ABSTRACT
This research work is aimed at modeling the causes of death among adult patients aged 15 years and above admitted at Federal Medical Centre (FMC), Owerri, Imo state. The data used for the study were extracted from record available at the Data Unit of Federal Medical Centre, Owerri, Imo State, and covered the period, 2013 – 2018. The data were analyzed using descriptive and multinomial logistic regression methods. 368 out of the 998 patients admitted died, implying a mortality rate of 369 per thousand of such patients. The average mortality rate was higher in the females (372 per 1,000 patients) group compared to male,(366 per 1,000 patients) group. The sex ratio shows excess female deaths over male deaths in the two youngest age groups 15-29 and 30-44, while the reverse was the case in the older age groups. Four major groups of diseases accounted for 70 percent of all deaths among the patients; they include Cardiovascular diseases, Infections diseases, Genitourinary diseases, and Digestive disorder. The most fatal of these groups of diseases is Genitourinary diseases with a fatality rate of 527 deaths per one thousand cases, which seems to be higher for males (578 deaths per 1,000 cases) than for females (407 deaths per 1,000 cases). The result of the multinomial logistic Regression revealed that Genitourinary group of diseases has the highest probability (0.7672) of causing death among adult patients admitted in Federal Medical Centre, Owerri. Other less fatal diseases include Malignant neoplasms with a probability of 0.0802, and Digestive disorder with probability of 0.0522.
TABLE
OF CONTENTS
Title
Page i
Declaration ii
Certification iii
Dedication iv
Acknowledgements v
Acronyms vii
Table
of Contents ix
List
of Tables x
List
of Figures xii
Abstract xiii
CHAPTER 1: INTRODUCTION 1
1.1 Background of the Study 1
1.2 Statement of Problem 5
1.3 Aim and Objective 5
1.3.1 General Objective 6
1.3.2 The Specific Objective 6
1.4 Significant of Study 6
1.5 Scope of Study 7
CHAPTER 2: LITERATURE REVIEW 8
2.1 Conceptual Framework 8
2.1.1 Leading cause of death 8
2.1.2 Causes of the sudden natural death in
various hospital 11
2.1.3 Maternal mortality in Nigeria hospital 11
2.2 Empirical Review 13
CHAPTER 3:
METHODOLOGY 18
3.1 Sources of Data 18
3.2 Variable Specification 18
3.2.1 The response variable and baseline category 18
3.2.2 Explanatory variables 19
3.2.3 Model building 19
3.3 Method of Analysis 20
3.3.1 Age- sex structure of the research data. 20
3.4 Multinomial Logistic Regression Model 21
3.4.1 Estimating response probability of cause of
death among patients aged 22
years
and above .
3.4.2 Parameter estimation 25
3.5 Assumptions of Multinomial Logistic
Regression 28
3.5.1 Goodness-of-fit test 28
3.5.2 Test for multicollinearity 30
3.5.3 Variance inflation factor (VIF): 30
3.5.4 Remedial measures for multicollinearity 31
3.5.5 Classification table of the polytomous
predicted variable 31
3.6 Estimating the Wald test statistic 33
3.7 Estimating the Pseudo R2 test
statistic 34
CHAPTER 4:
RESULTS AND DISCUSSION
4.1 The response variable categories 36
4.2
Determining the Leading Causes of
Death In FMC Owerri 39
4.3: Result
for Goodness-of-Fit-Test 46
4.4 Tests
for Multicollinearity 47
4.4.1
Examination of the Pearson correlation 47
4.4.2 Multicollinearity test using variance
inflation factor (VIF) 48
4.5 Multinomial
Results 49
4.6
Predicting The Probability of Dying
of Each Cause of Death 60
4.7 Fitting
A Statistical Model to Causes of Death Data Among And
Patient Aged 15 Years and Above 63
4.7.1 The estimated result of the model fitting
information 65
4.7.2
Likelihood Ratio Tests for selected model 66
4.8 Results for Pseudo R-Square 68
CHAPTER 5:
CONCLUSION AND RECOMMENDATIONS
5.1
Conclusion 69
5.2
Recommendations 70
References 71
Appendix 76
LIST
OF TABLES
3.2: Explanatory variables and their categories
19
4.1: Frequencies of the response variable
categories 36
4.2: Distribution of patients aged 15 years and
above admitted in
FMC, Owerri and deaths among them, 2013-2018. 38
4.3:
Levels and trend of mortality rates
among patients aged 15 years
and above admitted at FMC, Owerri
2013-2018. 39
4.4: Distribution
of death by cause, place of residence, for the period
2013-2018,
Federal Medical Centre, Owerri. 40
4.5: Cause of death structure for patients aged 15 years and above
admitted in FMC, Owerri 2013
-2018. 41
4.6: Distribution of
deaths by age and sex period 2013-2018
at
FMC, Owerri. 42
4.7: Fatality
rate of diseases for which patients Aged 15 years and
above were admitted in FMC, Owerri 2013-2018 44
4.8:
The estimation of the deviance and Pearson’s chi-square
goodness-of-fit test 46
4.9: Pearson
correlation for the explanatory variables 47
4.10: Estimated
collinearity statistics (tolerance and VIF) of explanatory
variables
for patient age 15 years and above, who were admitted at
FMC, Owerri
2013-2018. 48
4.11: Logit
coefficients from multinomial 50
4.12: Logit
coefficients, of multinomial logistic regression of dying
of
1of 9 causes Vs dying of other causes, on selected predictor
among patients aged
15 years and above admitted in FMC,
Owerri, 2013-2018. 57
4.13:
Estimated probability of dying for each
response variable
category among patients Age 15 years and
above admitted in Federal
Medical Centre Owerri, from 2013-2018. 63
4.14:
Estimated step summary of fitted model 65
4.15:
Estimated model fitting
information 66
4.16: Estimated
likelihood ratio tests for selected model of the patient
age
15years and admitted in the Federal Medical Centre Owerri,
2013-2018.
67.
4.17:
Pseudo R-Square 68
LIST OF FIGURES
4.1: Percentage distribution of total deaths by cause according to
sex
among patients age 15 years
and above, FMC, Owerri: 2013-2018. 42
4.2: Case fatality rate by sex among patients
aged 15 years and above, FMC,
Owerri: 2013-2018. 45
CHINONYEREM, C (2023). Modelling Of Cause Of Death In Federal Medical Centre, Owerri, Imo State: A Multinomial Logistic Regression Approach. Mouau.afribary.org: Retrieved Nov 17, 2024, from https://repository.mouau.edu.ng/work/view/modelling-of-cause-of-death-in-federal-medical-centre-owerri-imo-state-a-multinomial-logistic-regression-approach-7-2
CATHERINE, CHINONYEREM. "Modelling Of Cause Of Death In Federal Medical Centre, Owerri, Imo State: A Multinomial Logistic Regression Approach" Mouau.afribary.org. Mouau.afribary.org, 15 Aug. 2023, https://repository.mouau.edu.ng/work/view/modelling-of-cause-of-death-in-federal-medical-centre-owerri-imo-state-a-multinomial-logistic-regression-approach-7-2. Accessed 17 Nov. 2024.
CATHERINE, CHINONYEREM. "Modelling Of Cause Of Death In Federal Medical Centre, Owerri, Imo State: A Multinomial Logistic Regression Approach". Mouau.afribary.org, Mouau.afribary.org, 15 Aug. 2023. Web. 17 Nov. 2024. < https://repository.mouau.edu.ng/work/view/modelling-of-cause-of-death-in-federal-medical-centre-owerri-imo-state-a-multinomial-logistic-regression-approach-7-2 >.
CATHERINE, CHINONYEREM. "Modelling Of Cause Of Death In Federal Medical Centre, Owerri, Imo State: A Multinomial Logistic Regression Approach" Mouau.afribary.org (2023). Accessed 17 Nov. 2024. https://repository.mouau.edu.ng/work/view/modelling-of-cause-of-death-in-federal-medical-centre-owerri-imo-state-a-multinomial-logistic-regression-approach-7-2