STATISTICAL ANALYSIS ON FERTILITY AND MORTALITY CASES (A CASE STUDY OF RASHEED SHEKONI TEACHING HOSPITAL FROM 2014–2024)

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Product Code: 00010289

No of Pages: 58

No of Chapters: 5

File Format: Microsoft Word

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ABSTRACT

This study analyzes fertility and mortality trends at Rasheed Shekoni Teaching Hospital, Dutse, using data collected from 2014 to 2024. The findings show consistent increases in both fertility and mortality cases over the 11-year period. Descriptive statistics reveal average annual counts of 572 fertility cases and 54 mortality cases, with both variables showing steady upward trajectories. Linear regression analysis indicates strong positive relationships between time and both fertility (R² = 0.97) and mortality (R² = 0.95), confirming significant annual growth. Quadratic regression models provide an even better fit (R² = 0.982 for fertility; R² = 0.967 for mortality), revealing accelerating fertility growth and a gradually increasing mortality trend. Forecasts based on the preferred quadratic models project fertility cases to rise to approximately 740 in 2025 and 773 in 2026, while mortality cases are expected to reach 70 and 73, respectively. These trends highlight the need for strengthened resource allocation, staffing expansion, and infrastructural development within the hospital. While the models demonstrate high predictive accuracy, forecast uncertainty remains due to potential external influences such as policy changes, demographic shifts, and Statistics events. The study concludes that proactive planning and continuous data monitoring are essential for managing the increasing demand for healthcare services at the institution.

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DECLARATION.. ii

CERTIFICATION.. iii

APPROVAL PAGE.. iv

DEDICATION.. v

ACKNOWLEDGEMENTS. vi

TABLE OF CONTENTS. vii

ABSTRACT. ix

CHAPTER ONE.. 1

1.0 INTRODUCTION.. 1

1.2 Statement of the Problem.. 2

1.3 Aim and Objectives of the Study. 2

1.5 Scope and Limitations of the Study. 3

CHAPTER TWO.. 4

LITERATURE REVIEW... 4

2.1 Introduction. 4

2.2 Conceptual Framework. 4

2.2.1 Fertility: Definition and Measurement 4

2.3 Theoretical Perspectives. 6

2.3.1 Demographic Transition Theory. 6

2.3.2 Proximate Determinants Framework. 7

2.4 Empirical Review.. 7

2.4.1 Global Trends in Fertility and Mortality. 7

2.4.2 Fertility and Mortality in Nigeria. 8

2.4.3 Hospital-Based Fertility and Mortality Studies. 10

2.4.5 Factors Influencing Mortality. 13

2.5 Statistical Methods in Fertility and Mortality Analysis. 15

2.5.1 Descriptive Statistical Analysis. 15

2.5.2 Time Series Analysis. Error! Bookmark not defined.

2.5.3 Rate Calculation and Standardization. 16

2.6 Data Quality and Completeness in Hospital Records. 17

CHAPTER THREE.. 21

3.0 METHODOLOGY.. 21

3.1 Research Design. 21

3.2 Method of Data Collection: 21

3.6.1 Descriptive Statistical Analysis. Error! Bookmark not defined.

3.6.2.2 Quadratic Regression Model 22

3.6.2.3 Model Comparison and Selection. 23

3.6.3 Model Assumptions and Diagnostics. Error! Bookmark not defined.

3.6.4 Presentation of Results. 23

CHAPTER FOUR.. 25

DATA PRESENTATION AND ANALYSIS. 25

4.1 Data Summary. 25

4.2 Data Analysis. 25

4.3 Linear Model Analysis. 26

4.4 Quadratic Model Analysis. 27

CHAPTER FIVE.. 31

5.0 SUMMARY, CONCLUSION AND RECOMMENDATIONS. 31

5.1 Summary. 31

5.2 Conclusion. 32

5.3 Recommendations. 32

Reference. 33

 


 

 


CHAPTER ONE

1.0 INTRODUCTION

Fertility and mortality are two core pillars of population change. Fertility describes patterns of childbearing, while mortality captures the frequency and causes of death in a population. In Nigeria, fertility remains high compared to global levels, even though a slow decline is underway, and mortality especially among mothers and young children remains a major Statistics concern (NPC & ICF, 2019; Olowolafe et al., 2023; UN IGME, 2023). Understanding recent trends inside health facilities helps managers and policymakers see what is changing on the ground and what to improve (WHO, 2025).

National survey data show Nigeria’s total fertility rate (TFR) was above five children per woman in 2018, with large regional differences rates are typically higher in the North-West than the national average (NPC & ICF, 2019; Kunnuji et al., 2022). Studies also link fertility patterns to age at first birth, women’s education, and access to family planning (Agbana et al., 2022; Olowolafe et al., 2023). That means hospital delivery records, antenatal (ANC) registers, and family planning logs can reveal useful “facility-based fertility patterns,” such as the age distribution of mothers, parity, and short birth intervals that increase risk (NPC & ICF, 2019; Salawu et al., 2021).

Mortality trends are equally important. According to the UN Inter-agency Group for Child Mortality Estimation, under-five deaths remain high in sub-Saharan Africa, with Nigeria contributing a large share of global deaths (UN IGME, 2023; UNICEF, 2025). Neonatal mortality in Nigeria has been stubbornly high, and recent analyses using DHS/MICS data show slow progress and persistent regional gaps (Kunnuji et al., 2022; Wammanda et al., 2022). Within facilities, tracking neonatal deaths, stillbirths, and post-neonatal deaths against total live births helps identify preventable factors like infections, birth asphyxia, prematurity, and delays in seeking or receiving care (UNICEF, 2025; Wammanda et al., 2022).


1.2 Statement of the Problem

Despite sustained national and international interventions, Nigeria continues to record high fertility rates and a substantial number of preventable maternal and newborn deaths. Hospital records, which could provide critical local evidence for timely quality improvement, remain underutilized. At Rasheed Shekoni Teaching Hospital, where numerous childbirths and patient referrals are documented, there appears to be no known existing research that explores the trends and underlying causes of fertility-related challenges (such as high parity and short birth intervals) and mortality outcomes (including maternal, neonatal, and under-five deaths) between 2014 and 2024.


1.3 Aim and Objectives of the Study

The aim of this research is to analyze the data on fertility and mortality cases at Rasheed Shekoni Teaching Hospital from 2014 to 2024 through the following objectives:

1.      To fit a linear model for maternal data and forecast for 2025-2026

2.      To fit a linear model for fertility data and forecast for 2025-2026

3.      To test whether there is significant difference between fertility and mortality       

1.4 Significance of the Study

This study is important because it helps doctors, hospital managers, health planners, and researchers better understand patterns of births and deaths at Rasheed Shekoni Teaching Hospital over the years. 

It will help the hospital plan ahead for the future (2025–2026) using data-based forecasts.  Health officials and government bodies can use the results to improve health programs for mothers and children. Researchers and students in health, statistics, and Statistics will also benefit from the models used in this study for future studies. The study shows if there is a big difference between fertility and mortality, which can help in focusing on the more pressing issues.


1.5 Scope and Limitations of the Study

Scope: The research focuses only on data from Rasheed Shekoni Teaching Hospital between 2014 and 2024. It covers maternal, fertility, and mortality cases.  The study uses statistical models (linear and quadratic) to analyze trends and make forecasts for 2025 and 2026.

Limitations: The findings are based only on data from one hospital, so they may not represent the whole state or country. Missing or incomplete records may affect the accuracy of the results. The models used may not capture unexpected future events like disease outbreaks or policy changes.



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