PROPORTIONAL ODDS MODELLING OF HIV INFECTION AMONG PREGNANT WOMEN (A CASE STUDY OF FEDERAL MEDICAL CENTRE, OWERRI)

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.  

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