Bachelorarbeit, 2017
28 Seiten, Note: 2.0
ABSTRACT
Acknowledgement
Abbreviations
1.0.0 INTRODUCTION
1.1.0 Background
1.2.0 Problem Statement
1.3.0 Justification
1.4.0 GENERAL OBJECTIVES
1.5.0 Specific Objective
1.6.0 Research Question
1.7.0 Hypotheses Statements
1.8.0 Scope of Study
1.9.0 Limitation
2.0.0 Literature review.
2.1.0 Malaria in Zambia
2.2.0 Malaria transmission and illness
2.3.0 Factors associated with malaria illness
2.4.0 Conceptual Framework
3.0.0 Methodology
3.1.0 Sample design
3.2 Variable definition; table 2
3.3.0 Model estimation Technique
3.4.0 Justification for choice of probit model
4.0.0 FINDINGS
4.1.0 Introduction
4.2.0 Data presentation
4.2.1 Proportional presentation of malaria distribution across selected factors
4.3.0 Summary of Diagnostic Test
4.4.0 Probit Regression Model With Robust Standard Errors
4.5.0 Marginal effects of probit analysis
4.5.1 The extent of socioeconomic factors influence on malaria
4.6.0 Hypothesis testing
5.0.0 DISCUSSION.
5.1.0 Socio economic factors influencing malaria among children under five
5.1.1 Statistically significant factors
5.1.2 Statistically insignificant factors
5.2.0 Conclusion
5.3.0 Recommendations
6.0.0 REFRENCE
There are wide gaps in empirical information on socioeconomic determinants of malaria among children under five. The main objective of this study was to investigate the socioeconomic factors such as mother’s education level, wealth of household, age of child, employment status and gender of child among other variables to establish how they influence malaria in children under five years of age.
Initially a proportional cross-sectional analysis was conducted using the 2013/14 Zambia demographic health survey report (ZDHS) data. The results of proportion of children who had malaria by their socioeconomic characteristics were highest among children aged 12-23 months with malaria of 27.1 percent prevalence levels while across child gender about 20.4 percent males and 21.6 percent females had malaria . In relation to mothers education highest proportions were observed among mothers with no education representing 24 percent with lowest 15percent for those with more than secondary school level of education. In terms of wealth the highest proportion was observed from second and lowest wealth quartile with 23.6 and 22.7 percent respectively while the lowest 17.6 percent was observed from those in the highest or richest level of wealth.
Then a probit regression analysis was done among selected socioeconomic factors and marginal effects where computed and presented in table 5, the probit regression show that a total of 9722 observations were analyzed and that if the average age of a child in months goes up by one unit, the probability of a child having malaria reduces by 0.078%. In terms of education mothers who have had no education increases the probability of a child having malaria by 3.22% holding other variable constant. This is a clear indication of the influences of socio economic factors on prevalence of malaria in children under five.
We would like to extend our deepest appreciation to our supervisor Dr. Jolly Kamwanga for his tireless direction and guidance that forged this study. We further acknowledge the Director of National Malaria Control (NMC) Dr. H. Busiku for his guidance and most importantly our Lecturer Dr. C.M Chiliba and Mr. B. Chizonde for their general guidance on how to conduct the study. We also recognize the invaluable contributions to this study by the entire team from the Department of Economics of the University of Zambia and our fellow students. Special gratitude to all respondents for finding time to interact with this study in their classes and offices hence enabling its completion, May God bless them abundantly.
Above all, we absolutely indebted to the Almighty God for the gift of life and health we undeservedly enjoyed throughout the period of our studies.
MOH: Ministry of health
NMCC: National malaria control Centre
MOJ: Ministry of Justice
WHO: World health organization
IRS: Indoor residual spraying
ITN: Insecticide treated nets
ZDHS: Zambia demographic health survey
MIS: Malaria indicator survey
HMIS: Health management and information system
RDT: Rapid diagnostic test
IMCI: Integrated management of childhood illness
ITGFHW: Integrated technical guidelines for frontline health workers
Malaria is an entrenched global health challenge particularly in the sub-Saharan African countries. An estimated 219 million cases of malaria and 660,000 malaria deaths occurred worldwide in 2010, (WHO: World malaria report, 2012). Approximately 80% of malaria episodes and 90% of the deaths were reported from the African continent according to the 2012 world malaria report. Endemic malaria results in tremendous economic losses annually and is a central element of the vicious cycle of poverty in many developing countries. International funding for malaria control rose to a peak of USD 1.84 billion in 2012,World malaria report (2012) . The world malaria report of 2011 shows an estimated 655,000 malaria deaths in the world, majority of which were under-five children from Africa . Thus, it remains a leading cause of death in children under five years (Sutcliffe CG, 2012). The World Health Organization and United Nations Children’s Education Fund (UNICEF, 2008) also indicate in the African Malaria Report that over 3,000 children die from malaria in Africa daily with a child dying every 30 seconds.
Malaria prevention and control in Zambia commenced in 1952. Since then great progress have been achieved, however, malaria still kills more children under the age of five than any other disease. It affects more than 4 million Zambians annually (UNICEF, 2008), causing 30% of outpatient visits resulting into about 8000 deaths each year. Under five children and pregnant women are most vulnerable with 35 to 50 percent child mortality and 20 percent maternal mortality, (Asenso-Okyere, 2003). Overall, the 2012 malaria indicator survey MIS shows that malaria parasite prevalence was 14.9% with more parasitaemia among children in rural areas (20.2%) compared to urban areas (13.7%). On average, parasitaemia prevalence peaked among children aged four years and was highest in Luapula province (32.1%) and in the lowest wealth quintile (27.4%), (MIS, 2012).
Malaria parasite rates typically increase with increasing age in the first five years of life (MIS, 2012). A number of studies have been conducted on malaria among under-five children and had attributed the disease to nonuse of insecticide treated nets (ITNs) by care givers among other studies have also conducted studies on malaria related beliefs and behaviors, treatment, prevention, and control in Southern and western provinces. However, little research has been done on socioeconomic determinants of malaria in Zambia. As such, this study sought to examine the socioeconomic factors that determine malaria among under-five children in Zambia using the latest cross sectional data from the 2013/14 Zambia demographic survey report.
Malaria is endemic both in urban and rural areas. It is documented as the most common cause of out-patient attendance and hospital admission in all age groups in Zambia (Kalubula M, 2016). Malaria is associated with the socio-economic status (SES) of countries. Given the extent of malaria in southern Africa, a full understanding of the factors associated with malaria incidence is important. This study will examine to what extent social and economic factors influence malaria episodes in households in children under five using the 2013/14 Zambia demographic survey data. Most studies have focused on the effectiveness of scientific methods of interventions such as indoor residual spraying, insecticide treated nets and Intermittent preservative treatment while other researchers have focused on the determinants of ITN use or factors influencing demand for IRS very few knowledge is linked to the social economic factors that determine malaria in children under five. This study intends to add education of the mother, wealth, age, sex, area and to establish the probability of children having malaria.
There is need to fully understand the determinants of malaria in order to reduce the burden that malaria puts on the health care system as well as the economic system. Being endemic in sub-Saharan Africa, there is need for adequate information about malaria for effective health policies to be put in place. Policies that the poor countries and communities can afford are vital as they will be easy to implement, compared to policies that require the intervention of donors.
Studies carried out previously show that the environment (temperature, humidity and rainfall), behaviour and demographic factor also an important driver of malaria (Bennett, 2013). Determining the spatial distribution of malaria is also important in ensuring that areas with high incidence are prioritized in the distribution of resources as well as in malaria prevention programs.
This study will give insight as to what are some of the socioeconomic factors that increase the chances of under five children to have malaria as such change the perception of policy makers from the business as usual syndrome in the fight against malaria.
The general objective of the study was to describe and analyze social and economic determinants of malaria incidence among children under five years in households in the Zambian population of 2014.
- To investigate the determinants of malaria episodes in children under five years in Zambia.
- To investigate the extent to which social and economic factors influence malaria episodes among children under five
- To investigate and compare proportional distribution of malaria episodes among socioeconomic factors.
- What are the socioeconomic factors associated with malaria?
- How is malaria distributed across socio economic status in children?
- What relationship exists between factors and malaria in children?
- To what extent do the determinants affect the occurrence of malaria in children under five?
- Socioeconomic factors have no influence on malaria episodes among children under five
- Wealth of household has no influence on malaria in children under five
- Mothers education has no influence on malaria in children under five
- The findings can be used as empirical evidence regarding the influence of socioeconomic factors on malaria occurrence among under five children
- The findings can be used as a basis for policy formulation in the fight against malaria
- The findings will add to the existing literature and general body of knowledge
This study focuses on an inquiry on the socioeconomic determinants of malaria in children under five years of age in Zambia. There are other factors that influence prevalence of malaria in children; these include demographic factors such as age, sex, ethnicity and environmental factors like temperature, humidity, climate etc. Our study seeks to use secondary data from the 2013/14 Zambia demographic health survey (ZDHS) to establish the social and economic factors that influence malaria in children such as mother’s education , child age, child gender , region of residence and economic factors such as wealth of household. We will cover the sample of under five children surveyed in the ZDHS which was done at national level.
This study relies on secondary data obtained from the ZDHS report. We could not conduct primary data collection because time and resource constraints. In order to access data a formal request was made on 30th July, 2017 to the Program Demographic Health Survey (PDHS) world data where access was granted on 2nd August, 2017 specific to the our research topic. Therefore, we had no control as to what extent the data we need was to be made available for instance the only variable which closely relates with malaria in children was a question of fever in the last two weeks , the data set did not have precise information on the malaria test results in children under five years, consequently, fever in the last two weeks was used as proxy to explain malaria in children since by definition all fever above 38.5 degree Celsius in children must be treated as malaria this was the case definition in Zambia and many sub-Saharan African countries before the introduction and availability of rapid diagnostic tests or in absence of malaria confirmation procedures.
Finally money was a major constraint as movement to meet with our supervisors required transport. The last minute new regulations by national malaria control center requiring a medical approval form delayed our data collection process.
Zambia is one of the unique countries that have experienced down and upward swing in the prevalence of malaria in the past 60 decades. Prior to 1970, malaria in urban areas in Zambia, especially towns along the line of rail (Copper, Lusaka to Livingstone), was kept to a minimum due to effective implementation of prevention and control programme (MoH, 2007). Vector control, especially IRS, was at its highest in the local, municipal and mine controlled towns and this contributed to reduction in malaria incidence. Konkola copper mines effectively carried out IRS, which resulted in reduction of incidence rate from 68/1000 to 20/1000 for Chingola and 158/1000 for Chililabombwe respectively, (Chanda E, 2011).
In addition, according to the Health Information Management System, HMIS (2010-2015) data, malaria incidence in Zambia increased from 230/1000 cases in 2010 to 335/1000 cases in 2015. These variations in incidence rates show a general increase in malaria cases at national level. However, notable increase and decreases has been observed in some provinces the largest relative decline in parasite prevalence by microscopy was observed in Luapula Province (51% - 32%), 2010 to 2012 HMIS data. North-Western Province had the largest relative increase in parasite prevalence (6% - 17%), while Northern Province remained relatively unchanged (24%). HMIS (2010-2012).
Malaria can be defined as a protozoan infection of the genus Plasmodium, transmitted through the bite of an infected female mosquito belonging to the genus Anopheles (MoH, 2000)Plasmodium falciparum is a protozoan parasite, one of the species Plasmodium that causes malaria in humans, transmitted by the female Anopheles mosquito. Under 5 child means a child whose aged 0–5 years.
Malaria is caused by four species of parasites of the genus Plasmodium that affect humans (P. falciparum, P. vivax, P. ovale, and P. malariae). Malaria is mainly found in tropical Introduction areas(Mendis and Carter, 1995). Malaria due to P. falciparum is the most dangerous form and it is mainly found in Africa; P. vivax is less dangerous but more widespread, and the other two species are found much less frequently (WHO: World malaria report, 2012). P. falciparum is responsible for almost all the malaria mortality cases in Sub-Saharan Africa and it is often stated that the continent bears over 90 percent of the global P. falciparum burden (Snow and Omumbo, 2006). Malaria infection is caused by mosquito bites and manifests itself in different ways. Severe malaria can result in severe anaemia, respiratory distress in relation to metabolic acidosis, or cerebral malaria. In adults, multi-organ involvement is also frequent. Immunity may develop in malaria endemic areas, resulting in mild infections to occur, particularly in adults. No clinical syndrome is entirely specific for malaria, (Ayeni, 2011).
Malaria transmission is controlled by environmental factors which affect the intensity of distribution, seasonality and transmission (Alegana, 2006). Malaria thrives in conditions that promote the growth of the vector of malaria which is the mosquito. Studies have shown that a dirty environment can result in increased malaria transmission (Sutcliffe CG, 2012). Other factors are temperature, humidity, rainfall, forest clearance, agriculture and non-availability of insecticide treated mosquito nets (Eisele TP, 2012), rainfall leaves pools of stagnant water that are good breeding for mosquitoes, clearing of forests results in light being able to penetrate into the forest and therefore providing ideal breeding for mosquitoes and in Zambia, firewood is the main source of fuel (Chanda E, 2011). This leads to the destruction of forests and thereby promoting mosquito breeding. Agricultural methods that involve irrigation as well as the building of dams also promote the breeding of mosquitoes therefore these results in increased malaria transmission (Abeku, 2003). All these factors promote malaria illness as these result in increased chances of a person being bitten by mosquitoes.
Another study suggested that, socio-economic status (SES), immunization, knowledge, human behaviour and general under nutrition also play a role in increasing malaria illness and mortality. Nutrition is linked to economic status if one is economically sound then they are able to provide adequately for themselves and therefore resulting in a well-nourished body. A well-nourished body is immune competent to fight off malaria infection by mounting an adequate response to infection as compared to an immune vulnerable undernourished body (Eisele TP, 2012). Malaria severely affects nutrition by limiting food intake through lack of appetite and vomiting; Nutritional status also affects responses to anti-malarial medication (Bates, 2004) resulting in drug resistance. Approximately 67% of anaemia cases in children in malaria-endemic countries are thought to be the result of malaria (Bates , 2004). Health status is also linked to economic status and malaria is also affected by the economic status of an individual as well as country (Asenso-Okyere, 2003). A poor economic status results in inadequate health care facilities in Zambia and therefore increasing vulnerability of the population to malaria. A review of literature on SES and malaria showed that malaria and low SES were interlinked.
Age and gender are the other important factors that are also associated with malaria illness with the majority of malaria illness and deaths occurring in children under the age of five. Studies carried out in Gabon and Tanzania showed that children over the age of five were most at risk in the transmission of malaria (D. Houeto, 2007; Eisele TP, 2012). In the Tanzania study, males were more at risk of malaria illness compared to females, (Kim D, 2012). A study carried out in rural Nigeria did not show any difference between the sexes but showed that prevalence of malaria was highest in 11 to 20 years age group (Ayeni, 2011). Another study carried out in Kenya showed that parasitaemia decreased with age with children in the 1-4 year age group having the highest prevalence at 83% and decreasing to 60% in the 10-14 year age group (Brooker, 2008). In Zambia it has been shown that malaria increase with age and that children under five carry the heaviest burden of malaria, the parasite rates typically increase with increasing age in the first five years of life this is because their immune system is not yet fully developed, (Chizema-Kawesha E, 2010).
Studies also suggest that location also plays an important role in malaria transmission. In one study carried out in Ethiopia, clustering or hot spots of malaria were revealed (Abeku, 2003). Another study carried out in Ghana showed that distance from a water body plays an important role in malaria prevalence (Asenso-Okyere, 2003).
The conceptual framework table 1 , shows the relationship of socioeconomic factors on malaria. Abbildung in dieser Leseprobe nicht enthalten
This paper used secondary data drawn from the 2013/14 Zambia Demographic and Health Survey (ZDHS) children’s data file. The ZDHS is a national sample survey designed to provide up to date information on background characteristics of the respondents, fertility levels, sexual activity, fertility preferences, awareness and use of family planning methods, breastfeeding practices, nutritional status of mothers and young children, early childhood mortality and maternal mortality, maternal and child health, awareness and behaviors regarding HIV/AIDS and other sexually transmitted infections (STIs), and prevalence and incidence of HIV/AIDS and other STIs. The target groups were men age 15-59 years and women age 15-49 years in randomly selected households across Zambia, (Phiri, 2013). Information about children age 0-5 years was also collected, including data on weight and height. The survey collected blood samples for HIV testing in order to determine national and provincial prevalence and incidence rates. The Question for malaria incidence and prevalence data was collected on children who reported to have had fever in the past 2 weeks before the survey diagnostics test where not conducted.
The ZDHS was carried out by the Central Statistics office (CSO), the ministry of health (MoH), the University of Zambia Teaching Hospital (UTH) Virology Laboratory, the Tropical Diseases Research Centre (TDRC), and the Department of Population Studies at the University of Zambia (UNZA), (CSO, MOH, ICF international, 2015).
The sample for the 2013-14 ZDHS was designed to provide estimates at the national and provincial levels, as well as for rural and urban areas within the provinces. This is the first time the ZDHS has been designed to provide estimates at such disaggregated levels for many of the survey indicators. The updated list of enumeration areas (EAs) for the 2010 Population and Housing Census provided the sampling frame for the survey. The frame comprises 25,631 EAs and 2,815,897 households. A representative sample of 18,052 households was drawn for the 2013-14 ZDHS. The survey used a two-stage stratified cluster sample design, with EAs (or clusters) selected during the first stage and households selected during the second stage. In the first stage, 722 EAs (305 in urban areas and 417 in rural areas) were selected with probability proportional to size. Zambia is now administratively divided into 10 provinces (Central, Copperbelt, Eastern, Luapula, Lusaka, Muchinga, Northern, North Western, Southern, and Western). Stratification was achieved by separating each province into urban and rural areas. Therefore, the 10 provinces were stratified into 20 sampling strata. In the second stage, a complete list of households served as the sampling frame in the selection of households for enumeration. An average of 25 households was selected in each EA. It was during the second stage of selection that a representative sample of 18,052 households was selected. Data collection took place over an eight-month period, from August 2013 to April 2014. (Central statistics office, 2015).
Out of a total of 18,052 households selected from 722 clusters 16,258 were occupied at the time of the fieldwork and 15,920 of the occupied households were successfully interviewed, yielding a household response rate of 98 percent. In the interviewed households, a total of 17,064 women age 15-49 were identified as eligible for individual interviews, and 96 percent of these women were successfully interviewed. A total of 16,209 men age 15-59 were identified as eligible for interviews, and 91 percent were successfully interviewed. Generally, Individual response rates were slightly lower in urban areas than in rural areas.
The survey obtained information on women’s exposure to malaria during their most recent pregnancy in the five years preceding the survey and the treatment for malaria. They were also asked if any of their children born in the five years preceding the survey had malaria, or fever in the last two weeks prior to survey and whether these children were treated for malaria, and about the type of treatment they received.
In this study fever in the last two weeks was used as a surrogate for malaria firstly because the data set from ZDHS had no information on the test results for malaria in children under five. Secondly malaria is the leading cause of fever in Sub-Saharan Africa, where 30 to 60% of fevers especially in infants and young children are attributed to malaria (Mabunda S, 2009). In highly endemic areas, fever alone is used as a proxy for symptomatic malaria it was applied in a study in Mozambique where a report of fever in last 30 days was associated with confirmed Rapid diagnostic testing RDT results. In Zambia Fever is a major manifestation of malaria and other acute infections in children. Malaria contributes to high levels of morbidity and mortality. While fever can occur year-round, malaria is more prevalent following the end of the rainy season. In the past, malaria treatment guidelines as well as the ITG guidelines were based on the assumption that fever on its own was an indication of malaria, in line with the then-prevailing epidemiological pattern of malaria in the country (CSO, MOH, ICF international, 2015). As such Medical personnel used this method to diagnose patients especially if they have no means to conduct confirmatory tests such cases are reported as clinical malaria and treatment is given (Chirwa, 2002, p. 69) . However, it must be acknowledged that while report of fever approximates symptomatic malaria, it underestimates malaria prevalence in children especially in the rainy season. The statistical package STATA (version 12) was used to process the data.
[...]
Der GRIN Verlag hat sich seit 1998 auf die Veröffentlichung akademischer eBooks und Bücher spezialisiert. Der GRIN Verlag steht damit als erstes Unternehmen für User Generated Quality Content. Die Verlagsseiten GRIN.com, Hausarbeiten.de und Diplomarbeiten24 bieten für Hochschullehrer, Absolventen und Studenten die ideale Plattform, wissenschaftliche Texte wie Hausarbeiten, Referate, Bachelorarbeiten, Masterarbeiten, Diplomarbeiten, Dissertationen und wissenschaftliche Aufsätze einem breiten Publikum zu präsentieren.
Kostenfreie Veröffentlichung: Hausarbeit, Bachelorarbeit, Diplomarbeit, Dissertation, Masterarbeit, Interpretation oder Referat jetzt veröffentlichen!
Kommentare