1.1 Introduction
Deaths that occur in a child's first year of life are known as infant mortality. Given that the variable in child-level analysis is inherently dichotomous (often 0 for survival and 1 for dying within the specified age range), logistic regression or probity analysis seem acceptable. This method's drawback is that it requires removing from the sample any youngsters who have not been fully exposed to the risk of mortality. A risks model, which is employed in more recent research, allows the entire sample to be used because it accounts for censoring of children who have not been fully exposed.
The mother's mortality rate, which can be considered as a continuous variable and estimated using OLS (Ordinary Least Squares), can be determined if the mother is the unit of analysis rather than the child. However, as it enables the inclusion of child-specific characteristics, child-specific analysis should be chosen.
This chapter will address the background information that motivated this study, the challenges that prompted it, its aim, and its objectives as a preface to subsequent sections of the study. Additional factors include the study's significance, scope, limitations, research questions and hypotheses, and the definition of technical terms.
1.2 Background of Study
The absence of all signs of life at any point after birth is what the World Health Organization (W.H.O.) defines as mortality, or death. Thus, mortality can be defined as the annual chance of dying, expressed as a death rate. Nonetheless, childhood mortality is the type of death that frequently causes concern among the deceased. This is because there is a health risk associated with this population group. As to the World Health Organization, the rate of child mortality serves as a crucial indicator of a nation's socio-economic progress and the well-being of its women population.
Reducing child mortality by two-thirds between 1990 and 2030 is one of the key goals of the Millennium Development Goals (MDG) (UNICEF, 2006), and a key measure of achieving this goal is the infant mortality rate. Demographers use several measures of childhood mortality in health surveys: neonatal mortality, which is the likelihood of dying in the first month of life; infant mortality, which is the likelihood of dying before turning one year old; and post natal mortality, which is the sum of the mortality rates of newborns and neonates. However, the study's main focus is infant mortality.
Numerous infants perish in the universe for various reasons. The precise causes of the numerous newborn fatalities that occur every hour might not be known if these causes of death are not observed, acknowledged, and given the necessary attention. Using statistical approaches to extract information related to the population or sample of interest is the most effective way to accomplish this task and provide recommendations. Today, data collection and analysis are widely valued in every facet of our society. Nowadays, statistics is a key component of practically every discipline, including astronomy, biology, botany, psychology, physics, chemistry, economics, and business. Thus, there are many applications for statistics.
Data analysis using suitable statistical tools or procedures yields relevant predictions, inferences, decisions, and meaningful conclusions. Thus, a lot of work has gone into using statistical tools to forecast the key variables causing infant death worldwide. Statistical approaches such as regression and correlation analysis have become widely used in mortality research based on variables or factors that are known to predict mortality. Socioeconomic factors, including vaccinations, exclusive breastfeeding, and the adoption and use of insecticide-treated nets, have been found to be major predictors of child mortality in studies utilizing statistical approaches, particularly in developing nations. The risk of morbidity and mortality, mother education, access to safe drinking water, sanitation facilities, and maternal and child health care services are some of these proximate factors (Uddin, Hossain & Ullah, 2008).
The infant mortality rate in Nigeria is appallingly high compared to the average rate in other nations, even with these recognized contributing factors. According to statistics, Nigeria accounts for up to 20% of all child fatalities in sub-Saharan Africa. According to the National Bureau of Statistics (NBS), 2011 report and the World Bank (2013), child mortality in Nigeria rose from 138 per 1,000 live births in 2007 to 158 per 1,000 live births in 2011. However, there are particular times of greater susceptibility within the infant group. For example, deaths that occur during the first year of life (infant) account for 60% of child mortality; the most susceptible time is the first 24 hours of life, which is followed by the first week and the first month (Kyei, 2011). Therefore, by using statistical approaches, data on baby mortality can be analyzed to obtain valuable insights that can aid in identifying the true factors that contribute to infant mortality.
1.3 Statement of Problems
Investigation revealed that nearly 10 million children worldwide lose their lives each year, according to a UNICEF report from 2006. in the first four weeks of life, 4 million newborns (or 40% of mortality among children under five) pass away. The estimated infant mortality rate in Nigeria is 191 per 1000 live births. More than any other country in Africa, Nigeria loses over a million children to preventable diseases, according to Ogunjimi, Ibe, and Ikorok (2012).
The northern Nigerian states of Borno, Yobe, and Zamfara account for the highest number of infant deaths in the country, with 257–270 deaths per 1000 live births. As is evident, the majority of research has a broad focus on child mortality and is primarily conducted throughout Nigeria.
In light of this, this study makes an effort to examine a single instance of Delta State and highlight the different factors that the state's infant mortality has, as shown by statistics from Delta Central Hospital in Asaba.
1.4 Aim and Objectives of Study
The aim of the study is to examine the predictors of infant mortality in Delta State, Nigeria. In achieving this aim, the following specific objectives were laid out as follows:
- To determine if there is increased level of infant mortality in the area under study;
- To determine the predictors of infant mortality in the area under study;
- To examine the infant mortality rate trend in the area under study; and
- To ascertain if there is any difference in the age specific death rate in infant mortality in the area under study.
1.5 Research Questions
The study came up with research questions so as to be able to ascertain the above stated objectives. The specific research questions for the study are stated below as follows:
- Is increased level of infant mortality in the area under study?
- Is there any difference in the age specific death rate in infant mortality in the area under study?
- What is the infant mortality rate trend in the area under study?
- What are the predictors of infant mortality in the area under study?
1.6 Research Hypothesis
In order to pursue the objective of this study, the following generalized statements have been designed to guide and aids in obtaining the result for the experiment to be conducted. For this work, the null hypothesis will be represented with H0 while the alternative hypothesis will be represented with hypothesis H1.
Hypothesis One
- H0: There is no significant difference in the age specific death rate in infant mortality in the area under study
- H1: There is a significant difference in the age specific death rate in infant mortality in the area under study
1.7 Significance of Study
Since infant mortality is one of the factors that contribute to population fluctuation, researchers have long been interested in studying it. One key measure of the general health of a nation is infant mortality. This is because these statistics help with population forecasts for a country or a demographic group, as well as indicating the efficacy of population and health initiatives and policies in any given country. Statistics on infant mortality can be used to pinpoint particular communities that are more vulnerable to health issues.
The findings of the study could have a big impact on government initiatives to solve the problem and discourage young girls from having abortions. The results of this study would be strengthened by more investigation into the high rate of mortality and associated topics in Nigeria.
1.8 Scope of Study
The scope of the research is focused on the Predictors of Infant Mortality in Delta State, Nigeria The study is hinged on educating young girls in Benin metropolis about the dangers and complications of abortion as well as to reduce mortality rate among young girls on related issues.
1.9 Limitations of the Study
During the course of this study, there were some problems encountered which stood as limitations to the research work. Some of the limitations include:
- Time Constraint: The time frame given to accomplish this project was very short due to school academic calendar and it was carried out under pressure which made the researcher not to implement some necessary features.
- Research Material: availability of research material is a major setback to the scope of the study.
- Financial Constraint: Insufficient fund tends to impede the efficiency of the researcher in sourcing for the relevant materials, literature or information and in the process of data collection (internet, questionnaire and interview).
- Initial Cooperation Delay from Respondents: A particular limitation of this work came as a result of the respondent refusal to offer their cooperation at the initial time they were contacted. This contributed in making the success of this research study difficult.
1.10 Definition of terms
Mortality:
It refers to Death especially on a large scale
Statistics:
A branch of mathematics that is used to arrange, classify, analyze and present data for the purpose of decision making.
Dependent Variable:
It refers to the variable that is being predicted or estimated.
Independent Variable:
It refers to the variable that provides the basis for estimation. It is the predictor variable.
Residual:
This is the difference between the actual and the predicted value of the dependent variable.
Homoscedasticity:
It is a situation where the residuals are same for all estimated values of the dependent variable.
Autocorrelation:
This occurs if successive observations of the dependent variable correlated.
Regression Equation:
An equation that defines the relationship between dependent variable and one or more independent variable.
Least Square Principle:
An equation determined by minimizing the sum of the squares of the vertical distances between the actual y values and the predicted values of y.
Standard Error:
A measure of the scatter, or dispersion of the observed values around the line of regression.
Coefficient of Determination:
It refers to the proportion of the total variation in the dependent variable y that is explained or accounted for by the variation in the independent variable x.
Infant:
They are children less than one year old.
Immunization:
This involves giving the infants drugs to prevent them from diseases.
Mortality:
This refers to the number of deaths within a particular society and within a particular period of time.
