ABSTRACT
This study investigated the impact of socio-demographic factors on HIV infected pregnant women in Imo State. Data used were collected from the Federal Medical Centre, Owerr. The data comprised HIV status and socio-demographic factors of pregnant women attending antenatal care in Federal Medical Centre, Owerri. The Socio-Demographic factors included the independent variables which include Age, Residence, Senatorial Zone, Marital Status, Contraceptive Use, Education, Religion and Employment status of the pregnant women. Descriptive statistics tools and Ordinal Logistic Regression Model (Proportional Odds Model) were used for data analysis. The results of the analyses showed that “Age” which is one of the variables used in the analysis was categorized and result showed that pregnant women between the ages of 15-19 years are prone to contacting HIV/AIDS as compared to higher age categories. “Marital status” was also categorized and tested, result showed that Married pregnant women were more vulnerable to contacting HIV/AIDS as compared with the Single and Divorced pregnant women. Another result was shown in the “Use of Contraceptives” which showed that some of the pregnant women Never used any form of Contraceptives when compared with the result of those pregnant women that uses contraceptives which made them liable to contacting HIV/AIDS. Further result showed that “Residence” as another variable was tested and result showed that the Rural dwellers are more susceptible to contacting the deadly disease called HIV/AIDS. Lastlty, “Senatorial” was shown to be statistically significant as the various categories under it were all tested and result showed that the pregnant women residing in Orlu Senatorial zone were inclined to contacting HIV/AIDS as compared to the result of Owerri and Okigwe Senatorial zones.
TABLE OF CONTENT
Title page i
Declaration ii
Dedication iii
Certification iv
Acknowledgement v
Table of Content vi
List of Tables vii
List of Figures viii
Abstract ix
CHAPTER
1: INTRODUCTION
1.1
Background of the
study 1
1.2 Statement of the problem 2
1.3 Aim and objectives of the study 3
1.4 Significance of the study 3
1.5 Scope of the study 3
CHAPTER
2: LITERATURE REVIEW 4
CHAPTER
3: MATERIALS AND METHODS 16
3.1 Data collection 16
3.2 Categorization of variables of the study 16
3.3 Method of
analysis 18
3.3.1 Descriptive
statistical analysis 18
3.3.2 General ordinal
logistic regression 18
3.3.2.1 Assumptions of ordinal regression model 19
3.3.2.2 Specification of ordinal logistic regression model
for HIV status
of pregnant women 19
3.3.2.3 Maximum
likelihood estimation of the parameter of the ordinal
regression
model 21
3.4 Test of significance on parameters of
ordinal logistic regression 24
3.4.1 Chi-square
test for independence 25
3.4.2 Pearson Chi-square goodness of fit and the
deviance 26
3.5 Model adequacy checking 26
3.5.1 Justification of assumption of ordinal
dependent variable. 27
3.5.2 Justification of assumption of continuous,
ordinal or nominal
independent variable. 27
3.5.3 Justification of the assumption of
independence 27
3.5.4 Justification of the assumption of no
multicollinearity 28
3.5.5 Estimation of
pseudo R2 28
CHAPTER
4: RESULTS AND DISCUSSION
4.1 Descriptive
statistical analysis 30
4.1.1 Description of HIV status of pregnant women
in Imo state by their socio-demographic characteristics 30
4.1.1 Charts representation of HIV status of
pregnant women in Imo State by their socio-demographic characteristics
4.2 Results of model fitting information 41
4.3 Results of
ordinal logistic regression analysis 42
4.3.1 Test
of association of HIV status and socio-demographic variables of
pregnant
women in Imo State using Chi-square test of independence 45
4.3.2 Result of Pearson and deviance goodness of
fit test 46
4.3.3 Result for
pseudo R-square for the fitted ordinal logistic regression model 46
4.3.4 Result for the test of parallel line assumption for the fitted
ordinal logistic
regression model 47
4.4 Discussion of
results 48
CHAPTER 5: CONCLUSION AND RECOMMENDATIONS
5.1 Conclusion 50
5.2
Recommendation 51
References 52
Appendices 55
LIST OF TABLES
Table Title
Page
3.1: Categories of the dependent variable with
the corresponding codes 16
3.2: List of independent variables with respective
names, categories and codes 16
4.1: Frequency (Percentage distribution) of HIV
status of pregnant women in
Imo State by their socio-demographic
characteristics 30
4.2:
Ordinal logistic regression model
fitting information 42
4.3: Maximum
likelihood estimates of parameters of the ordinal logistic
regression model 43
4.4:
Chi-Square Test of independence of
HIV status on socio-demographic
variables of
pregnant women in Imo State 45
4.5:
Pearson and Deviance Goodness-of-fit
test for the fitted ordinal logistic
regression model 46
4.6:
Pseudo R-Square for the fitted ordinal logistic regression model for HIVstatus 47
4.7: Test
of Parallel Line assumption for the fitted ordinal logistic regression 47
LIST OF FIGURES
Figures Title Page
4.1:
HIV status of pregnant
women by age 34
4.2:
HIV status of pregnant
women by residence 35
4.3: HIV status of pregnant women by
Senatorial zone 36
4.4: HIV status of pregnant women by
marital status 37
4.5: HIV status of pregnant women by
contraceptive use 38
4.6: HIV status of pregnant women by
education 39
4.7: HIV status of pregnant women by
religion 40
4.8: HIV status of pregnant women by
employment 41
CHAPTER 1
INTRODUCTION
1.1 BACKGROUND OF THE STUDY
The HIV virus otherwise called the Human Immuno-deficiency
Virus (HIV) has been a cankerworm that is bedeviling human-kind. It is a
retrovirus known to cause human Immune-deficiency infection, with sequel
advancement to Acquired Immuno-deficiency Syndrome (AIDS) if not properly
managed. AIDS is a distinct syndrome associated with severe and life-threatening
clinical conditions. It remains one of the world's most significant public health
challenges. Human Immuno-deficiency Virus (HIV)
attacks the body’s immune system, gradually destroying its ability to fight
infections and certain cancers. HIV can develop into Acquired Immuno-Deficiency
syndrome (AIDs), if left untreated. HIV is of concern because it has serious
impact on virtually every facet of human endeavor to include socio-economic
activities with special emphasis on how it affects the fertility of the
infected individual (Salu et al.,
2018).
HIV testing is thebest way for
treatment care and support services. Checking of HIV status will definitely
empower individuals and couples in taking measures to prevent HIV acquisition
or onward transmission. For those already infected, a positive result is
necessary to access treatment and, in the case of pregnant mothers it helps
them for the Prevention of Mother to Child Transmission (PMTCT) services (Ali,
2015). In the case of communities, awareness of HIV status through testing
could reduce HIV related stigma and discrimination. Population related surveys
provide national level prevalence estimates and the opportunity for behavioral,
social and other biological information (WHO, 2003).
According to Stover (2004), fertility
is one of the components of population change in any country therefore; any
disease affecting it will have serious impact on demographic transition. He
further states that Nigeria has experienced high fertility levels over the last
two decades despite numerous policies oriented programs by the government and
international agencies. He further advised that negative influence and poor
planning on fertility has a psychological sense in reducing fertility.
According to Alvarez (2011) he emphasized that Logistic
Regression Model is a bid to determine the influence of Socio-Demographic
factors on HIV in pregnant women. His study reveals that categorical responses
on pregnancy outcome in terms of some predictors will determine the goodness of
fit, as well as the validity of assumption. In many epidemiological studies on
socio-demographic influence on HIV infected pregnant women, the model (Ordinal
Logistic Regression) can be utilized as a tool to model data. Ordinal Logistic
Regression is a Statistical Model used to model the relationship between
variables with Ordinal-Scale response variables with continuous/categorical
explanatory variables.
1.2 STATEMENT OF THE PROBLEM
In Statistical
Analysis, one may seek to analyze the factors that led to the emergence of
certain diseases so as to make inferences on how to take appropriate control
measures and HIV is no exception. Work done by Chen (2010) has attempted to
determine the influence of Socio-demographic factors on HIV infection among
pregnant women and their fertility rate. However, this study approached the
problem from the Binary Logistic Regression perspective and thus considered
only Binary Dependent Variables. Several other works have attempted to use
other methods such as multiple regression and non-parametric models to analyze
the various risk factors on HIV infection. Thus, it becomes pertinent to carry
out this study so as to bridge this gap of making inference for more than two
levels of dependent variables.
1.3 AIM AND OBJECTIVES OF THE STUDY
The aim of this study is to determine
the impact of socio-demographic factors that affects HIV status of pregnant
women in Imo state. Hence, the specific objectives include:
(i)
To fit an appropriate
Ordinal Logistic Regression Model to the Socio-demographic risk factors of HIV/AIDS infection among pregnant women,
(ii)
To determine whether or
not the fitted model is adequate for prediction
(iii)
To test for the
significance of socio-demographic factors in HIV infection of pregnant women in
Imo State.
1.4
SIGNIFICANCE OF THE STUDY
Of utmost
importance to health planners are the factors leading to the growth and
development of diseases. The outcome of this study will guide health planners
in handling the problem of HIV amongst pregnant women, in that, it will equip
them with the necessary factors that influence HIV infected pregnant women.
Furthermore, researchers who may wish to carry out a similar study will find
this work useful.
1.5 SCOPE OF THE STUDY AND LIMITATION
This
study focuses on the use of Ordinal Logistic Regression Model of the Influence
of Socio-demographic risk factors on HIV infection among pregnant women. The
study was conducted using data from the Federal Medical Centre, Owerri. The
data used for this study covers only the years 2015 and 2016 respectively. Moreover, the researcher did not find it easy
in getting necessary information from Federal Medical Centre Owerri, as several
protocols had to be undertaken before the document will be released. The time
available for this research work was limited, hence it posed3 a little
challenge to this work. Financial constraint was another challenge that was
faced in the cause of this study. 
Buyers has the right to create
dispute within seven (7) days of purchase for 100% refund request when
you experience issue with the file received.
Dispute can only be created when
you receive a corrupt file, a wrong file or irregularities in the table of
contents and content of the file you received.
ProjectShelve.com shall either
provide the appropriate file within 48hrs or
send refund excluding your bank transaction charges. Term and
Conditions are applied.
Buyers are expected to confirm
that the material you are paying for is available on our website
ProjectShelve.com and you have selected the right material, you have also gone
through the preliminary pages and it interests you before payment. DO NOT MAKE
BANK PAYMENT IF YOUR TOPIC IS NOT ON THE WEBSITE.
In case of payment for a
material not available on ProjectShelve.com, the management of
ProjectShelve.com has the right to keep your money until you send a topic that
is available on our website within 48 hours.
You cannot change topic after
receiving material of the topic you ordered and paid for.
Login To Comment