Social And Environmental Determinants Of Prevalence Of Malaria In Umudibia Nekede, Owerri West Local Government Area, Imo State
Social And Environmental Determinants Of Prevalence Of Malaria In Umudibia Nekede, Owerri West Local Government Area, Imo State
Abstract
The present study on social and environmental determinants of prevalence of malaria was carried out in Umudibia Nekede, Owerri West local Government area of Imo state between May and September, 2017. Researched structured questionnaire and in-depth interview were used to get personal data of participants.
Blood samples were obtained from 400 consented participants from the four zones in Umudibia. mRDT and blood film examination using rapid Giemsa staining techniques were used to detect presence of malaria parasite. Only Plasmodium falciparum was sought for as the mRDT kit was only specific for the species.
The age group 1-10 years had the highest malaria prevalence of 28.6% while the age group 21-30 had the least prevalence of 18.8%. (Not yet complete).
Table Of Contents
Preliminary Page(s)
- Content page
- Title page
- Declaration
- Certification
- Approval page
- Dedication
- Acknowledgements
- Abstract
- Table of contents
- List of figures
- List of plates
- List of Appendices
Chapter One
Introduction and Literature Review
- 1.1 Introduction
- 1.2 Aim and objectives of the study
- 1.3 Justification of the study
- 1.4 Literature review
- 1.5 History of malaria
- 1.6 Malaria Disease and burden
- 1.7 Mode of Transmission
- 1.8 Life cycle of malaria parasite
- 1.9 Vectors of malaria
- 1.10 Pathological aspect
- 1.11 Diagnosis
- 1.12 Control and prevention
Chapter Two
2.0 Materials and Methods
- 2.1 Study area
- 2.2 Ethical consideration
- 2.3 Study population
- 2.4 Sample collection
Chapter Three
3.0 Results
Chapter Four
4.0 Discussions and Recommendations
- 4.1 Discussions
- 4.2 Recommendations
- References
- Appendices
- List of figures
Chapter One
Literature Review
1.1 Introduction
Malaria has continued to be a major public health problem in the World today despite concerted efforts aimed at its control and elimination. The organism that causes the illness (Plasmodium) spends parts of its life cycle in the mosquito and the other in man (Gupta and Ghai, 2007). Malaria portends a serious present and future global concern. It is present in over one hundred countries worldwide and responsible for over 100 million clinical cases and an estimated 1-2 million deaths annually.
However, the burden of mortality and morbidity is worse in poor countries and amongst the most disadvantaged in these countries. The World Health Organization (WHO) suggests that Africa bear almost 90% of the global burden of malaria. Nigeria, due to its population of over 160 million people bears the largest share of the burden (300, 000 malaria related deaths annually, especially in children under 5 years). Nigeria with three other countries, suffer about 50% of global malaria mortality (WHO, 2012; 2010).
The last couple of decades, especially the 1950s onward, have witnessed unprecedented global interest and efforts towards eradication of malaria (Stratton et al., 2008). Programs such as the Roll Back Malaria Initiative (RBM) and the Multilateral Initiative on Malaria (MIM) have seen international donor organizations (public and private) spend millions of dollars on malaria eradication programs (Williams and Jones, 2004). Unfortunately, the results have not been completely positive. Today, despite decades of concerted global efforts, malaria related mortality is higher than half a century ago (WHO, 2010). Malaria has become the most important vector borne disease in Africa.
Today, scholars are arguing that the growing malaria epidemic in some African countries rest partly on the social, cultural and environmental factors peculiar to these countries that are often ignored in the design and implementation of malaria interventions (Jombo et al., 2010). There is a growing consensus that for interventions to succeed, they must focus on the fundamental causes of malaria by addressing the socio-cultural, behavioural and environmental dimensions of risks driving the malaria epidemic (WHO, 2012; 2010).
Many variables have been found to affect malaria transmission in addition to climatic changes. These are environmental modification (e.g., deforestation, increases in irrigation, blocked swamp drainage), population growth, limited access to health care systems, and lack of or unsuccessful malaria control measures (Patz and Lindsay, 1999). Most of the studies, however, do not take into account all of the factors that are related to malaria transmission.
Although malaria is one of the most climate-sensitive vector-borne diseases (Morse, 1995), several other factors have been identified as contributing to its emergence and spread. These include environmental and socio-economic change, deterioration of health care and food production systems, and the modification of microbial/vector adaptation (McMichael et al., 1998; Morse, 1995; Epstein, 1992).
1.2 Justification Of Study
Malaria is a serious problem in Africa where one in every five (20%) childhood deaths ids due to the effects of the disease (Sachs and Malaney, 2002). There were an estimated 216 million episodes of malaria in 2010, of which approximately 81% or 174 million cases were in African Region.
The control of malaria involves three living beings (man, mosquito and larva) and their environment. Man is highly mobile and able to facilitate the spread of the disease far and wide mosquitoes are moving and highly adaptable (Najera and Zaim, 2003). Eggs and larvae are highly adaptable to various environmental situations.
This interrelationship of the various living beings sustaining the burden of malaria can be described as malaria chain. Thus, malaria control involves measures that are deployed to disrupt the chain in order to reduce malaria burden to a point where it is not of public health importance. Makuola et al., 2014).
Effective malaria control must leverage on the various opportunities to interrupt the critical challenge of man, mosquito and larva. Since the year 2000, great progress has been made in tackling the disease, with massive campaigns to distribute insecticide-treated mosquito bed nets, to spraying homes with insecticide to kill adult mosquitoes and use of drugs for disease prevention and treatment (all targeted towards man as host and mosquitoes) have been the focus of malaria control efforts.
These strategies have helped reduce global malaria mortality by a quarter in the past decade. However, this success is now threatened by resistance to drugs and chemicals in the malaria parasite and its mosquito carriers, which could render insecticide treated bed nets, indoor residual spraying and widely available drugs less effective.
The environmental dimensions of malaria chain as regarding egg and larval reduction through larviciding is not very prominent in discussions on malaria control. In addition, the impact of environmental factors, while generally acknowledged, has not been properly researched in Nigeria, especially in the Eastern part of the country, and Imo state, in particular, as is evident in very few publications on this area.
The absence of such knowledge among the inhabitants of the study may have contributed to their inability to prevent malaria transmission and thus increase disease prevalence. This dearth of research in this area thus makes it imperative for further research to be made in order to create awareness. This will in turn help to reduce the incidence of infection on the part of the populace
1.3 Aims And Objectives Of The Study
1.3.1 Aim
The main aim of this study is to investigate the social and environmental determinants of malaria in Umudibia, Nekede, Owerri-West, L. G. A, Imo State.
1.3.2 Specific Objectives Are;
- To ascertain the overall malaria prevalence/status in the study area.
- To determine the relationship between socio-demographic characteristics and malaria status in the area.
- To ascertain the relationship between social and environmental factors and malaria status in the area.
- To determine the relationship between housing characteristics and malaria status.
- To ascertain the relationship between malaria status, environmental factors and level of awareness.
1.4 Research Questions
- What is the overall malaria prevalence/status in the study area?
- What is the relationship between the socio-demographic characteristics and malaria status in the study area?
- What is the relationship between social and environmental factors and malaria status in the area?
- What is the relationship between housing characteristics and malaria status in the area?
- What is the relationship between malaria status, environmental factors and level of awareness?
1.5 Research Hypothesis
- H0: There is no significant relationship in the overall malaria prevalence/status in the study area.
Ha: There is significant relationship in the overall malaria prevalence/status in the study area. - H0: There is no significant relationship between demographic characteristics and malaria prevalence in Umudibia, Nekede.
H0: There is significant relationship between demographic characteristics and malaria prevalence in Umudibia Nekede - H0: There is no significant relationship between social and environmental factors and malaria status in the area.
Ha: There is significant relationship between social and environmental determinants and malaria status in the area. - H0: There is no significant relationship between housing characteristics and malaria status in the area.
Ha: There is significant relationship between housing characteristics and malaria status in the area. - H0: There is no significant relationship between malaria status, environmental factors and level of awareness.
H4: There is significant relationship between malaria status, environmental factors and the level of awareness.
1.6 Literature Review
Malaria is a mosquito-borne infectious disease of humans caused by eukaryotic protists of the genus Plasmodium (Phylum Apicomplexa). In humans, malaria is largely caused by P. falciparum, P. malariae, P. ovale, and P. vivax. Fong et al., (1971) and Singh et al., (2004) noted a fifth species, Plasmodium knowlesi, a zoonosis that causes malaria in macaques but can also infect human. Plasmodium falciparum is the most common cause of infection and is responsible for about 80% of all malaria cases, and is responsible for about 90% of the deaths from malaria (Mendis et al, 2001). Malaria caused by Plasmodium vivax, Plasmodium ovale and Plasmodium malariae is generally a milder disease that is rarely fatal.
These four major species causing human malaria differ morphologically, immunologically, in geographical distribution relapse pattern and in drug response.
- Plasmodium vivax, which is synonymous with Haemamoeba vivax, is the cause of vivax or benign tertian malaria. It is the most common malaria is more common in the Americas and Asia than in the tropical region.
- Plasmodium ovale is the cause of ovale malaria or ovale tertian. It is the least common malaria parasite of man and restricted to West Africa, principally on the West coast. Ovale malaria produces a mild illness.
- Plasmodium malariae is the cause of malariae or quartan malaria. It is found in isolated places scattered across the globe such as tropical Africa, Burma, Sir Lanka, and some parts of India. Though it cause severe fever, quartan malaria is usually not life threatening.
- Plasmodium falciparum is the cause of malignant sub-tertian or falciparum malaria. The specific name “falciparum” was derived by Welch from “falx” (sickle or crescent) and “parere” (P. falciparum is the cause of the most severe, often fatal form of the disease. It remains almost unchallenged as one of the greatest killers of human race over most part of tropical Africa and elsewhere in the tropics. In the past, Plasmodium falciparum used to be common in the southern United States of America and along the Mediterranean shores but now it is rare in these areas following malaria eradication programmes. (Beaver et al., 1984).
Malaria is widespread in tropical and subtropical regions, including much of Sub-Saharan Africa, Asia and the Americas. The disease results from the multiplication of malaria parasites within red blood cells, causing symptoms that typically include fever and headache, in severe cases progressing to coma, and death. Each year, Philips (2010) reported that there are more than 225 million cases of malaria, killing around 781,000 people each year.
The majority of deaths according to Snow (2005) are young children in sub-Saharan Africa. Ninety percent of malaria-related deaths occur in sub-Saharan Africa. Malaria is commonly associated with poverty, and can indeed be a cause of poverty (Institute for the Study of Labor, 2008), as well a major hindrance to economic development.
Chapter Four
4.0 Discussion And Recommendation
4.1 Discussion
The study investigated social and environmental determinants of malaria prevalence in Umudibia Nekede, Owerri West Local Government Area of Imo state. The overall malaria prevalence (51.3%) in the study population is low compared to values of similar studies carried out earlier within the same geographical area, Aba (86.40%) and Umuahia (74.40%), (Kalu et al.,2012). Aribodor et al., (2003) reported malaria prevalence of 76% in Azia, Anambra state, while Ukpabi and Ajoku (2001) reported prevalence of 80.25% in Okigwe and Owerri, Imo state. The prevalence is also lower than the prevalence reported by Sam Wobo et al., (2014) which revealed an overall prevalence of 71.1% in Ogun state and 53.5% obtained in same state in 2010.(Sam Wobo et al., 2010). This wide range of difference may be attributed to difference may be attributed to difference in climatic factors and behavioural patterns of people in the area which promote mosquito breeding and susceptibility of the people to vector bites. The recent observation which showed markedly reduced malaria prevalence in the area might also reflect an improvement in malaria control strategies such as distribution of insecticide treated bed nets especially to the most vulnerable groups (children under five years of age and pregnant mothers) and public enlightenment. This agrees with report from Kenya (Okiro et al., 2007) and Cameroun (Kimbi et al., 2013) which showed that malaria morbidity and mortality was on a decline as a result of scale up antimicrobial activities.
The study revealed a significant (P<0.05) influence of sex on the prevalence of malaria status in the area, with males having a higher prevalence (33.8%) when compared with females (17.5%). (Table 3). This agrees with the result obtained by Sam Wobo et al., (2014) in Ogun state, Malcom (2001), Ukpai and Ajoku (2001) in Owerri and Okigwe, in Awka metropolis, Anambra state ( Mbanugo and Ejims, 2000) and in Udi, Enugu state (Ezeanya, 1998). Studies have also shown that females have better immunity to malaria and varieties of other parasitic diseases and this was attributed to hormonal and genetic factors (Mendel and White, 1994) except during pregnancies. This may equally be attributed to the fact that males expose their bodies more often than females, especially when the weather is hot, thus, increasing their chances of being bitten by mosquitoes. The finding also agrees with the finding of Kimbi et al., who recorded that malaria parasite was significantly higher in males than in females.
This result, however, contrasts sharply with findings of Kalu et al., 2012, who recorded a higher parasitaemia in females in Aba (91.2%, n=14) and Umuahia (80.8%, n= 101) than in males in the same area, Aba and Umuahia (81.6% and 68.0%), respectively.
The present study showed that subjects <= 10 years of age had the highest prevalence (28.6%), n=22). Though there were disparities, malaria prevalence was not statistically significant in the various age groups (P>0.05). Kimbi et al., (2013) also reported that children in the youngest age group <= 6 years had significantly high malaria parasite prevalence when compared to the older ones. The result also agrees with Sam Wobo et al., (2014) who recorded that age group 0-10 years had the highest prevalence 94(81%) while the age group 51-60 years had the least 6(54.5%). This may be attributed to low- transferred maternal immunity or infection acquired through the mother. The finding further agrees with the report of Bodker et al., (2006) who stated that acquired immunity is both exposure- and age- dependent, and the older ones are likely to have developed some degree of immunity, as a result of repeated infections. Disparities in age cohort parasitaemia were also observed by Kalu et al., 2012 who reported the highest prevalence (92.3%) among the youths (21-30 years) and the lowest (71.4%) in children (0-10 years) in Aba while in Umuahia, adolescents (11-20 years) had the highest prevalence (90.0%) and the oldest age group (above 60 years) had the least. This could be explained by the fact that during hot weathers, adults are mostly seen sleeping outdoors, sometimes for the whole night, thereby exposing themselves to the risk of mosquito bites. Marital status was not statistically associated with malaria prevalence in the study area (P>0.05). The result shows that singles had the highest malaria prevalence (24.4%, n=40) than the married (19.4%, n=28). This agrees with the report of Sam Wobo et al., 2014. This could be attributed to the married subjects being more conscious of their environment, also coupled with the responsibility of keeping their children safe and healthy were of utmost priorities.
Prevalence of malaria parasitaemia was not statistically significant among the different occupational groups (P>0.05) though it was highest in students (27.3%). This could be due financial constraints to implement necessary mosquito control strategies, and this suggests inadequate protection, greater exposure to mosquitoes. Students also show a laissez-faire attitude towards keeping their environment clean. This is followed by artisans with a disease prevalence of 24.3%. This could be attributed to lack of correct knowledge of malaria transmission. More so, the nature of their job exposes them to bites of the vectors of malaria. Suffixed to this, is that the daily hustle and bustle involved might cause fatigue resulting in deep-sleep nights which favours the uninterrupted blood–sucking tendency of malaria vectors. Business men had the least prevalence (18.5%, n=20). This finding disagrees with the finding of Kalu et al., 2013 who recorded that traders were the most infected in the area.
Further stratification of the prevalence according to educational status gave a non –significant relationship (P>0.05), even though the highest prevalence was found among those with no formal education (). This could be attributed to ignorance and behavioural attitudes. Education invariably affects people’s perceptions about causes of certain diseases of which malaria was not an exception. Lack of knowledge about the consequences of undue exposure to mosquito bites accounted for high prevalence rate of malaria infection. This report also agrees with the report of Sam Wobo et al., 2013.
The association of Umudibia with malaria prevalence is not surprising, since Umudibia is on transition from rural to urban layout with a lot of bushes in many unoccupied plots in-between homes. Mini- farming and a lot of house construction works are going on in the area, thus creating potholes for stagnant water. These probably increase additional breeding sites for malaria vectors. The following variables: Presence Of Drains (POD), Solid Waste in Drains (SWD) and Presence of Weeds (POW) having P-value < 0.05 level of significance contribute significantly as independent variables in explaining the dependent variable, malaria prevalence in the area. Other environmental factors such as Presence of Stagnated Water in Drains (STWD) was not statistically significant (P>0.05) while presence of stagnant water around homes (SWAH) was statistically significant (P<0.05). The finding is supported by Poland et al., (2002) who suggested that permanent natural bodies of water, such as swamps, serve as unique breeding grounds. Kimbi et al., 2013 also recorded that stagnant water around residences was associated with significantly higher malaria parasite prevalence when compared to those who did not have stagnant water. Amenu (2014) recorded the distribution of plasmodium species through stagnant water was 87.5% and through non stagnant water were 12.5%. The study also agrees with the work of Adefemi and Awo (2015) on social and environmental determinants of malaria among under-five children in Nigeria. Pockets of water in flower vases kept around homes, indiscriminately littered tins/tyres and run off from boreholes great pools of water within the study area.
These are good breeding sites for anopheline mosquito vectors of malaria which prefer clean water to polluted one. This suggests that the presence of stagnant water around homes constitutes a risk factor that needs to be taken into consideration, when planning control measures against malaria, as malaria vectors need water for the survival of the immature stages. However, the findings disagree with Nwoke et al., 2017, who stated that environmental factor such as living close to stagnant water was not statistically significant, p> 0.05 while living close to blocked drains and water retaining plants were statistically significant, p<0.05. Availaibilty of Mosquito Nets (AMN) and the use of Insecticide Treated Nets (UITN) having p>0.05 level of significance do not contribute significantly to malaria prevalence in the area. This could be as a result of torn ITNs and the owners were still exposed to mosquito bites. It could also be attributed to lack of re-treatment of the nets or that the owners were already exposed to mosquito bites before retiring to bed.
Furthermore, the use of Indoor Residual Spraying (IRS) probably, in addition to the UITN, leads to a reduction in man- vector contact and thus reduces the transmission of malaria. The result from this study showed that there is a significant (p=0.00, p<0.05) relationship between IRS and malaria status in the area. A comparative study done in Kenya showed that sleeping in a room sprayed with insecticide reduced the risk of infection by 75% while sleeping under an ITN reduced the risk of infection by 63% (Guyatt et al., 2002). The efficacy of IRS has also been demonstrated in several studies in several studies in Peru (Guthmann et al., 2001) and Ethiopia (Bekele et al., 2012). More so, Hamel et al., 2011 recorded that participants who combined IRS and ITNs had 61% reduction in parasitaemia compared with those participants who had ITNs and no IRS. Contrastingly, the findings of this study disagrees with the report of Nwoke et al., 2017 which recorded that none use of ITNs was significantly associated with malaria prevalence (p<0.05).
All the respondents in the study area lived in cement/brick houses. Thus, household type (HHT) may have contributed to the overall low malaria prevalence (51.3%) in the study area. This agrees with the findings of Kimbi et al., (2013) who recorded a higher prevalence in those living in plank than brick houses, the difference, however, was not significant. Protopoff et al., (2009) in a similar work, reported that mosquitoes can easily enter houses constructed of poor materials with open eaves (such as plank houses which usually have crevices on the walls), and these are associated with higher risks of malaria as mosquitoes can easily enter and remain in the sleeping rooms during the night. Ferreira et al., (2012) also reported that individuals who lived in wooden houses and shacks made of black canvas had a higher prevalence, suggesting that those types of housing construction favour the transmission of malaria Some other studies have also reported that wooden houses and huts of canvas do not represent real barriers between the household and the external environment (Santos et al., 2005; Souza-Santos et al., 2008). However, Peterson et al., (2009) did not find any association with malaria incidence and housing quality.
Presence of Business Around Homes (BAH) was also statistically significant (p=0.00, p<0.05) with malaria prevalence (10.0%) was found among those having business around homes than those without. These could be attributed to indiscriminate disposal of waste generated, which could serve as breeding sites for mosquitoes.
Table 5 sought to find out the housing characteristics and their relationship with malaria status. With respect to type of roof present in houses, 40(10.0%) of the respondents lived in tile (ceramic) roofed housed and had a malaria prevalence of 28(70.0%) while those who lived in corrugated/galvanized sheets- roofed houses had 66(18.3%) prevalence. Since the p-value is less than the alpha (0.05), then we conclude that there is a significant relationship between type of roof and malaria status in the area.
All the respondents lived in cement/brick house with an overall malaria prevalence of 51.3%
In relation to water sources for domestic use, 164 (41.0%) stord water in containers inside house and had a malaria prevalence of 29(17.7%). On the other hand, 236(59.0%) stored water within house, out of which 65(27.5%) had malaria parasite. Chi square analysis showed that there is a significant relationship (p<0.05) between water sources and malaria prevalence in the study area. This could be because such stored water was not used up within five days of storage and this time interval encourages the breeding of mosquito larvae (Service, 1999). This suggests that the practice of water storage within the house may be a strong risk practice for malaria transmission, especially among people that store water in open containers (Idowu, 2014). In a similar study by Aziz et al., 2012, it was recorded that storing water inside homes was a routine due to scarcity of water resources and this increased indoor/peri domestic breeding of mosquito larvae. This also correlated with a similar study by Arunachalam et al., (2010). The finding of this study also agrees with similar work by Mafiana et al., (1998) which recorded Anopheles gambiae breeding in domestic containers. However, Idowu (2014) did not find any statistical relationship between women who stored water within house (51.9%) and those who did not.
Out of 85(21.3%) that admitted the presence of agricultural land around house, 40(47.1%) had malaria parasite while out of 315(78.8%) that had no agricultural land around homes, 54(17.1%) showed positive for malaria parasite. P-value < 0.05 show that there is a significant relationship between presence of agricultural land around home and malaria prevalence in the study area. The presence of higher biting rates and sporozoite infective Anopheles in households close to farms than those on the far side of the farms, have shown that malaria parasite transmission could be permanent during the year (Yadouleton et al., 2010). This could be explained by the presence of permanent pools and puddles maintained during watering of vegetables and other crops. This also agrees with the report of Oladepo et al., (2010); Nwoke et al., (2005) and Vennila, (2002).
Table 6 tries to establish the relationship between malaria status, environmental factors and level of awareness. Knowledge of correct signs and symptom was statistically significant (p<0.05) in relation to malaria transmission. Among the 230 (57.5%) of the respondents that identified high fever as the correct sign and symptom for malaria, only 28(12.2%) were positive for malaria. This could have accounted for their seeking for treatment as early as possible, thus the relatively low prevalence (51.3%) in the study area.
Knowledge of environmental factors in malaria transmission was similarly statistically significant. A higher prevalence (35.7%) was seen among those that had no knowledge of environmental factors in malaria transmission. However, only 65(16.3%) had the correct knowledge that indiscriminate waste disposal serves as a major environmental factor that determines malaria transmission in the study area, and thus higher prevalence of malaria (80.0%). Ferreira et al., (2012) reported that though respondents correctly reported that mosquitoes transmit malaria, yet most had no knowledge of the time of highest mosquito activity. These results indicate that knowledge about the mechanisms of malaria transmission among respondents was not complete, thereby exposing them to a greater risk of getting the disease.
Several studies found a higher incidence of malaria among individuals with inadequate knowledge about the mechanisms of malaria transmission and the preventive measures (Pineda and Agudelo, 2005; Tsuyuoka et al., 2001). Poor malaria knowledge can negatively impact malaria programmes (Ovadge and Nriagu,2016).
4.2 Recommendations
Based on the findings of this study, the following recommendations were made
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