Hence, P = 0.50, while q = 1 − 0.50 = 0.50, then the estimated minimum sample size required for the study is [INSIDE:2],

[INLINE:1]

A multi-stage sampling technique was used in selecting respondents for the study. Ughelli North LGA has eleven political wards that served as health administrative units. Each of the political wards has several communities. While some of the communities have PHCs, others do not. In the first stage, four political units were randomly selected. In the second stage, one community that has PHC was selected in each of the four political wards using simple random sampling techniques. The study location was the PHCs in each of the selected communities. In the third stage; we allocated the estimated sample size among the four PHCs using the proportional sampling technique, which was based on the number of pregnant women that registered for ANC in each of the facilities. In the fourth stage, the number of clients interviewed for each of the facilities was worked out by dividing the average monthly antenatal attendance for the health facility by the total monthly antenatal attendance for the four facilities. We gathered after preliminary visitation to the four facilities that the total monthly antenatal attendance for the four facilities was 400. The sample size for each of the facilities is therefore worked below.

The proportion for each health centre

[INLINE:2]

Anticipating a 10% nonresponse rate, we adjusted the sample size estimate to account for nonresponse rate by dividing the sample size calculated with a factor f, that is, n/f, where f is the assumed rate of response, which in this study is 90%.[27] Thus, our estimated sample size was readjusted [INSIDE:3] = 427. Thus, 427 questionnaires were administered, entered into the software and were thus analyzed.

For Agbarha-otor PHC, the average monthly antenatal attendance is 132. Hence, the number of clients interviewed was 132 × [INSIDE:4] = 141.

Ekrerhavwe PHC, the average monthly antenatal attendance, is 138. Hence, the number of clients interviewed was 138 × [INSIDE:5] = 147.

Ovara Unukpo PHC, the average monthly antenatal attendance is 50. Hence, the number of clients Interviewed was 50 × [INSIDE:6] = 53.

For Evwereni PHC, the average monthly antenatal attendance is 80. Hence, the number of clients interviewed was 80 × [INSIDE:7] = 85.

In the final stage, eligible and consenting respondents attending ANC in the four facilities were recruited into the survey. The research team visited each of the facilities until the required number allotted to each selected facility was obtained. Consented clients were interviewed at the exit point from PHCs after they must have been attended to at the PHCs.

Data collection procedure

A pretested structured questionnaire was used to elicit information from 427 pregnant teenagers attending ANC in four PHCs in the study area. The questionnaire was first administered to 8 women in PHCs in Emevor, a nearby community to the research communities, and tested for reliability. The questionnaire elicited information on women's sociodemographic characteristics, maternal care behavior, malaria prevention and control, and barriers to maternal care utilization from PHCs. The questionnaire was administered through the aid of trained field Research Assistants. The questionnaire was administered through face-to-face interview with respondents.

Outcome indicators

Three malaria prevention and control indicators were examined. They were the use of indoor residual sprays (IRSs), sleeping under ITNs, and intermittently treating malaria in pregnancy (IPTP) using fansidar. Three of the indicators were binary, with responses of yes coded 1 and No coded 0.

Independent variables

Three of the indicators (IRS, ITNs, and IPTp) were regressed on various predictors. Drawing from the model of health service utilization and past studies on malaria prevention practices in Nigeria,[11],[12],[13],[14] the following independent variables were included in the study: maternal age, maternal education; religion, woman's employment status, marital status, Number of children ever given birth to, experience with pregnancy-related complications, the intention of pregnancy, breadwinner of the home, knowledge of at least two pregnancy-related complications due to malaria, partake in household's health decision, partake in household's decisions on choice of food to cook and freedom to spend own income.

Data analysis

Data collected were cleaned coded, and entered into excel format. Coded data were analyzed with Stata version 13.0 for windows(Stata Corp LP, College Station, TXS USA) for windows. Univariate analysis involving percentages and frequencies was conducted to describe the summary statistics of the included variables. Test of association involving the use of Chi-square was used to test the level of association among the included variables. Multivariate logistic regression was performed to identify significant predictors, all at a 5% level of significance.

Ethical approval

Approval to conduct the study was obtained from the University of Benin Ethics Review committee. Written approval to access PHCs was obtained from the PHCs board at Ughelli North LGA, Delta State. Because of the high rate of illiteracy in the study area, verbal consent was obtained from participants.

 Results



Demographic characteristics of study participants

In [Table 1], the characteristics of the study participants are presented. Majority of the women were within the age group 18–19 (59.7%). Approximately 43% of them had the primary educational qualification, while only 5.6% had tertiary educational qualifications. A higher proportion of the respondents were affiliated with other Christians (47.5%). Approximately 57% of teenage mothers were married and living with their husbands. Most of the teenage mothers reported the birth of at least three children (51.5%). Majority of the women did not desire their pregnancies and only 41.5% of them were able to mention at least two pregnancy-related complications that are due to malaria. Approximately 48% partake in making household health decisions, and 57% partake in making household's decisions on choice of food to cook. Only 17.3% of them were engaged in economic activities outside the homes. Consequently, 74.2% of them depended on their husbands as their breadwinners. Conclusively, malaria prevention and control practices were low among the participants, as only 50.1% of them reported sleeping under ITNs, 49.2% were using IRS and 38.4% intermittently treat malaria in pregnancy (IPTp).{Table 1}

Bivariate analysis

In [Table 2], the relationship between the various sociodemographic characteristics of pregnant teenagers and malaria prevention practices, such as the use of IRS, sleeping under ITNs and intermittently treating malaria while pregnant is presented.{Table 2}

Factors associated with indoor residual spray

In [Table 2], factors significantly associated with the use of IRS are maternal education, partaking in household health decision, woman's employment status, intention of pregnancy, experience with complications, knowledge of at least two pregnancy-related complications due to malaria, and the number of children ever given birth to. About 44.1% of those with no formal education or primary education used IRS compared to 63.4% with secondary or tertiary education. This makes a difference of 19.3%. While 55.6% of teenage mothers who were partaking in making household health decisions used IRS, for those who were not it was 46.4%. Women's employment status significantly influenced the use of IRS. Approximately 69% of employed teenagers used IRS and only 47% of unemployed ones did the same. Intention of pregnancy was significantly associated with the use of IRS. While about 67% of teenagers who desired their pregnancies use IRS for those who did not desire, it was 44%. Experience with pregnancy-related complications was significantly associated with the use of IRS. About 44% of teenagers who had no prior experience with pregnancy-related complications used IRS for those who had it was 61% making a difference of 17%. Knowledge of at least two pregnancy-related complications due to malaria was significantly associated with the use of IRS. While 72% of teenagers who could mention at least two pregnancy-related complications due to malaria used IRS for those who could not it was 47%. The number of children ever given birth to significantly influence the use of IRS. About 66% of teenagers with 0–1 child used IRS and for those who reported 2 children, it was 30.6%.

Factors associated with insecticide treated net

Sleeping under ITN were significantly associated with maternal education, partake in household's health decisions, woman's employment status, intention of pregnancy, experience with pregnancy-related complications, knowledge of at least two pregnancy-related complications due to malaria and number of children ever given birth to. About 85.3% of teenagers who had no formal education or primary education slept under ITNs compared to 32.4% of those who had secondary or tertiary education. This made a difference of 52.9%. Roughly, 67% of teenagers who partake in making household health decision slept under ITN and 34.5% who did not partake in such decisions slept under ITNs. About 39.2% of employed teenagers slept under ITN compared to 52.4% of those not employed. Approximately 59.5% of those who did not desire pregnancy slept under ITN compared to 29.3% who desired their pregnancies. This makes a difference of 30.2%. Roughly 67% of teenagers who had no experience with pregnancy-related complications slept under ITN compared to 27% with such experience, making a difference of 40%. About 85% of teenage mothers who reported between 0 and 1 child slept under ITN compared to 31.8% of those with at least three children.

Factors associated with Intermittent preventive treatment of malaria

Intermittently treating malaria in pregnancy were significantly associated with maternal education, partake in household's health decisions, freedom to spend own income, partaking in household choice of food, woman's employment status, the intention of pregnancy, experience with pregnancy-related complications, knowledge of at least two pregnancy-related complications due to malaria and number of children ever given birth to. About 15.8% of teenagers with no formal education or primary education intermittently treated malaria in pregnancy compared to 79.8% of those with secondary or tertiary education. Roughly 59% of teenagers who partake in making household health decisions intermittently treated malaria in pregnancy and 19% who did not partake in such decisions did the same. Approximately 16% of teenagers who did not report freedom in spending own income intermittently treated malaria in pregnancy compared to 56% of those who did. Furthermore, 45.7% of teenagers who partake in making household decision on the choice of food intermittently treated malaria in pregnancy compared to 28.6% of those who did not. About 16.2% of employed teenagers intermittently treated malaria in pregnancy compared to 43.1% of those not employed. Approximately 53.1% of those who did not desire pregnancy intermittently treated malaria in pregnancy to 6.0% who desired their pregnancy. This makes a difference of 46.9%. Roughly 62.8% of teenagers who had no experience with pregnancy-related complications intermittently treated malaria in pregnancy compared to 4.0% with such experience, making a difference of 58.8%. About 85% of teenage mothers who reported between 0 and 1 child intermittently treated malaria in pregnancy compared to 14.5% of those with at least three children.

Multivariate results

In [Table 3], results of the multivariate analysis using binary logistic regression showing predictors of malaria prevention practices is presented.{Table 3}

Predictors of indoor residual spray

In [Table 3], the predictors of IRS are presented. Those who reported secondary educational qualification (adjusted odds ratio [aOR]: 2.72, P = 0.01) were approximately three times significantly more likely to use IRS while pregnant. Those who did not partake in household health decisions (aOR: 0.37, P < 0.01) were significantly less likely to use IRS. Those who desired pregnancy (aOR: 2.59, P = 0.02) were approximately three times significantly more likely to use IRS. Those who once experienced pregnancy-related complications (aOR: 2.20, P = 0.04) reported an approximately 2-fold increase in the odds for using IRS.

Predictors of insecticide treated nets

In [Table 3], the predictors of ITNs were presented. Those who had secondary educational qualification (aOR: 5.27, P < 0.001) reported an approximately 5-fold increase in the odds for sleeping under ITNs. In comparison to those who partake in making household health decision, those who do not (aOR: 0.60, P = 0.06) were significantly less likely to sleep under ITNs. Those who desired pregnancy (aOR: 2.83, P = 0.03) reported an approximately 3-fold increase in the odds for sleeping under ITNs. In reference to those who reported 0–1 child, those who reported 2 (aOR: 0.37, P = 0.01) and ≥3 (aOR: 0.22, P < 0.001) were significantly less likely to sleep under ITNs.

Predictors of intermittently treat malaria in pregnancy

In [Table 3], the predictors of IPTp are presented. In reference to those who reported no formal education, those who had secondary educational qualifications (aOR: 9.23, P < 0.001) and tertiary educational qualifications (aOR: 6.16, P = 0.04) were significantly more likely to IPTp. Those who desired their pregnancies (aOR: 7780584, P = 0.01) were significantly more likely to IPTp. In reference to those who reported 0–1 child, those who reported 2 (aOR: 0.22, P < 0.001) and ≥3 (aOR: 0.09, P < 0.001) were significantly less likely to IPTp.

 Discussion



In this study, we investigated the sociodemographic factors influencing malaria prevention practices among 427 pregnant teenagers drawn from four PHCs in Ughelli North LGA in Delta State, Southern Nigeria. The study was motivated by the fact that there was high malaria prevalence among pregnant women in Nigeria;[26],[28] despite this, several Nigerian women do not utilize malaria prevention practices.[6] Furthermore, there is a high patronage of traditional herbal medicine and self-medication by pregnant women.[6] There is no scientific proof of the efficacy of several herbal medications pregnant women take in Nigeria. The result revealed that 50.1% of the respondents slept under ITNs, 49.2% reported they were using IRS and 38.4% were intermittently treating malaria in pregnancy taking fansidar. The rates are below the targeted rates for the various indicators. For instance, NMCSP (2009–2013) targeted that 100% of pregnant women should take two doses of S-P, while an additional dose should be taken by pregnant women that are human immune virus positive.[21]

The study results showed that teenage mothers who were not employed were 54% significantly less likely to use IRS. Women's employment status is used as a proxy for household socioeconomic status in this study. This finding, therefore, corroborates findings from several other studies which reported strong ties between household socioeconomic status and malaria prevention practices.[6],[29],[30] This does not come as a surprise since the amount of money kept for malaria treatment can only be gotten from one's income and respondents who were not employed may not have savings to pay for malaria treatment and control methods. Hence, to reduce the socioeconomic costs associated with malaria burden, prevention controls should be made affordable to unemployed rural women, particularly teenage mothers.

We found out that maternal education significantly influences the three indicators (that is ITNs, IRS, and IPTp). Teenage mothers that reported both secondary and tertiary educational qualifications were significantly more likely to sleep under ITNs, use IRS and IPTp by taking fansidar. For instance, respondents who reported secondary education were respectively 172%, 429%, and 823% significantly more likely to use IRS, sleep under ITNs and IPTp. This study, therefore, confirms the benefit of education in malaria adherence and control. The same finding was reported by a Nigerian study[24] and study elsewhere.[6] In another study conducted in Sunyani Municipality, Ghana, Ibrahim et al.[31] reported that education was significantly related to at least three doses of S-P. The effect of maternal education on malaria adherence and control is because better-educated women understand the complications that may result from a malaria attack and they are ready to get the best treatment for it. There is a need to develop health programs that educate pregnant women on the transmission mechanism of malaria, the control methods and the consequences of noncontrol or treatment.

We also found out that a teenage mother who reported at least two children were less likely to adhere to malaria prevention and treatment. The finding is in harmony with a Ghanaian study,[23] which reported that mothers with several births were less likely to use S-P. This may be due to either overcrowdedness in the home or stress associated with children's upkeep.

The results showed that teenage mothers who could mention at least two pregnancy-related complications due to malaria attacks were 81% significantly more likely to use IRS. Hence, knowledge is power and better-informed teenage mothers will take precautionary measures to protect themselves from malaria attack. Finally, teenage mothers who once experienced pregnancy-related complications were 120% significantly more likely to use IRS. This is because the experience is the best teacher.

Limitations of the study

The findings from this study should be viewed in light of certain limitations. First, the report analyzed is verbal without any form of validation. Second, it may not be possible to generalize the findings from the study because of limited scope.

 Conclusion



The study concluded that the rate at which teenage mothers adhere to malaria control is low; hence intervention programs designed to improve their access should target illiterate and unemployed teenage mothers.

Acknowledgements

The authors wish to appreciate all the research assistants who helped in gathering the data.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.

References

1Malaney P. Microeconomic Approaches to Evaluating the Burden of Malaria, CID Working Paper. Centre for International Development at Harvard University; 2003. Available from: https://www.ideas.repec.org/cid/wpfacu/99. [Last accessed on 2019 May 24].
2Okorosobo T, Okorosobo F, Mwabu G, Orem JN, Kirigia JM. Economic burden of malaria in six countries of Africa. Eur J Bus Manag 2011;3:42-62.
3Ahuru, RR, Onwumah OE. Determinants of Choice of Treatment by Tuberculosis Patients in Nigeria, Amity Journal of Health Care Management 2019;4:1-14.
4Ahuru RR, Osaze D, Henry EA.What role does health play in enhancing labour productivity in Nigeria? Academic Journal of Economic Studies 2020;6:102-11.
5Enato EF. Malaria in pregnancy and its reproductive health effects. In: Okonofua FE, editor. Reproductive Health Challenge for Africa. Boston: Brown Walker Press; 2014. p. 213-9.
6Dako-Gyeke M, Kofie HM. Factors influencing prevention and control of malaria among pregnant women resident in urban slums, Southern Ghana. Afr J Reprod Health 2015;19:44-52.
7Chukwuocha UM, Dozie IN, Chukwuocha AN. Malaria and its burden among pregnant women in parts of the Niger Delta area of Nigeria. Asian Pac J Reprod 2012;1:147-51.
8Sabina K. Prevalence and epidemiology of malaria in Nigeria: A review. Int J Res Pharm Biosci 2017;4:10-2.
9Onwujekwe O, Malikel P, Mustafa SI, Mnzavaa A. Do malaria preventive interventions reach the poor? Socioeconomic inequities in expenditure on and use of Mosquito control tools in Sudan. Health Policy Plan 2006;21:10-6. Doi. 10.1093/heapol/czj004.
10National Population Commission. Nigeria Demographic and Health Survey. Abuja: National Population Commission; 2018. p. 630.
11Tabbabi A. Socioeconomic impact of malaria in Africa. ACTA Sci Microbiol 2018;1:32-34.
12Gallup JL, Sachs JD. The economic burden of malaria: A new look at the number. Am J Trop Med Hyg 2001;64:85-96.
13The World Health Organization Fact Sheet about Malaria. Available from: https://www.who.int/news room/fact sheet/detail/malaria.[Last accessed on 2019 May 08].
14Ahuru RR, Iseghohi JO. The economic burden of malaria, evidence from Nigeria's data. Amity Journal of Healthcare Management 2018;3:28-39.
15Sede IP. Government expenditure and Malaria in Nigeria. J Manag Soc Sci 2017;3:1-10.
16Alaba OA, Alaba OB. Malaria in Children: Implication for the Productivity of Female Care Gives in Nigeria, Selected Paper for the Conference of the Nigeria Economic Society titled Human Resource Development in Africa; 2002.
17Osakede UA, Lawanson AO. Cost Burden of malaria: Evidence from Nigeria. Asian J Hum Soc Stud 2016;4:266-77.
18Onwujekwe OE, Uzochukwu BS, Obikeze EN, Okoronkwo I, Ochonma OG, Onoka CA, et al. Investigating determinants of out-of-pocket spending and strategies for coping with payments for healthcare in Southeast Nigeria. BMC Health Serv Res 2010;10:67.
19Omotosho O, Ichoku HE. Distributional analysis of household health expenditure in Nigeria. Dev Ctry Stud 2016;6:111-9.
20Onwujekwe O, Okereke, E, Onoka C, Uzochukwu B, Kirigia J, Petu A. Willingness to pay for community-based health insurance in Nigeria: Do economic status and place of residence matter? Health Policy Plan 2010;25:155-61.
21Ankomah A, Adebayo SB, Arogundale ED, Anyant J, Nwokolo E. Determinants of Insecticide-treated net ownership and utilization among pregnant women in Nigeria. BMC Public Health 2012;12:105.
22Oladimeji EK, Tsoka-Gwegweni JM, Gengiah S, Daftany A, Naido K. Barriers to effective uptake of malaria prevention interventions in Ibadan, South-West Nigeria: A qualitative study. Int J Community Med Public Health 2018;5:1304-10.
23Diala C, Pennas T, Choi P, Rogers S. Barriers to Uptake of Malaria Prevention and Treatment during Pregnancy in Cross River State and Nasarawa State, Nigeria. Washington, DC: C-chge/FHI360.
24Olorunfemi EA, Ariba AA, Iyaniwura C. Determinants of intermittent preventive treatment of malaria during pregnancy (IPTp) utilization in a rural town in Western Nigeria. Reprod Health 2012;9:12.
25UNDP and Delta State. Delta State Development Performance Delta UNDP Health Sector Report, 1991-2013; 2014. Available from: http://www.undp.org/content/dam/Nigeria/docs. [Last accessed on 2016 Aug 16].
26Okonofua F, Ntoimo L, Ogungbangbe J, Anjirin S, Imonghan W, Yaya S. Predicto rs of women utilization of PHC for skilled pregnancy care in rural Nigeria. BMC Pregnancy Child 2018;18:106.
27Nnebue CC, Ebenebe UE, Adogu PO, Adinma ED, Ifeadike CO, Nwabueze AS. Adequacy of resources for provision of maternal health services at the Primary Health Care level in Nnewi, Nigeria. Niger Med J 2014;55:235-41.
28Federal Ministry of Health. National Malaria Strategic Plan 2009-2013. Abuja, Nigeria: Federal Ministry of Health; 2009.
29Gamage-Mendis AC, Carter R, Mendis C, De Zoysa AP, Herath PR, Mendis KN. Clustering of malaria infections within an endemic population: Risk of malaria associated with the type of housing construction. Am J Trop Med Hyg 1991;45:77-85.
30Alemu A, Tsegayem W, Golassa L, Abebe G. Urban malaria and associated risk factors in Jimma town, South-West Ethiopia. Malar J 2011;10:173.
31Ibrahim H, Maya ET, Issah K, Apanga PA, Bachan EG, Noora CL. Factors influencing uptake of intermittent preventive treatment of malaria in pregnant women using sulfadoxine-pyrimethamine in Sunyani Municipality, Ghana. Pan Afr Med J 2017;28:122.