BARRIERS TO USE OF HEALTHCARE DURING PREGNANCY IN NIGERIA by ____________________________

BARRIERS TO USE OF HEALTHCARE DURING PREGNANCY IN NIGERIA by ____________________________
BARRIERS TO USE OF HEALTHCARE DURING PREGNANCY IN NIGERIA
by
Jayleen K. L. Gunn
____________________________
A Dissertation Submitted to the Faculty of the
DEPARTMENT OF EPIDEMIOLOGY AND BIOSTATISTICS
In Partial Fulfillment of the Requirements
For the Degree of
DOCTOR OF PHILOSOPHY
WITH A MAJOR IN EPIDEMIOLOGY
In the Graduate College
THE UNIVERSITY OF ARIZONA
2015
2
THE UNIVERSITY OF ARIZONA
GRADUATE COLLEGE
As members of the Dissertation Committee, we certify that we have read the dissertation
prepared by Jayleen Gunn, titled Barriers to Use of Healthcare During Pregnancy in
Nigeria and recommend that it be accepted as fulfilling the dissertation requirement for
the Degree of Doctor of Philosophy.
______________________________________________ Date: (August 4, 2015)
John Ehiri, PhD
______________________________________________ Date: (August 4, 2015)
Kacey Ernst, PhD
______________________________________________ Date: (August 4, 2015)
Sydney Pettygrove, PhD
Final approval and acceptance of this dissertation is contingent upon the candidate’s
submission of the final copies of the dissertation to the Graduate College.
I hereby certify that I have read this dissertation prepared under my direction and
recommend that it be accepted as fulfilling the dissertation requirement.
______________________________________________ Date: (August 4, 2015)
Dissertation Director: Elizabeth Jacobs, PhD
3
STATEMENT BY AUTHOR
This dissertation has been submitted in partial fulfillment of the requirements for an
advanced degree at the University of Arizona and is deposited in the University Library
to be made available to borrowers under rules of the Library. Brief quotations from this
dissertation are allowable without special permission, provided that an accurate
acknowledgement of the source is made. Requests for permission for extended quotation
from or reproduction of this manuscript in whole or in part may be granted by the head of
the major department or the Dean of the Graduate College when in his or her judgment
the proposed use of the material is in the interests of scholarship. In all other instances,
however, permission must be obtained from the author.
SIGNED: Jayleen Gunn
4
ACKNOWLEDGEMENTS
There are many individuals who supported me through this dissertation work and
the years leading up to it. I am grateful for the unwavering support of my family and
friends. Mom, thank you for proof-reading countless papers and listening to me complain
on a weekly if not daily basis. Without you I may have never made it out of freshman
English. Dad, thank you for talking mom into letting me go to South Africa. It was
instrumental in getting me where I am today. I would also like to thank every “teacher” I
have had along the way. From pre-K to PhD—you have all provided me with loving
support and instilled in me the belief that there is always more for me to learn.
I am especially thankful for having a committee that was so supportive of
my ideas and tolerant of what must have felt like an endless supply of questions. Thank
you all for being so patient. Dr. Jacobs, thank you for taking me on as a student. You
have been an extremely dedicated mentor. Without you I never would have been able to
make it through this process on time. Your dedication to students is something I admire.
Dr. Ehiri, without you this dissertation would be nonexistent. We have spent countless
hours together on numerous research projects, which I know will have a positive
influence on my future. Dr.’s Ernst and Pettygrove—you have always opened your doors
when I stopped by and taken the time to address my questions—thank you. Lastly, I
would like to thank Dr. Ezeanolue and the Healthy Beginning Initiative team for
entrusting me to tell part of the story of the women with whom you worked.
5
DEDICATION
To my parents—thanks for letting me explore the world beyond our fencepost.
6
TABLE OF CONTENTS
LIST OF TABLES ...............................................................................................................8
LIST OF FIGURES .............................................................................................................9
ABSTRACT .......................................................................................................................10
CHAPTER 1: INTRODUCTION ......................................................................................13
The Problem ...........................................................................................................13
Goals and objectives ..............................................................................................14
Role of the author in the present research ..............................................................15
Background ............................................................................................................16
Worldwide maternal mortality: Developed vs. developing countries ...................18
Maternal mortality in sub-Saharan Africa .............................................................18
United Nations Millennium Development Goals ..................................................20
Three Delay Model ................................................................................................21
Diseases influencing women’s health during pregnancy in sub-Saharan
Africa .........................................................................................................24
Malaria ...........................................................................................24
Human Immunodeficiency Virus / Acquired
Immunodeficiency Syndrome. ...........................................28
Anemia ...........................................................................................30
Comorbid diseases influencing maternal mortality in sub-Saharan Africa ...........32
Socioeconomic and cultural risk factors associated with access to care
during pregnancy in sub-Saharan Africa ...................................................34
Age .................................................................................................34
Family composition .......................................................................35
Education, employment and income ..............................................36
Distance of healthcare facility and skill level of provider .............36
Summary of the socioeconomic and cultural risk factors
associated with access to care during pregnancy in
sub-Saharan Africa.............................................................37
Cesarean section.....................................................................................................38
Nigeria....................................................................................................................41
Summary of the Introduction .................................................................................44
CHAPTER 2: METHODS .................................................................................................46
Introduction ............................................................................................................46
METHODS: Healthy Beginnings Initiative ...........................................................47
Overview ........................................................................................47
Population ......................................................................................47
Recruitment ....................................................................................50
Survey ............................................................................................51
Laboratory Measures .....................................................................51
Statistical Analysis .........................................................................54
7
Ethics Review ................................................................................55
METHODS: Demographic and Health Survey......................................................56
Overview ........................................................................................56
Population ......................................................................................56
Recruitment ....................................................................................58
Survey ............................................................................................59
Statistical Analysis .........................................................................60
Ethics Review ................................................................................61
CHAPTER 3: RESULTS ...................................................................................................62
Results: Malaria Parasitemia in Pregnancy (Aims 1 and 2) ..................................62
Results: Cesarean section in Enugu State, Nigeria (Aims 3 and 4) .......................65
Results: Cesarean section in Nigeria (Aims 5 and 6) ............................................72
Comparison of Cesarean Section Results Across Samples....................................84
CHAPTER 4: DISCUSSION.............................................................................................90
Malaria Parasitemia in Pregnancy .........................................................................90
Cesarean section in Enugu State, Nigeria ..............................................................91
Cesarean Sections in Nigeria .................................................................................96
Overall Discussion ...............................................................................................100
Strengths and Limitations ............................................................102
Practice and Policy.......................................................................104
Future Directions .........................................................................106
Conclusion ...................................................................................108
REFERENCES ................................................................................................................111
APPENDIX A: MANUSCRIPT 1 ...................................................................................129
APPENDIX B: MANUSCRIPT 2 ...................................................................................142
APPENDIX C: MANUSCRIPT 3 ...................................................................................168
APPENDIX D: MOTHER QUESTIONNAIRE ..............................................................191
APPENDIX E: POST-DELIVERY QUESTIONNAIRE ................................................195
APPENDIX F: LABORATORY MANUAL ..................................................................197
8
LIST OF TABLES
Table 1: Malaria parasitemia by the Malaria Plus System ............................................. 63
Table 2: Comparison of participant’s characteristics’ by malaria parasitemia
low vs high ............................................................................................................ 63
Table 3: Logistic regression models for malaria parasitemia and participant
level characteristics .............................................................................................. 65
Table 4: Comparison of participant baseline characteristics and infant gender
with mode of delivery ........................................................................................... 67
Table 5: Crude and logistic regression models of the odds of C-Section vs
vaginal birth ........................................................................................................... 69
Table 6: Weighted chi-square of the socio-economic and medical factors
associated with mode of delivery .......................................................................... 71
Table 7: Weighted logistic regression models of the socio-economic factors
associated with mode of delivery ......................................................................... 74
Table 8: Weighted percent of reasons why women did not deliver at a
healthcare facility ................................................................................................. 79
Table 9: Weighted percent of reasons why women did not deliver at a
healthcare facility stratified by area of residence. ................................................. 81
Table 10: Among primigravida women, weighted percent of reasons why women
did not deliver at a healthcare facility stratified by area of residence .................. 82
Table 11: Comparison of the logistic regression models for Aim 4 and Aim 6
among the full sample ........................................................................................... 83
Table 12: Comparison of the logistic regression models for Aim 4 and Aim 6
among the full sample ........................................................................................... 86
Table 13: Comparison of the logistic regression models for Aim 4 and Aim 6
among primigravida women .................................................................................. 88
9
LIST OF FIGURES
Figure 1: Reasons for maternal mortality in sub-Saharan Africa ......................................19
Figure 2: The Three Delay Model: Why women delay accessing care in
developing countries..........................................................................................23
Figure 3: Flow chart representing the women included in Aim 1 and 2............................48
Figure 4: Flow chart representing the women included in Aim 3 and 4............................49
Figure 5: Flow chart representing the women included in Aim 5 and 6............................58
10
ABSTRACT
INTRODUCTION: In sub-Saharan Africa, access to care during pregnancy and
child birth is an abiding challenge for many women. Many women face socioeconomic,
cultural, and physical barriers while attempting to access healthcare facilities during
pregnancy. These barriers often result in women accessing healthcare facilities after lifethreatening complications develop, ultimately leading to high rates of maternal mortality.
In Nigeria, several locally endemic diseases, such as malaria and HIV, impinge on
population health. Having access to care during pregnancy provides an opportunity for
prompt diagnosis, treatment, and prevention of common endemic disease. This
dissertation focused on access to care during pregnancy in Nigeria by using two
indicators: malaria parasitemia and Cesarean-section (CS). Therefore, this dissertation
had two overarching goals. The first was to estimate the prevalence of malaria
parasitemia during pregnancy and to determine maternal risk factors associated with high
malaria parasitemia in Enugu State, Nigeria. The second was to establish the incidence of
CS and to determine the socioeconomic and medical risk factors that are associated with
having a CS among women in Enugu State, as well as in Nigeria as a whole.
METHODS: Secondary analyses of two unique datasets ––Healthy Beginnings
Initiative (HBI) and the Nigerian Demographic and Health Survey (DHS) ––were
conducted. The HBI cohort study took place in Enugu State, Nigeria. The prevalence of
peripheral malaria parasitemia in Enugu State was established within the context of HBI.
Malaria parasitemia was scored according to the Malaria Plus System (0 to ++++). For
this dissertation those in the 0 and + group were classified as low having parasitemia;
while those in the ++ and +++ groups were classified as having high parasitemia. Person-
11
level maternal risk factors that were associated with high malaria parasitemia were
estimated using crude and adjusted logistic regression modeling with malaria parasitemia
as the main outcome. The incidence of CS in Enugu State was also estimated within
context of the HBI cohort. Socioeconomic and medical risk factors associated with
having a CS in Enugu State, Nigeria were estimated. To investigate the extent to which
the findings from the HBI represent the rates of CS in Nigeria as a whole, the Nigerian
DHS was utilized. The Nigerian DHS was a cross-sectional study that was conducted
throughout Nigeria. The incidence of CS in all of Nigeria was estimated. Socioeconomic
and medical risk factors associated with having a CS were also investigated. Crude and
adjusted logistic regression models with CS as the main outcome are presented. Weights
were applied to all analyses conducted with the DHS to make the data representative at
the county level.
RESULTS: Over 99% of women in the HBI study tested positive for peripheral
malaria parasitemia. For each additional person in the household, a 6% lower odds of
high malaria parasitemia was found (p<0.05). Regarding CS, analyses of both datasets
indicated that Nigeria has relatively low rates of CS compared to the World Health
Organization’s recommendations. In the HBI, 7.2% of women in Enugu State, Nigeria
had a CS. Significantly lower odds of having a CS were observed among women who
live in a rural setting compared to those who reside in an urban setting (p<0.05).
Percentages of CS increased significantly as maternal age and/or education increased.
HBI results demonstrated 53% higher odds of having a CS if participants had high
malaria parasitemia compared to those with lower malaria parasitemia (p<0.05). Results
of the DHS yielded even lower rates of CS with only 2.3% of women in Nigeria overall
12
having had a CS during their last delivery. Consistent with analysis for Enugu State, in
the DHS women living in rural areas had significantly lower odds of having a CS than
those living in urban areas (p<0.05). Likewise, religion was significantly associated with
having had a CS; Muslim women had 54% lower odds of having a CS compared to
Catholics (p<0.05). Women who had health insurance and women who received prenatal
care from a skilled birth attendant had increased odds of having a CS compared to
women who did not have insurance and received no prenatal care (adjusted OR [aOR]
1.78: 95%CI 1.18-2.67, p<0.05; aOR 3.00: 1.51-5.96, p<0.05).
DISCUSSION: Based on the high prevalence of malaria among women in the
HBI study, education on best practices to prevent malaria during pregnancy, and
resources in support of these practices are urgently needed. Likewise, low rates of CS in
both Enugu State and across Nigeria indicate that Nigerian women may not have
adequate access to obstetric care during delivery. Results from this dissertation also
indicate that Nigerian women face barriers in obtaining adequate perinatal healthcare,
ultimately perpetuating the cycle of high maternal mortality and gross health deficiencies
that are common to Nigerian women.
13
CHAPTER 1
INTRODUCTION
The Problem
In 2014, an estimated 134,028,000 live births occurred globally; the equivalent of
255 births per minute [1]. Many of these births occur in developing countries, where
adequate prenatal care and healthcare facilities are either not accessible or nonexistent
[2]. Obtaining prenatal care is essential to the prevention, detection, and treatment of
health-related complications during pregnancy [3]. However, a number of individual and
health system characteristics contribute to the delay in women seeking healthcare
services during pregnancy [2, 4]. A disproportionate number of maternal and fetal deaths
occur in sub-Saharan Africa [5, 6].
As one of the fastest growing populations in the world, Nigeria is a key location
for studying woman’s access to healthcare during pregnancy. This rapid population
growth is at least partially attributable to Nigeria’s relatively high crude birth rate, at
38.03 births per 1,000 women [1]. In 2013, Nigeria had the second largest proportion of
global maternal deaths at 14% (n=40,000) [7]. Nigeria is also an important location for
examining the burden of infectious disease during pregnancy as two key contributors to
maternal mortality are human immunodeficiency virus (HIV) and malaria are common in
Nigeria [8]. Therefore, accessing health care during pregnancy is essential to decreasing
maternal mortality.
Only an estimated 35% of Nigerian women deliver at a healthcare facility [9] as
compared to 47% in Kenya[10] and 40% in Cameroon[11]. This is problematic because
14
obstetric complications occur most often around the time of delivery. Increasing access to
emergency obstetric care, such as Cesarean sections (CS), decreases maternal and infant
morbidity and mortality [12, 13]. These deaths would be largely preventable with
improved quality and increased coverage of healthcare [8]. However, previous research
has demonstrated that women encounter numerous barriers while attempting to access
healthcare during pregnancy, e.g. disease, distance to healthcare facility, lack of
transportation, and cost of procedures [2, 4]. Therefore, this dissertation had two
overarching goals. The first goal was to estimate the malaria burden of pregnant women
and to explore maternal risk factors associated with high malaria parasitemia in Enugu
State, Nigeria; the second goal was to estimate the incidence of CS in Nigeria and
determine what socioeconomic and medical risk factors are associated with having a CS
among women in Enugu State, as well as in Nigeria overall. This will all be discussed
within the framework of Thaddeus and Maine’s Three Delay Model [2] and the United
Nations’ Millennium Development Goals [14] in the introduction.
Goals and objectives
This dissertation will focus on common complications of pregnancy in Nigeria, by
using data from the Healthy Beginning Initiative Cohort in Enugu State, Nigeria, as well
as data from the Demographic and Health Survey. The Specific Aims for this dissertation
were to:
1. Estimate the population-based malaria burden during pregnancy in Enugu
State, located in southeastern Nigeria;
2. Explore person-level maternal risk factors associated with high malaria
parasitemia;
15
3. Estimate the incidence of CS among pregnant women in Enugu State, Nigeria
using data from the Healthy Beginnings Initiative;
4. Determine if socioeconomic or medical risk factors are associated with having
a CS within Enugu State, Nigeria;
5. Estimate the incidence of CS among pregnant women throughout Nigeria
using the Demographic and Health Study dataset; and to
6. Determine if socioeconomic or medical risk factors are associated with having
a CS in Nigeria.
Role of the author in the present research
Each Aim for this dissertation required the author to conduct a secondary data
analysis. For Specific Aims 1 – 4, data from the Healthy Beginnings Initiative cohort was
used, which were collected in Enugu State, Nigeria. The purpose of the Healthy
Beginnings Initiative was to determine if providing onsite laboratory testing of common
diseases to pregnant women and their spouses increased testing uptake. The author
developed a statistical analysis plan based on guidance provided by the principal
investigator of the overall study. The author also wrote two manuscripts using this data:
one based on Specific Aims 1 and 2, and another based on Specific Aims 3 and 4. The
parent study was approved by the Institutional Review Board of the University of
Nevada, Reno, and the Nigerian National Health Research Ethics Committee. This
secondary analysis was considered exempt from human subjects review by the Mel and
Enid Zuckerman College of Public Health Research Office.
A third manuscript explored Specific Aims 5 and 6. For this manuscript a
secondary analysis of the Demographic and Health Surveys (DHS) conducted in Nigeria
was performed. The DHS data are publically available to researchers. The author
16
developed the statistical analysis plan based on the recommendations of the authors of the
DHS, and was responsible for all data analysis and interpretation. This secondary analysis
was also considered exempt from human subjects review by the Mel and Enid
Zuckerman College of Public Health Research Office.
Background
It is well-documented that increasing women’s access to care during pregnancy
has long-lasting positive implications for her health and the health of her unborn fetus,
reducing morbidity and mortality during pregnancy. However, pregnant women in
developing countries often delay seeking care because of the large number of obstacles
they must overcome to obtain treatment at a healthcare facility [2, 4]. These barriers
include lack of knowledge of the importance of seeking care during pregnancy, poverty,
gender inequalities in household decision-making, cultural barriers, and geographical and
transportation barriers [2, 4]. Overcoming these barriers is essential to decrease maternal
and perinatal mortality in developing countries. Improving access to care decreases the
negative effects of common comorbid conditions associated with pregnancy, including
malaria, HIV, and anemia. These diseases require medical or behavioral interventions to
prevent future negative consequences for mothers and their neonates. Decreasing the
burden of malaria during pregnancy is essential, as malarial infection during pregnancy is
associated with an increase in maternal and perinatal mortality [15-18]. Therefore,
determining the prevalence of malaria among pregnant women in holoendemic areas is
crucial to evaluating if women are obtaining adequate prenatal care (Aims 1 and 2).
17
An understanding of the common barriers associated with accessing healthcare
during pregnancy is also important. Prompt access to life saving obstetric services, such
as CS, are needed to decrease maternal mortality in many developing countries.
However, many women face ongoing barriers that restrict them from accessing healthcare
during delivery. By determining the factors that are associated with uptake of CS, we can
better understand how to best allocate resources for future programing that targets
improving healthcare utilization among pregnant women (Aims 3-6).
In this dissertation I will first discuss maternal mortality worldwide and in subSaharan Africa (SSA). Next, I will provide an overview of the United Nations
Millennium Development Goals, which helped to provide a context for the Aims of this
dissertation. Additionally, I will discuss the Three Delay Model, a framework to organize
factors affecting women’s access to care in developing countries. Based on the
Millennium Development Goals and the Three Delay Model, this dissertation took a twopronged approach to discussing maternal mortality by investigating the disease-related,
and socioeconomic and cultural factors commonly associated with access to healthcare
and maternal mortality. Next, CS and its role in reducing maternal mortality in SSA will
be presented. Finally, the focus will turn to Nigeria, which contributes 14% of the global
burden of maternal deaths, as addressing factors that lead to maternal mortality in Nigeria
is essential to reducing global maternal mortality rates [7]. This dissertation includes 3
unique studies and 6 Aims, which will be discussed in Chapters 2 – 4.
18
Worldwide maternal mortality: Developed vs. developing countries
In 2013, 289,000 women died of mostly preventable pregnancy complications [5].
This equates to approximately 800 women per day who die from complications during
pregnancy or directly after childbirth [5]. Much of this burden is borne by women in
developing countries, where over 99% of maternal deaths took place in 2013. In that
year, the maternal mortality ratio in developing countries was 230 per 100,000 live births
compared to 16 per 100,000 live births in developed countries [5]. Furthermore,
according to the World Health Organization (WHO): “A woman’s lifetime risk of
maternal death – the probability that a 15 year old woman will eventually die from a
maternal cause – is 1 in 3700 in developed countries, versus 1 in 160 in developing
countries” [5]. Worldwide, 75% of maternal deaths can be attributed to 5 factors: severe
bleeding (most common after childbirth), infections (most common after childbirth), preeclampsia or eclampsia during pregnancy, complications associated with delivery, and
unsafe abortion [19]; the remaining 25% of maternal deaths are attributed to diseases
such as acquired immunodeficiency syndrome (AIDS) or malaria during pregnancy [5].
Maternal mortality in sub-Saharan Africa
Sub-Saharan Africa has historically carried a disproportionate burden of adverse
health related outcomes for women and children [14]. The adult lifetime risk of maternal
death is 1 in every 31 women in SSA [20]. According to a recent meta-analyses, maternal
deaths in SSA can be attributed to: obstructed labor [2.1% (95% CI: 0.7–5.2)],
HIV/AIDS related complications [6.4% (4.6–8.8%)], pre-existing medical conditions
[12.8% (7.0–22.3%)], unsafe abortion [9.6% (5.1–17.2%)], embolism [2.1% (0.8–4.5%)],
19
hemorrhage [24.5% (16.9–34.1%)], hypertension [16.0% (11.7–21%)], sepsis [10.3%
(5.5–18.2%)], complications of delivery [3.3% (1.5–6.7)] and other causes (13%) (See
Figure 1) [19]. Therefore, the majority of maternal deaths in SSA can be attributed to
lack of access to adequate care during pregnancy and birth. However, addressing a
woman’s access to proper healthcare during pregnancy in SSA and many other parts of
the world is often not straightforward. In order to address health disparities such as this,
the United Nations created the Millennium Development Goals.
Figure 1. Reasons for Maternal Mortality in sub-Saharan Africa
Adapted from Say, L., et al. Global causes of maternal death: A WHO
systematic analysis, 2014.
20
United Nations Millennium Development Goals
The Millennium Development Goals include 8 target goals with the aims of
decreasing poverty, hunger, illiteracy, gender inequality, and diseases; while also
attempting to increase environmental sustainability and access to healthcare, and were
established by the United Nations in 2000 [14]. These goals were created in an attempt to
focus efforts toward achieving common global objectives, including: 1) eradicating
extreme poverty and hunger; 2) achieving universal primary education; 3) promoting
gender equality and empowering women; 4) reducing child mortality; 5) improving
maternal health; 6) combating diseases such as HIV/AIDS and malaria; 7) ensuring
environmental sustainability; and 8) growing a global partnership for development [14].
Millennium Development Goals 5—improving maternal health—and 6—
combating diseases—are particularly relevant to the present research. Goal 5 has two
sub-goals: 1) to reduce the worldwide maternal mortality ratio by 75%, from 380
maternal deaths per 100,000 in 1990, to 95 maternal deaths per 100,000 in 2015; and 2)
to achieve universal access to reproductive healthcare by 2015 [21]. Millennium
Development Goal 6, has three sub-goals: 1) to halt and begin reversing the spread of
HIV by 2015; 2) to provide universal access to treatment for HIV/AIDS by 2010; and 3)
to halt and begin to reverse the incidence of malaria and other major diseases by 2015
[21]. Although progress has been made toward the Millennium Development Goals, they
have been difficult to achieve, in part because women in developing countries are
disproportionately burdened by barriers to reaching these goals, including lack of
education, equality, access to adequate care, and poverty [22].
21
In order to meet Millennium Development Goals 5 and 6, vast improvements in
facilities, infrastructure, and training of skilled obstetricians needed to be made within
SSA. However, in 2013, SSA continued to have the largest maternal mortality ratio at
510 deaths for every 100,000 live births in women between the ages of 15–49 [7].
Although this is a vast improvement to 1990 estimates of 990 deaths for every 100,000
live births in women aged 15–49 years, it is still more than double any other area in the
world [7]. It is also more than the initial world estimate of 330 maternal deaths for every
100,000 live births [7]. In order to achieve Millennium Development Goal 5, an average
annual decrease of 5.5% in maternal mortality ratio was needed in SSA [14]. However,
between 1990–2013, the average annual decrease in the maternal mortality ratio in SSA
was only 2.9%; approximately half of the target goal [7]. Furthermore in 2013, SSA still
accounted for 62% of the global burden of maternal deaths [7]. Accessing healthcare
during pregnancy is essential to achieving Millennium Development Goals 5 and 6.
However, women must overcome multiple barriers in order to gain access to care in SSA.
Understanding when women seek—or do not seek—treatment during pregnancy is
essential to understanding why it has been difficult to improve maternal health (Goal 5)
and combat diseases (Goal 6) in SSA.
Three Delay Model
The Three Delay Model is a conceptual framework that provides organization for
the factors affecting why women delay accessing care in developing countries. A number
of individual and health system characteristics obstruct access to healthcare and
contribute to the delay in women seeking healthcare services during pregnancy [2]. In
22
order to provide a framework for the obstacles women face while obtaining adequate
healthcare during pregnancy, Thaddeus and Maine developed the widely accepted Three
Delay Model [2]. This framework includes three kinds of delays: 1) delays in decisions to
seek care, 2) delays in arrival at a healthcare facility, and 3) delays in receiving adequate
treatment for obstetric complications (see Figure 2).
In SSA, several factors affect a woman’s decision to seek treatment during
pregnancy. Delays in seeking treatment during pregnancy (Delay 1) may come from a
variety of sources, including the financial costs of healthcare; the status of a woman
within her family; culture; age; education; and a woman’s overall health. Although
healthcare-seeking behavior is typically influenced by illness [2], delaying care may
increase the likelihood of medical complications and increase adverse events during
pregnancy and delivery.
Delays in reaching an adequate healthcare facility (Delay 2) are caused by factors
that affect a woman’s ability to physically reach a healthcare facility [2]. In order to reach
a healthcare facility, many women in SSA must either walk long distances—often in
rough terrain—or access an alternative form of transportation. Women living in rural
areas are often at an increased disadvantage as they must overcome limited transportation
options, poor road conditions, and high costs associated with travel [2, 4, 23]. Delays in
receiving adequate care at a healthcare facility (Delay 3) occur when factors affect a
facility’s ability to provide needed medical services. Healthcare facilities in developing
countries often suffer from shortages in trained personal, supplies, and equipment.
The Three Delay Model acknowledges that no decision is made in isolation and
that an overall connectedness between delays exists. The factors affecting seeking
23
treatment during pregnancy and reaching an adequate healthcare facility—Delays 1 and
2—are so closely intertwined that it makes little sense to discuss them in isolation.
Therefore, in the following sections this dissertation will focus on diseases that are
common in pregnant women in SSA and the socioeconomic and cultural influences that
affect a woman’s decision to seek treatment.
Figure 2: The Three Delay Model: Why women delay accessing care in
developing countries.
Note: This is a visual adaptation of the 3-delay model by Thaddeus and Maine (1994).
Delays do not exist in isolation and are all interconnected.
24
Diseases influencing women’s health during pregnancy in sub-Saharan Africa
As previously mentioned, healthcare seeking behavior is often influenced by
illness [2]. Costs associated with healthcare utilization often deter women from accessing
healthcare during pregnancy even when illness arises [2, 4, 24]. HIV/AIDS and malaria
are common in SSA and both diseases have been associated with adverse pregnancy
outcomes [15-18, 25-39]. HIV/AIDS may further decrease healthcare utilization because
of stigma associated with the disease [40, 41]. Anemia is also an important risk factor for
adverse pregnancy outcomes in SSA and is implicated in the relationship between
malaria and adverse pregnancy outcomes [18, 30, 42-45]. The following sections will
focus on how malaria, HIV/AIDS, and anemia affect pregnancy and neonatal outcomes in
SSA.
Malaria
Malaria, a mosquito-borne disease, is caused by the parasite, Plasmodium [46].
Five species of the protozoan parasite of the genus Plasmodium infect humans and cause
malaria: P. falciparum, P. malariae, P. ovale, P. vivax, and P. knowlesi. Of these, P.
falciparum causes the most severe form of malaria and is responsible for the largest
proportion of morbidity and mortality [47]. Malaria is transmitted when an infected
female mosquito of the genus Anopheles bites a human [48].
Globally, malaria is accountable for approximately 1.24 million deaths per year
[49]. It is also the leading cause of morbidity and mortality for children under five in SSA
[50, 51]. More malaria-related deaths in both children and adults occur in western,
eastern, and central Africa than any other part of the world [49]. Roughly 80% of all
25
cases and 90% of all deaths from malaria occur in SSA [50]; pregnant women are among
the most vulnerable to this disease.
Between 25 and 50 million women will become pregnant this year in malariaendemic areas of SSA [52, 53]. Pregnant women are twice as likely to be bitten by the
Anopheles mosquito than non-pregnant women [29, 54]. It is possible that this is because
of an increase in respiration and blood flow to the skin during pregnancy [29] that entices
the Anopheles mosquitos, which are attracted to moisture and heat, and consequently
increasing the number of mosquito bites to pregnant women [29]. Malaria infections from
P. falciparum show consistently high parasitemia levels throughout pregnancy, indicating
an inability to mount a sufficient immune response to the malaria parasite during
pregnancy [55-58]. Some cases of spontaneous recovery from malaria have been reported
[58, 59]; however, these results have been inconsistent [60, 61]. Recent studies suggest
that malaria, as either a primary or secondary infection, may contribute to almost 25% of
maternal deaths in endemic areas [34, 62]. In addition to its effects on pregnant women,
malaria infection during pregnancy is also linked to poor birth outcomes [25].
Maternal and fetal outcomes associated with malaria include maternal anemia
[26], preterm delivery, eclampsia, postpartum hemorrhage, intrauterine growth restriction
(IUGR), spontaneous abortion, puerperal fever, still-birth, and maternal and fetal deaths
[27]. Malaria is estimated to contribute to preterm delivery, resulting in approximately
19% of low birth weight births [63]. In malaria endemic areas, up to 200,000 newborn
deaths occur each year as a results of malaria during pregnancy [33]. Malaria is assumed
to produce adverse fetal outcomes via systemic effects, such as maternal anemia [26, 64,
65], or local effects such as placental infection [65-68]. Maternal anemia decreases
26
erythropoiesis [30, 69] and increases red blood cell apoptosis [30, 70], ultimately leading
to a maternal hypoxic state. During this hypoxic state, impaired growth and
vascularization occur within a pregnant woman, which in turn can lead to fetal hypoxia
[71]. Decreased vascularization leads to a reduction in the exchange of important
nutrients and gases across the placenta, including oxygen, which in turn, produces a fetal
hypoxic state [66, 72, 73]. Intrauterine growth restriction may occur because of fetal
hypoxia and decreased nutrient uptake [72]. Malaria infection is also thought to disrupt
cytokine activity, resulting in an increase in placental infection; this is especially found
during the first or second pregnancy, and can result in preterm infants with intrauterine
growth restriction [67, 68, 74-80]. Even cases of malaria that are asymptomatic may pose
a threat to an unborn fetus; therefore, prophylactic measures to prevent malaria during
pregnancy are recommended and are essential to achieving Millennium Development
Goals 5 and 6 [21, 81].
Prophylactic malaria measures during pregnancy include sleeping under
insecticide-treated nets (ITN) and intermittent preventative treatment with the inclusion
of sulphadoxine-pyrimethamine (IPTp-SP) as part of antenatal care [32]. Both of these
interventions have been deemed largely successful at reducing malaria transmission rates
during pregnancy, thereby decreasing both infant and maternal mortality [31, 82, 83].
This may be because a decrease in placental malaria infection is found in women who
receive more than three doses of IPTp-SP and sleep under ITN [82].
Although IPTp-SP and ITNs have demonstrated great efficacy in randomized
control trials, their real-world effectiveness has not been as high [84, 85]. Communitybased assessments of clinics that are implementing IPTp-SP programs have found
27
medication shortages in these facilities [86]. Furthermore, access to malaria preventative
measures is not synonymous with utilization. Numerous studies in SSA have shown low
utilization rates of ITN even when they are available in the house [85]. Discomfort
associated with sleeping under the net, damaged nets, disruption of sleeping
arrangements, forgetting, or an all-around dislike of sleeping under the nets, and
perceived low mosquito density are all common reasons reported for not sleeping under
an ITN [87]. Additionally, in SSA, a disproportionate number of women who do take
IPTp-SP and properly use ITN are wealthier and more educated [83]. Therefore, even
though mass distribution of malaria medications and ITN are essential to reducing
malaria during pregnancy, the effectiveness of these programs remains debatable.
In addition to socioeconomic factors that influence the malaria burden, cultural
beliefs often influence women’s decisions to seek treatment for malaria during
pregnancy. For example, in qualitative studies women have reported delaying antenatal
care early in pregnancy because of fear that a community member would put a hex on
them via witchcraft [88]. This link between modern medicine—including malaria
control—and witchcraft is fairly well documented in qualitative literature [89-91].
Incorporating these beliefs into malaria control programs remains essential to reducing
malaria during pregnancy.
In summary, a combination of socioeconomic and medical risk factors are related
to perpetuate malaria, leading to high morbidity and mortality rates among pregnant
women in malaria endemic areas. Therefore, by establishing the prevalence of malaria
parasitemia among pregnant women in Nigeria and discussing the socioeconomic risk
factors associated with malaria parasitemia, this dissertation will add to the overall
28
assessment of programs aimed to reduce malaria during pregnancy in Enugu State,
Nigeria.
Human Immunodeficiency Virus / Acquired Immunodeficiency Syndrome.
Human Immunodeficiency Virus (HIV) attacks the immune system and destroys
T-cells, a type of white blood cell that fight off infections [92]. Therefore, HIV weakens a
person’s ability to defend against infections [93]. As the virus invades the body, it
eventually makes the infected person immunodeficient. Acquired Immunodeficiency
Syndrome (AIDS), the most advanced state of an HIV infection occurs when the infected
individual’s CD4 count––a protein on immune cells such as T-cells––falls below 200
cells/mm3 [93]. HIV is primarily spread via unprotected sex, injection or transfusion of
infected blood, needle sharing, and mother-to-child transmission [94].
In 2013, 35 million people worldwide were living with HIV, of which 2.1 million
had become newly infected [93]. Sub-Saharan Africa accounted for 71%, or 25 million,
of prevalent cases and 70% or 1.6 million of the global incident cases of the disease [93,
95]. In SSA, women have the highest proportion of new HIV cases, which makes
children particularly vulnerable [20].
In 2008, the WHO estimated that 42,000 women died worldwide during
pregnancy from AIDS; in SSA alone, that number was an estimated 18,000 [20]. In fact,
AIDS was responsible for 9% of all maternal deaths in SSA in 2008 [20]. By 2013, the
WHO reported a decline in the number of estimated maternal deaths from AIDS in SSA
to 3.8% [7]. Therefore, in 2013, the AIDS-attributed maternal mortality ratio was 19
maternal deaths per 100,000 live births [7]. However, SSA contributed 91% of the
29
estimated global number of AIDS-related maternal deaths in 2013 (n=7,500) [6, 7]. This
high burden of HIV/AIDS in women within SSA also affects the region’s children.
The prevalence of HIV in children in SSA is 6 – 762 times that of children living
anywhere else in the world, with 1.6 million prevalent cases and 230,000 incident cases
[95]. Mother-to-child transmission (MTCT) of HIV is responsible for 90% of all HIV
infections in children [39]. Being HIV-positive (HIV+) during pregnancy is associated
with many adverse fetal outcomes that include low birth weight [96-98], increased infant
mortality [96-99], miscarriage [97, 98], small for gestation age [97, 98], and preterm birth
[97, 98]. Mother-to-child transmission can occur during pregnancy, labor, delivery, or
breastfeeding; in short, any time a child becomes exposed to infected maternal body
fluids (e.g. blood or breast milk) [93].
Treatment of HIV/AIDS in pregnant women decreases MTCT [93], and
prevention of mother-to-child transmission (PMTCT) services are designed to prevent
HIV transmission from an HIV-infected mother to her child [100]. When no preventative
measures are taken, MTCT rates are highest during delivery at 15–45% [37, 93, 101].
When preventative measures are taken, MTCT rates can be reduced to less than 2%
[101]. Prevention of mother-to-child transmission services include the short-term
provision of antiretrovirals to prevent HIV transmission from mother to child, and
lifelong antiretroviral treatment for HIV+ women [102]. A large increased effort has been
made to administer antiretroviral treatment to HIV+ women during pregnancy; however,
only 15% of young women in SSA aged 15-24 are aware of their HIV status [21].
Therefore, the majority of women of childbearing age do not receive PMTCT services
when needed. The stigma associated with HIV (i.e., negative attitudes about persons
30
living with HIV) complicates the use of PMTCT and remains an important barrier to
women deciding to seek care [40, 41].
A community-based, cross-sectional survey of mothers in eastern SSA showed
that stigma and lack of HIV knowledge were significantly associated with a decreased
likelihood of maternal HIV testing [103]. Another study in rural SSA [104] also
established that women who demonstrated stigma towards someone with HIV were less
likely to seek care at a healthcare facility during delivery. The authors of that study
reported—based on their qualitative data—that childbirth at a health facility was
commonly viewed as most appropriate for women with pregnancy complications (e.g.,
HIV); therefore, women who deliver at health facilities may be labeled as HIV+ in the
community [104]. This HIV stigma further delays women seeking treatment during
delivery when complications do arise. The medical procedure that is the focus of Aims 36 (CS), can only safely be performed in the context of a healthcare clinic setting;
therefore, a better understanding of the associations between stigma of HIV and
accessing healthcare becomes essential.
Anemia
Hemoglobin is the red blood cell protein that carries oxygen in the blood [105].
The measurement of hemoglobin concentration in the blood is the most common strategy
to assess the presence of anemia [106]. To measure hemoglobin concentration, a blood
sample is placed into an automated machine where the red blood cells are broken down to
get hemoglobin [106]. A chemical containing cyanide is exposed to the free hemoglobin,
which then binds tightly with the hemoglobin molecule to form cyanomethemoglobin
31
[106]. Next, a light is shown through the solution and the amount of absorbed light is
measured, determining the amount of hemoglobin [106]. The WHO classifies anemia in
pregnant woman as hemoglobin below 11g/dL [107], and severe anemia is classified as a
hemoglobin less than 7 g/dL [17].
Globally, 56 million pregnant women are affected with anemia [45]. In Africa, 19
million pregnant women are living with anemia, and it is estimated that 55.8% of all
pregnant women in Africa suffer from anemia compared to 44.4% of non-pregnant
women [45]. In SSA, anemia is seldom caused by one independent factor. Iron deficiency
may be the primary cause of anemia; however, it often coexists with blood disorders and
parasitic infections, such as malaria, hookworm and schistosomiasis [45, 108-112].
Because of the complex nature of anemia, few studies have assessed its etiology in
SSA[113]. This gap in the literature is likely the result of inadequate diagnostic facilities
in SSA and because parasitic infection and nutritional deficiencies often coexist in
SSA[113]. To treat anemia and raise hemoglobin levels, correctly diagnosing the causal
factors is essential [45]. As previously stated, this is often very difficult to accomplish in
SSA because women usually live with overlapping conditions [43]. Therefore, treating
any one of these conditions in isolation may not remedy anemia [43].
Pregnant women and children are two groups that are among the most susceptible
to all types of anemia [45], and an increased risk of maternal and child mortality
attributed to severe anemia has been well documented [42, 44]. It is commonly thought
that other poor maternal and perinatal outcomes, such as congestive heart failure, fetal
death, low birth weight, and preterm birth are linked to maternal anemia [17, 114];
however, these relationships are inconsistent. Some epidemiological studies have found a
32
relationship between maternal anemia and poor birth outcomes [73, 115-117], while
others have not [117-119]. This discrepancy in the literature is partly based on the
complex nature of the different causes of anemia in developing countries where diseases
such as malaria are often highly prevalent in women with anemia [45].
The effects of maternal hemoglobin levels on perinatal outcomes have not been
well established in malaria endemic areas [65, 120]. Malaria infection complicates this
relationship because little agreement exists on the mechanisms that mediate adverse fetal
outcomes in neonates [53, 64]. Malaria may have systemic effects such as maternal
anemia [26, 64, 65], or local effects such as placental infection [65-68] that may reduce
fetal birth weight. Maternal anemia decreases erythropoiesis [30, 69] and increases red
blood cell apoptosis [30, 70], which in turn may cause a fetal hypoxic state that then
adversely affects fetal outcomes [71]. Research linking hemoglobin to adverse perinatal
outcomes is contradictory, with results limited by small sample size and varying
according to geography [53, 99, 121], and thus more research is needed to clarify this
relationship.
Comorbid diseases influencing maternal mortality in sub-Saharan Africa.
A large number of pregnant women live in malaria endemic areas, putting women
and their infants at risk for adverse outcomes. However, these diseases do not exist in
isolation. A large proportion of women who are at risk for malaria live in areas with
concomitant high HIV prevalence, and one consequence of the expanding HIV/AIDS
epidemic is the increasing comorbidity of HIV and malaria [122]. This is of particular
concern in SSA where malaria is endemic and 80% of the world’s HIV+ women reside,
33
along with 90% of the world’s HIV+ children [123]. A woman’s susceptibility to malaria
is higher if she is also co-infected with HIV [35]. Not only does an HIV+ woman have an
increased susceptibility to malaria, but higher levels of malaria parasitemia are found in
women with HIV [52, 124, 125]. Women infected with both HIV and malaria during
pregnancy consistently show higher parasitemia densities and more severe anemia [52,
124]. By impairing the ability to develop immunity, HIV increases the burden of malaria
during pregnancy, putting both the mother and the neonate at risk [52, 126].
The comorbidity of HIV and malaria are associated with adverse outcomes for
both the mother and the neonate [96, 125]. Neonates born to women who had both HIV
and malaria had significantly lower birth weights [125], and an increased risk of stillbirth
or post-neonatal mortality [127, 128], preterm delivery [127], and maternal anemia [125],
compared to those born to mothers who were negative for both diseases [127]. An
increased risk of adverse perinatal outcomes is not found when comparing women who
have the dual infection of HIV and malaria to women who have malaria alone [75].
However, the results relating these comorbid conditions to fetal outcomes remain
understudied [125].
Because the malaria parasite affects red blood cells, pregnant women
disproportionately suffer from anemia as a result of malaria infection [34]. In fact, it has
been estimated that malaria is responsible for 25% of severe anemia during pregnancy in
SSA [17]. HIV further complicates this relationship as the co-infection of HIV and
malaria is often associated with even higher rates of severe anemia compared to those
who have only one of these conditions [15]. Therefore, women who live in areas with
high malaria transmission rates and high HIV rates also have an increased risk of anemia.
34
Treating these diseases during pregnancy is often not straight forward. Women
often delay seeking treatment for common diseases associated with pregnancy because of
socioeconomic and cultural beliefs. In order to have the greatest impression on most of
the Millennium Development Goals, treatment and control measure need to be
implemented that take into consideration the interconnectedness of disease and culture in
SSA [43, 129]. To gain a deeper understanding of risk factors associated with adverse
maternal and fetal outcomes, a holistic understanding—one that takes into consideration
socio/demographic, as well as medical risk factors—of a woman’s healthcare is required.
Therefore, the next section will focus on the socioeconomic and cultural factors that
influence maternal and perinatal health.
Socioeconomic and cultural risk factors associated with access to care during
pregnancy in sub-Saharan Africa
Socioeconomic factors and culture influence decision-making and affect
healthcare utilization in SSA (See Figure 2) [4]. Increasing healthcare utilization is
essential to achieving Millennium Development Goal 5, because the use of healthcare
services by women is a key determinate of her morbidity and mortality during pregnancy
[2, 4]. Therefore, these influences are essential to understanding why women delay
seeking treatment during pregnancy and will be discussed in the following sections.
Age
For many reasons, age is often used to represent experience utilizing healthcare
services [4, 130]. Because of cultural norms in many countries in SSA, younger women
35
are often less influential in their households than older women [131, 132]. This restricted
autonomy tends to deter adequate utilization of healthcare services [131, 133]. Therefore,
younger women—compared to their older counterparts—are less likely to receive more
than minimal prenatal care and are less likely to have a skilled birth attendant during
delivery-i.e. doctor, nurse, midwife [132]. In addition, age is also positively associated
with socioeconomic status and pregnancy wantedness [130, 132]. As wantedness
increases, more women attend prenatal care and have a doctor present at delivery in SSA
[130]. Similarly, it is typically more acceptable for older women to deliver at a healthcare
facility because of the increased risk of adverse maternal and fetal outcomes associated
with mothers’ age [130, 134, 135]. Therefore, older women are more likely to deliver at a
healthcare facility than younger women, and having a skilled birth attendant present at
delivery reduces maternal mortality [136].
Family composition
Family composition can also have a significant effect on a woman’s ability to
access healthcare. With multiple young children, women may have difficulty finding
adequate child care in order to deliver at a healthcare facility[4]. In addition, because of a
diffusion of power in family decision-making and resources, having extended family in
the home may effect a woman’s ability to make decisions about her own healthcare [4].
Being married may also affect a woman’s access to healthcare. Single women are thought
to have more autonomy, and therefore increase their utilization of healthcare services
when they can financially afford services or have positive support from family[4].
However, some evidence suggests that single women may be less likely to deliver at a
36
healthcare facility if they feel stigmatized because of being pregnant while unmarried
[137], thus decreasing their chances of delivering with a skilled birth attendant, and
increasing their risk of maternal and infant morbidity and mortality[138].
Education, employment and income
Education, employment status, and household income are typically highly
correlated and are all positively associated with utilization of healthcare facilities [137,
139-141]. Women with more education and women who are employed often show more
confidence in their household and decision-making skills [130, 137], which may increase
women’s rates of healthcare facility usage during pregnancy and using a skilled birth
attendant during delivery[4]. Likewise, women with more education and women who are
employed often have greater control over family resources and play a larger part in
reproductive decision-making [23, 142-144]. Women with lower incomes often lack the
financial ability to utilize healthcare services while pregnant, thereby increasing their
rates of adverse maternal and fetal outcomes [144].
Distance of healthcare facility and skill level of provider
Although most African countries have healthcare facilities with perinatal services
available, distance and poor road conditions often make healthcare facilities difficult to
access [2]. Many pregnant women simply do not attempt accessing healthcare because
transportation is not available and walking long distances is typically difficult and may
even be impossible during labor [2]. Those that do attempt to walk to a healthcare facility
for delivery, often deliver or die en route [2].
37
Even when facilities are in close proximity, rural healthcare clinics often lack the
necessary skilled healthcare providers, thus, putting women at risk of increased morbidity
and mortality during pregnancy [145]. The WHO estimates that two-thirds of the
countries in SSA have skilled healthcare worker shortages, with 20% to 60% of all
physicians trained in SSA working abroad [145]. According to the WHO, the lack of
qualified healthcare workers in SSA necessitates a 140% increase in the healthcare
workforce to make a positive change on health in the region [145]. Inequalities among
healthcare workers’ skill and quality of services are especially prominent in rural settings
where twice as many rural healthcare workers lack appropriate medical training
compared to urban healthcare workers [146].
Summary of the socioeconomic and cultural risk factors associated with access to care
during pregnancy in sub-Saharan Africa
In summary, a variety of socioeconomic and cultural risk factors are associated
with decreased access to care during pregnancy and labor in SSA. Women in SSA face a
variety of obstacles while trying to obtain adequate healthcare during pregnancy. Gender
inequalities and cultural acceptance of home deliveries are both common reasons women
delay seeking treatment at a healthcare facility [2, 23, 28, 147]. Costs associated with
healthcare utilization, as well as costs associated with transportation to healthcare
facilities, are deterrents to accessing healthcare during pregnancy in SSA [148]. Delays in
seeking treatment may result in women attempting to access healthcare facilities only
after life-threatening complications develop. Decreasing delays and increasing access to
38
emergency obstetric care, such as CS, is considered necessary to achieving Millennium
Development Goal 5 [12, 13].
The obstacles women face in trying to achieve adequate prenatal care rarely exist
in isolation and instead make a complex web of associations with healthcare utilization.
The third delay in Thaddeus and Maine’s model focuses on a woman questioning if the
healthcare facility can provide her with adequate care. One way of measuring adequate
care in developing countries is to look at a healthcare facility’s ability to perform
lifesaving obstetric measures if a complication arises [12, 13, 149]. This dissertation will
focus on one type of procedure, the Cesarean Section (CS) (Aims 3 – 6).
Cesarean section
As previously mentioned, one of the factors that influence a woman’s decision to
access healthcare is her perception of the healthcare facility’s ability to effectively treat
her (see Figure 2). CS is a medical procedure during which the baby is delivered through
a surgical incision in the mother’s abdomen and uterus [150]. In developing countries,
most CS are performed after an unexpected complication arises during delivery,
including deteriorating health of the mother or fetus, breech position of the baby, or
obstructed labor [150].
According to the WHO, the optimal rate of use of CS as a lifesaving intervention
for women and neonates is between 5 and 15% [151-154]. Lower rates than this suggest
an overall lack of access to healthcare, while higher rates suggest an overutilization of
CS. High proportions of CS are a major public health concern because of increased
adverse maternal and perinatal outcomes associated with elective CS [151, 155]. In the
39
past decade, global rates of CS have been on the rise [154]; however, overutilization of
CS is really only a major concern in middle- to high- income countries. In contrast, in
developing countries consistently low rates of CS are reported; this is especially true
among rural and poor populations [149].
Most of the continent of Africa consistently reports underutilization of CS, with
regional estimates varying from 1.8% in Middle Africa, 1.9% in Western Africa, 2.3% in
Eastern Africa, and 7.6% in Northern Africa, to 14.5% in Southern Africa [152]. Low
percentages in middle, western and eastern Africa indicate difficulty accessing adequate
maternal healthcare. As previous mentioned, socioeconomic and cultural influences often
play a role in women not utilizing a healthcare facility during delivery in SSA. Gender
inequalities and cultural acceptance of home deliveries are also common reasons women
delay seeking treatment at a healthcare facility [2, 23, 28, 147]. Even if a woman can
overcome the first two types of delays (See Figure 2), she may still be faced with a
healthcare facility that does not have the means to provide her with adequate care.
Having a skilled birth attendant present during perinatal delivery has been shown
to save the lives of women and neonates [5]. This is in part a result of the skilled
healthcare professionals’ ability to recognize the symptoms that may necessitate a CS
[138]. However, even with a skilled birth attendant, there remain limitations in the
availability of CS in SSA hospitals, such as a lack of appropriate operating facilities or
surgical instruments [149, 156]. Doctors and nurses in SSA are often working without
electrical power, water, or medication [156]. A survey of 77 hospitals in SSA found only
6% reported the ability to provide safe anesthesia for a CS and only 19% operated in
facilities where electricity was always available [157]. A mere 56% of the facilities
40
reported always having access to running water, and 23% reported having access to blood
for transfusions [157]. Because of facilities’ lack of water, electricity, medication, and
equipment, operations—including CS— are often associated with unacceptably high rates
of sepsis, hemorrhage, and death [149]. However, CS may be beneficial if preexisting
medical conditions exist.
To prevent MTCT of HIV in resource unconstrained areas, evidence suggests that
having a CS is beneficial if a woman’s HIV-RNA level is above 1000 copies/ml near
delivery [38]. Because women in resource-constrained areas are often unaware of their
viral load before delivery, having a CS could be beneficial for HIV-infected women
[158]. However, in resource-constrained areas, CS are often unavailable and unsafe;
therefore, the WHO guidelines do not currently recommend HIV+ women in resource
constrained regions have an elective CS [159].
To the authors’ knowledge, no epidemiological studies have investigated the
relationship between malaria parasitemia and mode of delivery. Currently, only case
studies are discussed in the literature [16, 160, 161]. Therefore, the relationship between
malaria parasitemia and CS warranted further attention and was studied as part of this
dissertation.
The effects of anemia on mode of delivery have only recently been studied. As
hemoglobin levels decreased from anemic to severe anemic, the duration of labor
increased [162]. Increased time in labor is often associated with maternal and fetal
distress-which is an indicator of the need for CS [162]. However, studies assessing the
relationship between anemia and CS are conflicting with some studies showing an
association while others have not [162-165]. The conflicting nature of these studies offers
41
very little insight into a possible biological relationship between anemia and CS.
Furthermore, the wide variability of the underlying populations in each of these studies
makes comparability difficult.
One approach to decreasing maternal mortality and achieving Millennium
Development Goal 5 was to increase utilization of lifesaving obstetric measures such as
CS and decreasing common diseases associated with pregnancy [12, 13, 149]. This
dissertation will assess the rates of CS in Nigeria, a country with one of the world’s
fastest-growing populations and second in the proportion of global maternal deaths (Aims
3-6).
Nigeria
Nigeria is the most populous country in SSA with a population of over 173
million [166]. By 2100, approximately 25% of Africa’s population, or about 1 billion
people, will reside in Nigeria [167]. This rapid population growth is at least partially
attributable to Nigeria’s relatively high crude birth rate, at 38.03 births per 1,000 women
[1]. This translates to 6,458,000 births per year [168]. In order to achieve Millennium
Development Goals 5 and 6 globally, Nigeria needed to bring about major decreases in
maternal mortality, in part by increasing access to healthcare facilities during pregnancy
and reducing health conditions such as malaria and HIV.
In 2013, the maternal mortality ratio in Nigeria was 560 deaths per every 100,000
live births, a 52% decrease from 1990 [7]. Although this decrease in maternal mortality
ratio is a great improvement, in 2013 Nigeria still had the second largest proportion of
global maternal deaths at 14% (n=40,000) [7]. The lifetime risk of maternal death from a
42
pregnancy-related outcome in Nigeria is one of the highest in SSA at 1 in 29 [169]. This
is in part because of the high prevalence of diseases such as malaria and HIV in Nigeria.
The burden of malaria in Nigeria strains an already fragile healthcare system, with
nearly 110 million clinical cases occurring a year, accounting for up to 60% of outpatient
visits and 30% of hospital admissions [170]. Approximately 97% of the Nigerian
population lives in malaria endemic areas, making exposure to malaria during pregnancy
a common occurrence [171]. Despite the WHO recommendation that all pregnant women
in malaria endemic areas receive IPTp-SP to improve birth outcomes [50, 172], during
2010–2012 Nigeria had one of the lowest proportions of pregnant women receiving IPTpSP for malaria with only 20% of pregnant women in Nigeria receiving one dose of IPTpSP, and less than 5% receiving four doses [50, 172]. In addition, only 33.7% of pregnant
women slept under an ITN [170, 173]. Because of the lack of proper treatment and
utilization of preventative measures, malaria contributes to an estimated 11% of all
maternal mortality within Nigeria [171].
Nigeria also has one of the highest numbers of HIV+ individuals, with 3.2 million
prevalent cases and 220,000 incident cases of HIV in 2013 [174]. Of particular concern in
Nigeria is the high prevalence of HIV among women of childbearing age [175]. In 2012,
only 30.1% (n=57,871) of HIV+ pregnant women were receiving antiretroviral treatment
to reduce the risk of MTCT [175]. Although this is almost double the proportion reported
in 2011, it is still well below the levels needed to reach the Millennium Development
Goal of halting the spread of HIV [175]. Furthermore, the Joint United Nations
Programme on HIV and AIDS showed that Nigeria is not on target to reach their goal of
43
eliminating new HIV infections among children, with only a 2.0% decline in three years,
making it one of the slowest declines in SSA [176].
Most studies assessing mode of delivery in Nigeria focus on having a doctor
present at delivery. Although having a doctor present at delivery is essential to
recognizing symptoms associated with the need to have a CS, it may not correlate with
his/her ability to perform a CS if fetal or maternal distress occurs. A study in Nigeria
demonstrated only 1 in 21 health facilities were equipped to perform CS [138].
Therefore, even when women are utilizing healthcare facilities to deliver, this may not
translate to access to a CS. Costs associated with healthcare utilization, as well as costs
associated with transportation to healthcare facilities, are deterrents to accessing
healthcare during pregnancy in Nigeria [148]. Some Nigerian women report that the
financial burden of obstetric care is associated with a bad omen for the family; therefore,
they may fail to seek seeking treatment at a healthcare facility even when complications
during labor arise [148].
In order to decrease the burden of diseases during pregnancy, women must access
a healthcare facility while pregnant. However, socioeconomic and demographic variables
are often associated with an individual’s ability and willingness to access healthcare
facilities. Rates of CS in Nigeria vary according to an individual’s socioeconomic status,
with the richest women having better access to CS compared to the poorest women, as
measured by the wealth index—a composite measure of household goods and living
standards often used for research in developing countries [153]. Education and age are
also a strong predictors of a woman’s willingness to have a CS in Nigeria with younger
and/or less educated women being more likely to refuse a CS even when it is medically
44
necessary [14, 15]. Culture also plays a substantial role in a Nigerian woman’s decision
to have a CS. Symphysiotomy—a procedure used during obstructed labor that involves
cutting through the cartilage and ligaments of the pelvic joint, or surgically expanding the
pelvis, to allow a baby to be delivered vaginally—was preferred by two-thirds of
Nigerian women [28]. Symphysiotomy was preferred over a CS because of the fears
associated with having the latter procedure [28].
Low access to CS, coupled with high rates of comorbid medical conditions and
low socioeconomic and cultural perceptions of healthcare facilities, are all factors that
contribute to Nigeria having the second largest proportion of maternal deaths globally
[7]. Therefore, women may ultimately attempt to access healthcare facilities only after
life-threatening complications develop. These delays result in approximately 75% of all
CS in Nigeria being linked to obstetric emergencies that could have been prevented by
earlier medical interventions [147]. In order to achieve Millennium Development Goals 5
and 6, Nigeria needs to increase access to emergency obstetric services, such as access to
CS, and decrease common diseases experienced during pregnancy such as malaria and
HIV [149, 177].
Summary of the Introduction
The United Nations’ Millennium Development Goals were ambitious, requiring
improvements to basic humanitarian rights, including improved access to water, food,
and healthcare, especially in areas of the world with extensive poverty such as SSA
[178]. Countries within SSA present a unique opportunity to explore the progress that has
been made in achieving these goals because of their historically high rates of infectious
45
diseases and infant and maternal mortality [178]. Evaluating the progress towards
achieving these goals is essential as new goals are developed. Of particular interest to this
dissertation are the indicators of progress toward achieving Millennium Development
Goals 5 and 6 in Nigeria. Millennium Development Goal 5 focuses on reducing maternal
mortality, while Goal 6 aims to reduce infectious diseases. Nigeria contributes to the
second largest proportion of the global number of maternal deaths, making access to
healthcare facilities—and safe emergency obstetric services within these facilities—a
priority [7]. Nigeria also has one of the highest populations of HIV+ individuals globally,
as well as the highest number of malaria cases and deaths [174, 179]. Therefore, within
SSA, Nigeria is a key location for assessment of both the medical and socioeconomic
associations related to pregnancy complications.
46
CHAPTER 2
METHODS
Introduction
The methods, results and discussion of this dissertation are presented in this
chapter. The three manuscripts developed based upon the six specific aims are presented
in detail in Appendices A – C. Secondary analyses of two preexisting datasets were
employed. Two distinct methodologies were used to complete three unique studies. The
first methodology employed was a secondary analysis of a randomized control trial: The
Healthy Beginnings Initiative (HBI). This randomized, controlled trial was designed to
investigate the effectiveness of congregational vs. clinic-based HIV testing to PMTCT of
HIV. This dissertation used data collected as part of a trial to assess peripheral malaria
parasitemia, mode of delivery, and socioeconomic and demographic information. The
second methodology also employed a primary data source: The Demographic and Health
Survey (DHS). The DHS utilizes a cross-sectional survey design to attain countryspecific results worldwide. Each survey collects information on socioeconomic and
health related variables. The DHS is an open-source dataset that is available to any
researcher; the work conducted herein included results from the Nigeria DHS dataset.
The results will be presented in Chapter 3 followed by a discussion in Chapter 4.
47
METHODS: Healthy Beginnings Initiative
Overview
Aims 1-4 utilized data from the HBI. For Aim 1, malaria parasitemia levels were
established for pregnant women in Enugu State, Nigeria. For Aim 2, person-level
maternal risk factors that were associated with high malaria parasitemia were
investigated. For Aim 3, the incidence of CS among pregnant women in the HBI was
established; and for Aim 4, the socioeconomic and medical risk factors associated with
having a CS were studied. The Methods and Results for Aims 1-4 will be described in
detail in the following section; the results will be presented in Chapter 3 followed by the
Discussion in Chapter 4.
Population
The Healthy Beginnings Initiative (HBI) cohort consisted of self-identified
pregnant women [180]. Pregnant women were encouraged to participate in the study even
when their male partner was unavailable or choose not to participate. Because of inherent
risks associated with having a multiple birth, only singleton deliveries were retained for
this dissertation. In total, 3002 women were recruited into the HBI cohort. Although the
HBI cohort dataset was utilized to carry out Aims 1-4, two distinct outcome measures
were utilized. Therefore, the total number of participants for Aims 1 and 2 differ from
Aims 3 and 4 (see Figures 3 and 4).
The outcome variable for Aims 1 and 2 was malaria parasitemia levels of
pregnant women. As previously mentioned, 3002 women were recruited in the HBI, but
information on malaria parasitemia was available for 2100 women (see Figure 3). Only
singleton deliveries of women aged 17-45 were included in this analysis, therefore an
48
additional 31 women were excluded. The total study population for Aim 1 was 2069
women. The dataset for Aim 2 included 1970 women; 99 women were excluded because
they were missing one or more of the following variables: gravidity, area of residence,
distance to nearest healthcare facility or household size (see Figure 3).
Figure 3: Flow chart representing the women included in Aims 1 and 2
The outcome variable for Aims 3 and 4 was mode of delivery: CS or vaginal
delivery. As previously stated, 3002 women were recruited for the HBI. However, 648
lacked information on mode of delivery and an additional 37 women were pregnant with
49
multiples and, therefore, excluded (see Figure 3). In total, Aim 3 included information on
a total of 2317 pregnant women. For Aim 4, an additional 648 women were excluded
because they were missing one or more of the following variables: gravidity, area of
residence, distance to nearest healthcare facility, or household size-leaving the total
sample size for Aim 4 at 1669 women (see Figure 4).
Figure 4: Flow chart representing the women included in Aims 3 and 4
50
Recruitment
Data for Aims 1 – 4 were obtained from the Healthy Beginnings Initiative (HBI)
cohort [151]. Recruitment first occurred at the level of the church, then the participant
level. Bishops overseeing the churches were first approached by the research team [151].
Permission for the study team to speak with each priest under the corresponding Bishop’s
diocese was granted by the Bishops. All priests agreed to allow recruitment within their
corresponding congregation. Recruitment occurred in 40 churches from four dioceses
(the Anglican diocese of Enugu, the Catholic diocese of Enugu, the Anglican diocese of
Oji-River, and the Catholic diocese of Agwu) in Enugu State, Nigeria [151]. This area of
Nigeria’s population is more than 95% Christian [151]. Recruitment from churches was
expected to provide a representative sample of pregnant woman in Enugu State, Nigeria,
as church attendance approaches 90% in the country [180, 181].
Church-based volunteer health advisors (VHAs) who could read and write in
English and Ibo were selected from each participating church and trained on basic
research methodology, including how to obtain informed consent and complete the
study’s survey instruments. In total, 144 mostly female VHA were recruited and trained
to administer the consent and survey [182]. The average age of the VHA was 30 years
old and each VHA had a minimum of a high school education [182].
Each Sunday, priests asked pregnant women and their male partners to come to
the altar so the priest could perform a prayer that included encouraging women to seek
care at a healthcare facility, for the woman to have healthy pregnancy, and for successful
delivery of her fetus. He then introduced the HBI study as a program that supported
51
pregnant women during their pregnancy [151]. Women were given information on the
study and, if interested, were asked to read and sign a written consent form. The VHA
reported that the majority of participants were unable to read the local language (Ibo) and
preferred to have the study material in English (exact count unknown). For participants
who could not read, a VHA or a research assistant read the consent form aloud in English
or Ibo; the participants gave their consent by affixing thumb prints or using initials.
Survey
A structured questionnaire was implemented at a 6th grade reading level (See
Appendix D and E) [9]. Trained research staff and VHA administered the survey.
Demographic and family structure information was utilized for this dissertation,
including gravidity, area of residence, distance to the nearest healthcare facility, and
household size. Other survey questions and laboratory measures not discussed in this
dissertation included contraceptive use, general health questionnaire, and information
about the male partner. All survey questions can be found in Appendices D and E. Postdelivery questionnaires were used to ascertain the mode of delivery, i.e., CS or vaginal
birth, and the infant’s gender.
Laboratory Measures
Variables assessed by laboratory tests were malaria parasitemia, hemoglobin,
human immunodeficiency virus (HIV), and sickle cell disease/trait (SCD). Participants
were tested for each laboratory measure either at baseline following recruitment into the
study or during their prenatal visits, whereupon records were obtained from participant’s
52
corresponding hospital. Aims 1 and 2 employed the data on malaria. Aims 3 and 4
utilized information on hemoglobin, malaria, HIV, and sickle cell disease. All laboratory
procedures utilized in Aims 1-4 can be found in Appendix F.
Peripheral parasitemia levels were assessed using the malaria plus system [183].
Thick blood smears were examined via oil immersion under microscopy [183]. Each
slide was carefully read by two experienced laboratory technicians; a third technician was
utilized to rectify any discordant results. To ensure further quality control, random slide
checks were made by a hospital review panel. The malaria plus system was scored as
follows: 0 for no parasites, + for 1–10 parasites per 100 high power field, ++ for 11–100
parasites per 100 high power field, +++ for 1–10 parasites per high power field, ++++ for
over 10 parasites per high power field. Thus, levels of parasitemia increase as the scoring
moves from 0 through ++++. For these analyses malaria parasitemia was dichotomized as
high and low based on the malaria plus system. Those in the 0 and + group were
classified as low parasitemia; while those in the ++ and +++ groups were classified as
high parasitemia. No participants showed malaria parasitemia consistent with the ++++
group.
The following paragraphs will explain the laboratory measures exclusively used
in Aims 3 and 4. Hemoglobin was assessed using the standard cyanmethemoglobin
method [106]. Drabkins solution (Ranjo Medix Laboratories, Lagos, Nigeria) with a pH
of 7–7.4 was measured at 5 ml and dispensed into a glass test tube. Whole blood was
pipetted into the Drabkins solution and allowed to sit at room temperature away from
sunlight for 5 minutes. The Drabkins fluid was then read using 540 nm in a
spectrophotometer to estimate the hemoglobin concentration. WHO guidelines for
53
anemia were employed [107], and pregnant woman were classified as anemic if they had
a hemoglobin level below 11g/dl.
HIV testing was performed using the Rapid Testing Serial Algorithm II [184]. For
this procedure, two concurrent HIV rapid tests, Uni-Gold Recombigen (Uni-Gold; Trinity
Biotech, Inc., Wicklow, Ireland) and Stat Pak (Chembio Diagnostic Systems Inc.,
Medford, New York, USA) were used. Both Uni-Gold and Stat Pak are single-use
immunochromatographic tests that detect HIV antibodies. Uni-Gold is used for the
detection of HIV-1; while Stat Pack can detect HIV – 1 and 2. Both tests are performed
by collecting whole blood from a finger stick that is placed on a test strip. Next, the test
strip was placed in the testing device and a wash solution unique to each test, was added.
Uni-Gold was set aside for 10–12 minutes and then read by a technician; Stat-Pak was
read after 15–20 minutes. If both tests were positive for HIV, the individual was
considered HIV+; if both tests were negative, the individual was considered HIV
negative. When the tests showed conflicting results, they were both repeated and the
results were read by another technician, who did not know the results of the first series of
tests. Uni-Gold has demonstrated high sensitivity (98.5%), specificity (99.5%), positive
predictive value (<99%) and negative predictive value (<99%%) in sub-Saharan African
populations [185, 186]. Stat-Pak has also demonstrated high sensitivity (99.7%),
specificity (96.9%), and negative predictive value (99.8%), but lower positive predictive
value (94.6%) in sub-Saharan African populations[187].
EDTA-treated venous blood samples were used to screen for SCD. Cellulose
acetate electrophoresis at pH 8.5 – 9.0 was used. Hemolysates were prepared by lysing
saline-washed, packed red cells in 13mM EDTA, 10.7mM KCN solution using a 1:4
54
ratio. Tris-EDTA-borate buffer with cellulose acetate strips were used to perform
electrophoresis. Each strip contained one microliter of a patient hemolysate and a
microliter of a control hemolysate containing hemoglobin A, S, and C. Electrophoresis
was performed at a constant power of 350V for 30 minutes or longer if maximum band
separation was not observed. Each strip’s band separations were compared to the control
genotypes: AA, AS, SS, and SC. To decrease the chances of a false positive or negative of
SCD, each sample was tested twice. If incongruent results occurred, the test was rerun.
Statistical Analysis
Two unique statistical analysis plans were utilized to complete Aims 1 and 2 and
Aims 3 and 4. The outcome variable for Aims 1 and 2 was malaria parasitemia. The
outcome variable for Aims 2 and 3 was delivery via. CS vs. vaginal delivery.
For Aims 1 and 2, gravidity was dichotomized as > 2 or < 2 previous pregnancies.
Associations between malaria parasitemia and continuous variables were determined
using ANOVA. Pearson's Chi-square test was used to examine associations of malaria
with categorical and dichotomous variables. Crude and adjusted logistic regression
models were used to determine the association between participant characteristics and
malaria parasitemia levels. Statistical significance was set at p<0.05. Data analyses were
conducted using Stata version 12.0 [Stata Corporation, College Station, TX].
For Aims 3 and 4, univariate analyses were based on Pearson's Chi-square test
for comparison of proportions for all variables. Fisher's exact tests for contingency tables
were used to test for significance in proportions when the expected cell counts were less
than 5. Chi-square analyses with p<0.10 were further analyzed using crude and adjusted
55
logistic regression with CS as the main outcome. Having a CS in previous pregnancies is
known to predict current CS; therefore, gravida was included in logistic regression
models. Because no information on previous CS was collected, a sensitivity analysis was
performed including only those experiencing their first pregnancy. Statistical significance
was set at p<0.05. An adjusted trend in the odds ratio (OR), using the “tabodds” function
in Stata [Stata Corporation, College Station, TX], to determine whether the odds of
having a CS increased with participants’ age and education. Participant’s age was
categorized as 15–24, 25–34, and 35–45. Only one women who had a CS had no formal
education; therefore, education was categorized as none/primary, secondary and tertiary
and above. Age and education were retained as categorical variables for inclusion in
multivariable models. Birthweight was collected as part of the parent study; however,
because it was self-reported and most newborns were not weighed at birth, birthweight
was not deemed reliable. Therefore, birthweight was not included in this analysis. A
second sensitivity analysis was done to compare those who did not complete a follow-up
interview with those who did complete a follow-up interview. Data analyses were
conducted using Stata version 12.0.
Ethics Review
The parent study was approved by the Institutional Review Board of the
University of Nevada, Reno, and the Nigerian National Health Research Ethics
Committee. This secondary analysis was considered exempt from human subjects review
by the Mel and Enid Zuckerman College of Public Health Research Office.
56
METHODS: Demographic and Health Survey
Overview
To address Aims 5 and 6 secondary analyses of The Nigerian Demographic and
Health Survey were performed. Individual sampling weights were utilized as provided
by the DHS to make the distribution of the data representative of all Nigeria. A weighted
analysis was conducted among participants from this cross-sectional study. For Aim 5,
the incidence of CS among pregnant women in Nigeria was estimated. In Aim 6, the
association between socioeconomic and/or medical risk factors and mode of delivery
within Nigeria was evaluated. The sample was restricted to singleton deliveries because
of the risks inherent to having multiple births. A sensitivity analysis was performed
among primigravida women. The Methods for each Specific Aim will be described in
detail in the following section; the Results and Discussion will follow in Chapters 3 and
4.
Population
The Nigerian DHS covered the entire population of non-institutional dwelling
units [188]. The 2013, households were selected as survey sites (n=40,680). In total,
38,904 households were occupied at the time of the field staff’s arrival. Of these 38,522
households were successfully interviewed yielding a response rate 99% [188]. Of
particular interest to this dissertation are responses from women on the individual survey.
Figure 5 illustrates the recruitment chain for women in the Nigerian DHS survey.
In total, 39,902 women were interviewed, of which 38,948 (97.6%) completed the full
57
interview. A large number of women were either nulliparous or did not provide
information on the mode of delivery of their last child; therefore, they were excluded
from this analysis (n=18,885). Only singleton deliveries were included in the present
study. Therefore, the dataset for Aim 5 included a total of 19,655 women aged 15–49
years for whom information on the mode of delivery (vaginal vs. CS) of their most recent
singleton pregnancy was available. For Aim 6, an additional 1,733 women were excluded
from the analyses because they were missing one or more of the following variables:
mother’s age, area of residence, mother’s education, religion, wealth index, difficulty
accessing a healthcare facility, health insurance, prenatal care provider, anti-malarial, past
CS, iron supplementation for at least half of pregnancy, or region of residence (see Figure
5). In total, Aim 6 included 17,932 women.
58
Figure 5: Flow chart representing the women included in Aims 5 and 6
Recruitment
The data for this analysis were obtained from the DHS conducted in Nigeria in
2013. The sampling frame used for Nigeria’s survey was prepared using the 2006
Population Census data from the Federal Republic of Nigeria provided by the National
Population Commission [188]. A total of five DHS have been conducted to date in
Nigeria in the following years: 1990, 1999, 2003, 2008 and 2013. The United States
59
Agency for International Development (USAID), the United Nations Population Fund
(UNFPA), the United Kingdom Department for International Development (DFID)
(through the Partnership for Transforming Health Systems Phase II), and the government
of Nigeria, provided the resources necessary to conduct the survey [188]. A
technical/quality assurance team was utilized for the administration and collection of the
survey. The team was headed by a project director/coordinator. Other members of the
team included 18 state coordinators who were in charge of recruiting and training the
field staff, monitoring the fieldwork, and assisting in any other project-related activities
[188]. All field staff received a four-week-long training course from January to February
2013 [188].
Field staffs were divided up into six geographical zones: north east, north central,
north west, south east, south central and south west [188]. Within these six zones, a total
of 37 interview teams were created, with one for each of the 36 states and one for the
Federal Capital Territory. Household interviews were conducted from February through
June 2013. Eight areas faced security difficulties; therefore, the survey was not completed
in these regions (four in Borno, two in Yobe, one in Nasarawa, and one in Plateau).
Survey
The DHS utilized a cross-sectional design to obtain nationally representative data
[189]. The DHS was designed to provide up-to-date information on fertility levels,
marriage, awareness and use of family planning methods, child feeding practices,
nutritional status of women and children, adult and childhood mortality, awareness and
attitudes about HIV/AIDS, and domestic violence [189]. In 2013, three questionnaires
60
were utilized to this obtain information: the Household Questionnaire, the Woman’s
Questionnaire, and the Man’s Questionnaire. The results reported here are form the
individual Woman’s Questionnaire [189]. The Women’s Questionnaire contains items on
the following topics: background characteristics, reproductive behavior and intentions,
contraception, antenatal, delivery and postnatal care, breastfeeding and nutrition,
children’s health, status of women, HIV and other sexually transmitted infections,
husband’s background and other topics related to environmental health, tobacco use and
health insurance. The DHS only collects information on any pregnancy-related outcomes
only in the five years prior to the survey.
Statistical Analysis
Because select populations were oversampled, individual sampling weights
provided by DHS were used as recommended [190]. Using weights allowed for
adjustment for nonresponse to questions, and made the data representative of the
underlying population on a national level. All data management and analyses were
conducted in STATA version 12.0 [Stata Corporation, College Station, TX] using the
‘svyset’ command. The outcome variable used for this analysis was whether the most
recent birth was reported as a CS or a vaginal delivery. A skilled birth attendant was
defined using the WHO as an accredited health professional including a doctor, nurse, or
midwife [191]. Otherwise, the attendant was classified as a non-skilled birth attendant.
Weighted univariate analyses utilized Pearson's Chi-square test for comparison of
proportions for all variables. Weighted crude and adjusted logistic regression with mode
of delivery, either vaginal or CS, as the main outcome was performed. Weighted
61
percentages were also performed for reasons why women did not deliver at a healthcare
facility. A sensitivity analysis was performed among those experiencing their first
pregnancy (n=3,596). Statistical significance of all tests are presented at p<0.05.
Ethics Review
All protocols and survey measures are submitted for review to ensure the
protection of human subjects. Nigeria’s protocols for each survey were approved by the
ICF International Institutional Review Board as a within country IRB board [192].
Survey data were collected by trained personnel, with participants verbally consenting at
the beginning of the interview [189]. This secondary analysis was considered exempt
from human subjects review by the Mel and Enid Zuckerman College of Public Health
Research Office.
62
CHAPTER 3
RESULTS
The results of this dissertation are summarized by the outcome variable that
corresponds to each Aim. Because Aims 1 and 2 have the same outcome variable
(peripheral malaria parasitemia levels), they are reported together under the same results
subheading. Aims 3 and 4, and 5 and 6 utilize different dataset. Therefore, the results for
Aims 3 and 4 will be presented apart from Aims 5 and 6 even though the outcome
variable, mode of delivery, is the same both studies. The Discussion for each Aim can be
found in Chapter 4 of this dissertation.
Results: Malaria Parasitemia in Pregnancy (Aims 1 and 2)
Malaria parasitemia levels were recorded for 2,069 pregnant women. Over 99%
of the women in the study tested positive for malaria parasitemia (n=2,052). Categorized
according to the malaria plus system, malaria parasitemia in our sample included: < 1%
in the no infection group (n=17); 62% in the + group (n=1275); 36% in the ++ group
(n=737); 2% in the +++group (n=40); with none categorized in the ++++ group (n=0)
(see Table 1). A total of 1,292 (62%) and 777 (38%) women were categorized as lowand high- parasitemia, respectively.
63
Table 1: Malaria parasitemia frequency by the Malaria Plus System
N(%)
Malaria Plus System
0
17 (<1)
+
1275 (62)
++
737 (36)
+++
40 (2)
++++
0 (0)
Total
2069 (100)
Notes: Levels of parasitemia increase as the
scoring moves from 0 through ++++
As shown in Table 2, no significant differences were found between high and low
malaria parasitemia and gravidity, area of residence, distance to nearest healthcare
facility, household size, or age of participants.
Table 2: Comparison of participant's characteristics by malaria parasitemia low vs. high
Parasitemia
Low
High
Total
P*
Number of Participants, N(%)
1292(62)
777(38)
2069(100)
Gravidity, N(%)
Primi/secundigravida
819(65.8)
486(65.9)
1305(65.5)
0.67
Multigravida
425(34.2)
263(35.1)
688(34.5)
Residence, N(%)
Urban
326(25.3)
189(24.1)
513(24.9)
0.54
Rural
960(74.7)
588(75.9)
1,548(75.1)
Distance to Healthcare Facility, N(%)
0-5(km)
464(36.1)
255(33.0)
719(34.9)
0.17
5-10(km)
487(37.9)
290(37.5)
777(37.8)
10+(km)
334(26.0)
228(29.5)
576(27.3)
Household size, Mean (SD)a
4.51(2.0)
4.36(1.9)
4.40(1.9)
0.07
29.10(5.8)
28.90(5.8)
Notes: Numbers may not add up to 2086 due to missing data.
29.00(5.7)
0.44
b
Age (Years), Mean (SD)
a
b
:
N for each category include n=1282 low parasitemia; n=768 high parasitemia; total n=2050
No missing data
*Significance based on Chi-square p-value < 0.05
64
Table 3 shows the results of logistic regression analysis of the association
between participant characteristics and malaria parasitemia. After controlling for
confounding variables, odds for high parasitemia were lower among those who had more
people in the household (For every one person increase in a household, OR=0.94, 95%
CI: 0.89–0.99).
65
Table 3: Logistic regression models for malaria parasitemia and participant level
characteristics
Crude model
Adjusteda
N
OR(95% CI)
OR(95% CI)
1305
Ref.
Ref.
Gravidity
Multigravida
Primi/secundigravida 688
1.04 (0.86-1.26) 0.93 (0.75-1.16)
Urban
513
Ref.
Rural
1548
1.07 (0.87-1.31) 1.07 (0.86-1.32)
0-5(km)
719
Ref.
5-10(km)
777
1.08 (0.88-1.34) 1.08 (0.87-1.34)
10+(km)
562
1.24 (0.99-1.56) 1.23 (0.98-1.56)
2050
0.96 (0.91-1.00) 0.94 (0.89-0.99)b
Residence
Ref.
Distance to Healthcare Facility
Ref.
Household size
Notes: a Overall model n=1970
b
Indicates significance at p<0.05
Results: Cesarean section in Enugu State, Nigeria (Aims 3 and 4)
As shown in Table 4, 167 (7.2%) women had CS and 2,150 (92.8%) had vaginal
deliveries. A woman’s age was statistically significantly associated with having a CS
(p<0.01), with a greater percentage of women aged 35–45 having had a CS (11.1%) than
66
women aged 25–34 (7.5%) or 15–24 (3.2%). Education was statistically significantly
associated with having a CS (p<0.01), with a greater percentage of women with tertiary
education having had a CS (15.1%) than those with a secondary education (6.0%) or a
primary education or less (4.9%). Employment status was also significantly associated
with having a CS (p=0.03); women with full-time employment had higher percentages of
CS than women who worked part time or who did not indicate they were currently
employed (8.7%, 5.0, and 7.1%, respectively). Area of residence (i.e., rural vs urban),
was significantly related to having a CS (p<0.01) with more women in urban settings
having a CS (12.2%) compared to women in rural settings (5.5%). A mother’s baseline
malaria parasitemia was significantly associated with having a CS (p=0.02); higher
percentages of women who had high malaria parasitemia at baseline had a CS than
women who displayed low levels of malaria parasitemia (8.9% vs 6.0%, respectively).
Infant’s gender was statistically associated with CS (p=0.01), with a higher rate of CS
occurring when mothers delivered male (8.6%) than female infants (5.9%). No significant
relationship was observed between CS and number of people in the household, gravidity,
distance to nearest healthcare facility, marital status, HIV, sickle cell disease (SCD), or
anemia. When analyses were restricted to women who had not had a prior pregnancy
(n=334), 7.8% (n=26) had CS and 92.2% (n=308) had vaginal deliveries (Table 4).
Among primigravida women, living in an urban environment was significantly related to
having a CS (p<0.01) with 14.3% of urban women having a CS compared to only 5.1%
of rural women. No other participant characteristics were significant predictors of having
a CS among primigravida women.
67
Table 4: Comparison of participant baseline characteristics and infant gender with mode
of delivery
C-Section
N
%
167
7.2
Total
Mother's Age
15-24 16
3.2
25-34 107
7.5
35-45 44
11.1
Education
None /Primary 30
4.9
Secondary 79
6
Tertiary 58
15.1
Employment Status
Full-time 74
8.7
Part-time 28
5
None 61
7.1
Residence
Urban 73
12.2
Rural 94
5.5
Malaria Parasitemia
High 59
8.9
Low 66
6
Infant’s Gender
Male 102
8.6
Female 64
5.9
Number of People in Household
1-2 31
3-4 75
5+ 60
8.7
8.2
5.8
Full Sample
Vaginal
N
%
2150
92.8
C-Section
N
%
26
7.8
P*
Primigravida
Vaginal
N
%
308
92.2
479
1317
354
96.8
92.5
88.9
<0.01 a* 9
15
2
5.8 146
9.3 147
11.8 15
94.2
90.7
88.2
0.34 a
578
1241
327
95.1
94
84.9
<0.01 a* 3
11
12
6
47
5.5 188
14.1 73
94
94.5
85.9
0.053 a
781
536
818
91.4
95
93.1
0.03 a*
6
6
14
5.8
9.4
8.5
97
58
150
94.2
90.6
91.5
0.64
528
1617
87.9
94.5
<0.01
14
12
14.3 84
5.1 224
85.7
94.9
<0.01*
604
1027
91.1
94
0.02 a*
5
14
5.3
8.3
90
155
94.7
91.7
0.36
1085
1028
91.4
94.1
0.01 a*
13
13
7.8
7.8
153
152
92.2
92.2
0.99
324
845
967
91.3
91.9
94.2
0.07
14
11
1
7.5 174
11.6 84
2.1 46
92.6
88.4
97.9
0.15
N/A
N/A
N/A
95
91.6
0.59 a
91.9
90.8
93.3
0.88
100
92.6
1.0 a
90.6
93.4
0.55 a
92.8
92.8
0.99
a*
Gravity
N/A
N/A N/A
Primigravida 26
7.8 308
92.2
0.62
N/A
N/A N/A
Multigravida 136
7
1797
93
Marital Status
3
5
Married 162
7.5 2010
92.5
0.07
57
23
8.4
Other 5
3.4 140
96.6
251
Distance to Healthcare Facility
9
8.1 102
0-5km 54
9.7 753
93.3
0.52
10
8.5 108
5-10km 61
7
817
93.1
7
6.7 97
10+km 51
8.2 872
91.8
HIV status
0
0
Positive 2
3.3 59
96.7
0.32
8
21
7.4 263
Negative 137
7.2 1757
92.8
Sickle Cell Status
5
9.4 48
AA-normal 100
7.3 1273
92.7
0.62
14
6.6 197
AS/AC-carrier 25
6.5 357
93.5
Anemia
7
7.2 90
Yes 53
8.3 589
91.7
0.16
12
7.2 155
No 72
6.5 1042
93.5
Notes: *Significance based on Pearson's Chi-square for Fisher's Exact, p<0.05 significant
a
P*
Indicates p-value based on Fishers Exact
a
68
Table 5 presents the crude and adjusted odds ratios (95% CIs) for having had a
CS or a vaginal birth by participant characteristics. The adjusted models showed that,
compared to women aged 15–24, the odds of having a CS were higher when the mother
was aged 25–34 years (adjusted OR (aOR): 2.01; 95% CI: 1.04–3.90) and when the
mother was aged 35–45 years (aOR: 2.73; 1.26–5.92; p-trend <0.01). Compared to those
with a primary school education or less, the odds of having a CS were higher if the
mother had at least a tertiary education (aOR: 2.91; 1.54–5.53), but not if she had a
secondary education (aOR: 1.27; 0.73–2.30; p-trend <0.01). The odds of having a CS
were significantly lower if participants were employed part-time compared to full-time
(aOR: 0.56; 0.32–0.97). Compared to women who lived in an urban setting, those who
lived in a rural setting had a significant reduction in the odds of having a CS (aOR: 0.58;
0.38–0.89). Significantly higher odds of having a CS were found among those with high
peripheral malaria parasitemia compared to those with low parasitemia (aOR: 1.53; 1.03–
2.27). After adjustment for confounders, no relationship was found between CS and
number of people in the household, gravidity, marital status and not being employed.
Among primigravida women, adjusted logistic regression models showed a significant
relationship between woman living in an urban vs rural environment and having a CS
(aOR: 0.27; 0.09–0.82). No other significant relationships were found among
primigravida women between having a CS and a woman’s baseline characteristics or the
gender of her infant.
69
Table 5: Crude and logistic regression models of the odds of C-Section vs vaginal birth
Full Sample
Among Primigravida
Crude
Adjusted
Crude
Adjusted
N=1669
N=256
Mother's Age
15-24 Ref
Ref
Ref
Ref
25-34 2.43(1.42-4.16)* 2.01(1.04-3.90)* 1.65(0.70-3.90) 0.85(0.23-3.10)
35-45 3.72(2.07-6.70)* 2.73(1.26-5.92)* 2.16(0.43-10.95) 1.54(0.22-10.75)
Education
None/Primary Ref
Ref
Ref
Ref
Secondary 1.22(0.80-1.89) 1.27(0.73-2.30) 0.92(0.25-3.42) 0.57(0.13-2.58)
Tertiary 3.42(2.15-5.42)* 2.91(1.54-5.53)* 2.58(0.69-9.61) 0.89(0.16-4.86)
Employment Status
Full-time Ref
Ref
Ref
Ref
Part-time 0.55(0.35-0.86)* 0.56(0.32-0.97)* 1.67(0.52-5.43) 1.72(0.43-6.85)
None 0.79(0.55-1.12) 0.80(0.52-1.25) 1.51(0.56-4.06) 1.42(0.42-4.87)
Residence
Urban Ref
Ref
Ref
Ref
Rural 0.42(0.30-0.58)* 0.58(0.38-0.89)* 0.32(0.14-0.72)* 0.27(0.09-0.82)*
Malaria Parasitemia
Low Ref
Ref
Ref
Ref
High 1.52(1.05-2.19)* 1.53(1.03-2.27)* 0.62(0.21-1.76) 0.67(0.22-2.06)
Infants Gender
Female Ref
Ref
Ref
Ref
Male 1.51(1.09-2.09)* 1.18(0.80-1.75) 0.99(0.45-2.21) 0.86(0.32-2.32)
Number of People in Household
1-2 Ref
Ref
Ref
Ref
3-4 0.93(0.60-1.43) 0.94(0.49-1.79) 1.63(0.71-3.74) 1.38(0.49-3.87)
5+ 0.65(0.41-1.02) 0.58(0.29-1.16) 0.27(0.03-2.11) 0.37(0.04-3.14)
Gravidity
Multigravida Ref
Ref
N/A
N/A
Primigravida 1.15(0.72-1.73) 1.03(0.55-1.96) N/A
N/A
Marital Status
Married Ref
Ref
Ref
Ref
Other 0.44(0.18-1.10) 0.93(0.32-2.71) 0.57(0.17-1.98) 0.67(0.12-3.61)
Notes: Models adjusted for other variables in the table
* Indicates significance at p<0.05
70
Table 6 shows the results of the sensitivity analysis exploring the characteristics
of participants who were lost to follow-up with those who completed the follow-up
survey. In total, 685 (n=23%) participants did not complete the follow-up survey. There
was a statistically significant relationship between completion of the follow-up interview,
when mode of delivery was assessed, and the following participant’s baseline
characteristics: mother’s age (p=0.04), employment status (p<0.01), area of residence
(p<0.01), number of people in the household (p=0.01), gravidity (p=0.03), and anemia
(p=0.03). A greater proportion of women aged 15-24 (24.4%) were lost to follow-up than
those aged 25-34 (19.7%) and those 35-45 (20.1%). A greater proportion of unemployed
women were lost to follow-up than those who worked part-time or full-time (25.7%,
14.6%, and 19.5%, respectively). In urban areas, more women were lost to follow-up
compared to rural areas (28.7% and 19.5%, respectively). As the number of people in the
household increased, fewer women were lost to follow-up. More anemic women were
lost to follow up than those who were not-anemic (16.9% vs 13.4%, respectively).
71
Table 6: Sensitivity analysis of participants who completed the follow-up
interview compared to those who were not present at the follow-up interview
Follow-up
No Follow-up
N
%
N
% p-value
Mother's Age
15-24
503
75.6
162
24.4
0.04
25-34
1439
80.3
354
19.7
35-45
401
79.9
101
20.1
Education
None /Primary
617
79.3
161
20.7
0.29
Secondary
1341
79.3
350
20.7
Tertiary
390
76.2
122
23.8
Employment Status
Full-time
869
80.5
211
19.5
0.00
Part-time
573
85.4
98
14.6
None
891
74.3
308
25.7
Residence
Urban
611
74.3
211
28.7
0.00
Rural
1736
80.5
420
19.5
Malaria Parasitemia
High
677
86.2
108
13.8
0.34
Low
1114
84.7
201
15.3
Number of People in Household
1-2
364
75.1
121
24.9
0.01
3-4
929
78.4
256
21.6
5+
1043
81.2
241
18.8
Gravity
Primigravida
338
84.3
63
15.7
0.03
Multigravida
1959
79.7
499
20.3
Marital Status
Married
2208
78.6
601
21.4
0.33
Other
146
75.7
47
24.3
Distance to Healthcare Facility
0-5km
819
80.7
196
19.3
0.24
5-10km
893
77.7
256
22.3
10+km
631
79.0
168
21.0
HIV status
Positive
63
92.7
5
7.4
0.13
Negative
1928
86.2
309
13.8
Sickle Cell Status
AA-normal
1400
85.1
246
14.9
0.45
AS/AC-carrier
390
86.5
61
13.5
Anemia
Yes
660
83.1
134
16.9
0.03
No
1131
86.6
175
13.4
72
Results: Cesarean section in Nigeria (Aims 5 and 6)
The results of the weighted chi-square are reported in Table 7. During their last
pregnancy, 2.3% of women had a CS and 97.7% had a vaginal delivery in Nigeria during
2008-2013. A statistically significant relationship between having a CS and mother’s age
was demonstrated (p<0.01), with higher percentages of women aged 34–49 having had a
CS (2.7%) compared to women aged 25–34 (2.4%) and 15–24 (1.6%). Area of residence
was significantly associated with having a CS (p<0.01), with more women in urban areas
having a CS (4.4%) than women in rural settings (1.1%). Education was a significantly
associated with having a CS (p<0.01), with women with a tertiary education or higher
having higher percentages of a CS (11.1%) compared to those with secondary, primary or
no formal education (3.6%, 2.0%, and 0.5% respectively). Religion was also a significant
factor in having a CS (p<0.01), with more Catholics having a CS (4.9%) compared to
Muslim (1.0%) or non-Catholic Christians (4.3%). Wealth index was also significantly
associated with having a CS (p<0.01); as wealth index increased so too did rates of CS,
with the poorest of women having the lowest percent of CS (0.5%) and the richest
women having the highest percentages of CS (7.2%). Difficulty accessing a healthcare
facility was also significantly associated with having a CS (p<0.01), with women who
reported no difficulty in accessing a healthcare facility having higher percentages of a CS
(2.8%) compared to women who reported difficulty accessing a healthcare facility
(1.1%). Having health insurance was significantly associated with having a CS (p<0.01);
those with health insurance displayed significantly higher percentages of having a CS
(11.7%) compared to those with no insurance (2.1%). Also, demonstrated was a
73
significant relationship betweentype of prenatal care provider and having a CS (p<0.01),
with women who obtained prenatal care from a skilled birth attendant having higher
percentages of CS (3.6%) than those who obtained prenatal care from an unskilled birth
attendant (0.9%) or did not receive prenatal care (0.4%). Having a skilled birth attendant
was also a significantly related to having a CS (p<0.01), with higher percentages in
women who had a skilled birth attendant present during delivery (16.1%) than those who
delivered with an unskilled birth attendant (0.6%). A significant relationship was
demonstrated between having a CS if a woman took anti-malaria medication (p<0.01),
with higher proportions of CS demonstrated among women who took anti-malaria
medication (3.3%), compared to those who did not (1.3%). Being offered an HIV test as
part of prenatal care was significantly related to having CS (p<0.01), with higher
proportions of CS among women who were offered HIV testing as part of prenatal care
(5.2%) compared to those who were not offered HIV testing as part of prenatal care
(1.5%). Lower percentages of CS were found among those who took iron
supplementation for at least half of their pregnancy (1.7%) compared to those who did
not take iron supplementation for at least half of their pregnancy (2.7%; chi-square
p<0.01). Having a CS during a previous pregnancy was also significantly associated with
current CS (p<0.01) with more women having a current CS if they had a previous CS
(50.9%) compared to those who did not (0.07%). The geographical area in which a
woman lives was also related to having a CS (p<0.01), with women in northern regions
having lower percentages of CS compared to women living in the southern regions of
Nigeria. No significant association between the gender of the infant and having a CS
were demonstrated (p=0.22).
74
Table 7: Weighted chi-square of the socio-economic and medical factors associated with mode of delivery
Full sample
Primigravida
Vaginal Cesarean
P
Vaginal Cesarean
N
%
%
N
%
%
Total sample
19665
97.7
2.3
3596
95.6
4.4
Age
15-24 5095
98.4
1.6 <0.01* 2521
97.3
2.6
25-34 9197
97.6
2.4
1000
92.3
7.7
34-49 5373
97.3
2.7
75
78.6
2.1
Area of Residence
Urban 6532
95.6
4.4 <0.01* 1324
92.3
7.7
Rural 13133
98.9
1.1
2272
97.7
2.3
Education
None 8997
99.5
0.5 <0.01* 1173
98.8
1.2
Primary 3989
98.0
2.0
519
97.4
2.6
Secondary 5379
96.4
3.6
1510
94.8
5.2
Higher 1300
88.9
11.1
394
85.8
14.3
Religion
Catholic 1602
95.1
4.9 <0.01*
360
90.2
9.5
Other Christian 6466
95.7
4.3
1431
93.5
6.5
Islam 11303
99.0
1.0
1770
98.0
2.0
Wealth index
Poorest 4308
99.5
0.5 <0.01*
587
98.9
1.1
Poorer 4513
99.1
0.9
762
97.2
2.8
Middle 3955
98.6
1.4
748
97.0
3.0
Richer 3668
97.6
2.4
740
96.7
3.4
Richest 3221
92.9
7.2
759
89.5
10.5
Difficulty accessing a healthcare facility
No 13327
97.2
2.8 <0.01* 2533
94.7
5.3
Yes 6259
98.9
1.1
1048
98.1
1.9
Infant's Gender
Male 9966
97.6
2.4 0.2159 1825
94.7
5.3
Female 9699
97.9
2.1
1771
96.6
3.4
Health Insurance
No 19235
97.9
2.1 <0.01* 3505
96.0
4.0
Yes 354
88.3
11.7
77
73.0
27.0
Prenatal Care Provider
No Prenatal Care 6496
99.6
0.4 <0.01*
954
99.2
0.8
Unskilled birth attendant 1710
99.1
0.9
291
98.6
1.4
Skilled birth attendant 11299
96.4
3.6
2335
93.6
6.4
P
<0.01*
<0.01*
<0.01*
<0.01*
<0.01*
<0.01*
0.02
<0.01*
<0.01*
75
Continued Table 7: Weighted chi-square of the socio-economic and medical factors associated with mode of delivery
Full sample
Primigravida
Vaginal Cesarean
P
Vaginal Cesarean
P
N
%
%
N
%
%
Delivered by:
Unskilled birth attendant 17601
99.3
0.6 <0.01* 3069
98.8
1.2 <0.01*
Skilled birth attendant 1974
83.9
16.1
513
77.6
22.4
Took Anti-Malaria Medication
No 9797
98.7
1.3 <0.01* 1674
97.6
2.4 <0.01*
Yes 9463
96.7
3.3
1851
93.9
6.1
Intestinal Parasite Medication
No 16015
97.9
2.1
0.04* 2888
95.9
4.1
0.2
Yes 2922
97.1
2.9
571
94.5
5.5
Offered HIV Test as part of Prenatal Care
No 5709
98.5
1.5 <0.01* 1028
96.9
3.1 <0.01*
Yes 6477
94.8
5.2
1429
91.5
8.5
Past CS
No 19548
99.3
0.07 <0.01* N/A
N/A
N/A
N/A
Yes 117
49.1
50.9
N/A
N/A
N/A
Iron Supplementation for at Least Half of Pregnancy
No 10081
97.3
2.7 <0.01* 1971
97.6
2.4 <0.01*
Yes 8650
98.3
1.7
1452
93.9
6.1
Region
North Central 3027
97.5
2.5 <0.01*
601
94.8
5.2 <0.01*
North East 3946
98.9
1.1
613
98.2
1.8
North West 6088
99.4
0.6
898
98.6
1.4
South East 1669
96.0
4.0
377
92.9
7.2
South Central 2436
95.4
4.6
570
92.9
7.1
South West 2499
95.0
5.0
537
92.2
7.8
Notes: *Significance based on weighted Chi-Square pvalue <0.05
Among primigravida women, 4.4% had a CS and 95.6% had a vaginal delivery.
Age was significantly related to having a CS (p<0.01), with higher percentages among
women 25–34 (7.7%) compared to those 15–24 (2.6%) and 34–49 (2.1%). Area of
residence was also significantly related to having a CS (p<0.01); with higher percentages
of CS occurring in urban areas (7.7%) compared to those in rural settings (2.3%).
Education was significantly related to having a CS (p<0.01); as education increased so
too did the percentage of women who had a CS (no education 1.2%; primary school
education 2.6%, secondary 5.2% and tertiary or higher 14.3%). Religion was also
significantly related to having a CS with higher percentages in Catholics (9.5%)
76
compared to other Christian denominations (6.5%) and Muslim (2.0%). Wealth index
was significantly related to having a CS (p<0.01). As wealth index increased so too did
the percent of women who had a CS (poorest 1.1%, poorer 2.8%, middle 3.0%, richer
3.4% and richest 10.5%). Expressing difficulty accessing a healthcare facility was also
significantly associated with having a CS (p<0.01); with a higher percent of CS occurring
among those who did not have difficulty accessing a healthcare facility (5.3%) compared
to those who had difficulty accessing a healthcare facility (1.9%). Infants gender was
significantly related to having a CS (p<0.01) with more women having a CS if they were
pregnant with a male infant (5.3%) than a female infant (3.4%). Health insurance was
also significantly related to having a CS (p<0.01); with more women having a CS if they
had health insurance (27%) compared to those without health insurance (4%). The type of
prenatal care provider was significantly associated to having a CS (p<0.01). Of the
women who received prenatal care from a skilled birth attendant, 6.4% had a CS
compared to 1.4% of those who attended an unskilled birth attendant for prenatal care
and 0.8% who did not receive any type of prenatal care. Results demonstrated a
significant relationship between type of provider present at delivery, skilled vs unskilled,
and having a CS (p<0.01). Primigravida women who delivered with a skilled birth
attendant had higher percentages of CS (22.4%) compared to women who delivered with
an unskilled birth attendant (1.2%). Taking anti-malaria medication during pregnancy
was also significantly associated with having a CS (p<0.01) with more women having a
CS if they also took anti-malaria medication (6.1%) as opposed to women who did not
take anti-malaria medication (2.4%). Among those who partook in prenatal care, a
significant association between being offered HIV testing and having a CS was
77
demonstrated (p<0.01). More women who were offered HIV testing as part of prenatal
care had a CS (8.5%) compared to those who were not offered an HIV test as part of
prenatal care (3.1%). A significant association was also demonstrated between taking
iron supplementation for at least half of pregnancy and having a CS (p<0.01). Women
who took iron supplementation for at least half or pregnancy had higher percentages of a
CS (6.1%) than those who did not take iron supplementation for at least half or pregnancy
(2.4%). The geographical area in which a woman lives was also related to having a CS
(p<0.01), with women in northern regions having lower percentages of CS compared to
women living in the southern regions of Nigeria.
Table 8 presents results from the weighted crude and adjusted odds ratios (95%
CIs) for mode of delivery by participant characteristics. In the full sample, including both
multigravida and primigravida births, the adjusted model demonstrated that compared to
women who live in urban areas, the odds of having a CS were lower if the women lived
in a rural setting (adjusted OR [aOR] 0.67: 95% 0.51–0.93). Compared to those with a no
education, the odds of having a CS were higher if the mother had at least a tertiary
education (aOR 2.71: 1.58–4.63) but not if she had a primary or secondary education
(aOR1.20: 0.76–1.90 and 1.54: 0.98–2.42 respectively). Compared to women who
practice Catholicism, lower odds of having a CS were demonstrated if the woman was
Muslim (aOR 0.46: 0.28–0.73). Women who had health insurance had higher odds of
having a CS compared to those without insurance (aOR 1.78: 1.18–2.67). Women who
received prenatal care from a skilled birth attendant had higher odds of having a CS
compared to women who did not received prenatal care (aOR 3.00: 1.51–5.96). Also,
women who had a CS during previous pregnancies had higher odds of having a CS
78
during their current pregnancy compared to women who had a previous vaginal delivery
(aOR 28.97:15.31–4.81). Compared to women in North Central Nigeria, women in the
North West had lower odds of having a CS (aOR 0.56:0.32–0.97). In the adjusted model,
no relationship was found between CS and taking prophylaxis malaria medication and
iron supplementation. Among primigravida women, compared to women who practice
Catholicism, lower odds of having a CS were demonstrated if the woman was Muslim or
an alternative form of Christianity (aOR 0.54: 0.30–0.98 and aOR 0.43: 0.19–0.96
respectively). Compared to those with no health insurance, those with health insurance
had higher odds of having a CS (aOR 4.11: 1.97–8.54). In the adjusted models, no other
significant relationships were demonstrated.
79
Table 8: Weighted logistic regression the socio-economic factors associated with mode of delivery
Full Sample
Primigravida
Unadjusted
Adjusted
Unadjusted
Adjusted
N=17932
n=3580
Age
15-24 Ref.
Ref.
Ref.
Ref.
25-34 1.53 (1.59-2.03)* 0.85 (0.61-1.18)
3.03 (2.04-4.52)* 1.26 (0.74- 2.16)
34-49 1.69 (1.23-2.32)* 1.08 (0.76-1.54)
9.95 (4.86-20.36)*4.24(1.78-10.14)*
Area of Residence
Urban Ref.
Rural 0.25(0.19-0.33)*
Ref.
0.67 (0.51-0.93)*
Ref.
Ref.
0.28 (0.20-0.42)* 0.55 (0.32-0.94)*
Ref.
1.20 (0.76-1.90)
1.54 (0.98-2.42)
2.71 (1.58-4.63)*
Ref.
Ref.
2.18 (0.96-4.94) 0.67 (0.27-1.69)
4.40 (2.47-7.83)* 1.15 (0.50-2.63)
13.38 (7.19-24.90)*
1.54 (0.61-3.84)
Ref.
0.80 (0.55-1.16)
0.46 (0.28-0.73)*
Ref.
Ref.
0.66 (0.39-1.12) 0.54 (0.30-0.98)*
0.19 (0.11-0.33)* 0.43 (0.19-0.96)*
Ref.
0.83 (0.44-1.53)
0.76 (0.42-1.39)
0.87 (0.46-1.65)
1.50 (0.77-3.90)
Ref.
Ref.
2.50 (0.98-6.38) 1.37 (0.50-3.75)
2.77 (1.09-7.01)* 0.76 (0.26-2.19)
3.08 (1.23-7.72)* 0.55 (0.17-1.74)
10.34 (4.45-24.16)*
0.87 (0.25-3.04)
Ref.
0.90 (0.62-1.30)
Ref.
Ref.
0.35 (0.20-0.60)* 0.66 (0.37-1.18)
Ref.
1.78 (1.18-2.67)*
Ref.
Ref.
8.95 (4.77-16.80)*4.11(1.97-8.54)*
Prenatal Care Provider
No Prenatal Care Ref.
Ref.
Unskilled birth attendant 2.51(1.25-5.03)*
1.35 (0.59-3.08)
Skilled birth attendant 10.45 (6.26-17.44)* 3.00 (1.51-5.96)*
Ref.
Ref.
1.72 (0.56-5.28)* 0.72 (0.18-2.93)
8.53 (3.59-20.29)*2.93 (0.96-8.90)
Education
None Ref.
Primary 3.79 (2.50-5.73)*
Secondary 7.06 (4.96-10.06)*
Higher 23.63(16.0-34.81)*
Religion
Catholic Ref.
Other Christian 0.88 (0.64-1.20)
Islam 0.19 (0.13-0.27)*
Wealth index
Poorest Ref.
Poorer 1.77 (0.98-3.19)
Middle 2.73 (1.54-4.83)*
Richer 4.58 (2.65-7.94)*
Richest 14.5 (8.66-24.13)*
Difficulty accessing a healthcare facility
No Ref.
Yes 0.37 (0.27-0.51)*
Health Insurance
No Ref.
Yes 6.12 (1.29-8.73)*
80
Continued Table 8: Weighted logistic regression the socio-economic factors associated with mode of delivery
Full Sample
Primigravida
Unadjusted
Adjusted
Unadjusted
Adjusted
N=17932
n=3580
Took Anti-Malaria Medication
No Ref.
Ref.
Ref.
Ref.
Yes 2.49 (1.91-3.24)* 1.28 (0.96-1.70)
2.65 (0.79-3.92) 1.41 (0.94-2.13)
Past CS
No Ref.
Ref.
N/A
Yes 51.20 (32.00-91.90)*28.97 (15.31-54.81)* N/A
Iron Supplementation for at Least Half of Pregnancy
No Ref.
Ref.
Yes 0.64 (0.49-0.83)* 1.20 (0.89-1.63)
N/A
N/A
Ref.
Ref.
0.67 (0.44-1.04) 1.07(0.68-1.68)
Region
North Central Ref.
Ref.
North East 0.45 (0.28-0.73)* 0.90 (0.54-1.50)
North West 0.25 (0.15-0.42)* 0.56 (0.32-0.97)*
South East 1.65 (1.11-2.44)* 0.78 (0.50-1.23)
South Central 1.89 (1.19-3.00)* 1.03 (0.67-1.59)
South West 2.07 (1.42-3.03)* 0.95 (0.65-1.37)
Notes: *Significance based on weighted logistic regression p <0.05
Ref.
0.34 (0.17-0.69)*
0.25 (0.22-0.52)*
1.40 (0.79-2.50)
1.39 (0.79-2.42)
0.54 (0.90-2.66)
Ref.
0.68 (0.29-1.64)
0.58 (0.26-1.30)
0.71 (0.35-1.44)
1.21 (0.65-2.27)
0.92(0.51-1.67)
Table 9 demonstrates the cultural beliefs and barriers that influenced women’s
ability to access a healthcare facility during delivery in Nigeria. Overall, 11,954 (67%)
women did not deliver at a healthcare facility. Cultural beliefs influenced many women’s
decision not to deliver at a healthcare facility; with 34.5% of women reporting that it was
not necessary to deliver at a healthcare facility; 8.1% stating that their husband’s family
did not allow them to access healthcare; 9.3% reporting it is not customary to deliver at a
healthcare facility; 1.4% reporting distrust of the healthcare facility; 0.5% reporting that
no female provider was available at the healthcare facility; and 0.2% reporting the they
did not like the attitude of the healthcare professional at the health facility. Physical and
financial barriers that influenced a woman’s ability to deliver at a healthcare facility
81
included: delivering too quickly (39.2%); inadequate transportation (15.5%); and costs
associated with delivering at a healthcare facility (9.3%). Among primigravida women,
1,760 (49%) did not deliver at a healthcare facility (Table 8). Cultural beliefs and
physical barriers were associated with accessing a healthcare facility in primigravida
women in a similar manner to the full sample.
Table 9: Weighted percents of reasons why women did not healthcare facility to deliver
Full sample (n=11954) Primigravida (n=1760)
Yes
No
Yes
No
Not Necessary
34.5
65.5
30.1
69.1
Husbands family didn't allow
8.1
91.9
8.8
91.2
Not Customary
9.3
90.7
7.3
92.8
Delivered too quickly
39.2
60.8
40.4
59.7
Transportation
15.5
84.5
16.8
83.2
Cost
9.3
90.7
10.2
89.8
Facility Not Open
2.3
97.7
3.0
97.0
Distrust of healthcare facility
1.4
98.6
1.2
98.8
No female provider
0.5
99.5
0.7
99.3
Attitude of healthcare professional
0.2
99.8
0.1
99.9
82
Tables 10 and 11 show the reasons women did not deliver at a healthcare facility,
stratified by area of residence. Both tables demonstrate that women living in rural areas
endorsed both cultural and physical barriers at a greater proportion that those living in
urban areas with the exception of women delivering too quickly.
Table 10: Weighted percents of reasons why women did not deliver at a healthcare
facility stratified by area of resdience
Rural
Urban
Full sample (n=9729) Full sample (n=2225)
Yes
No
Yes
No
Not Necessary
35.6
64.4
30.1
69.9
Husbands family didn't allow
Not Customary
8.6
10.0
91.4
90.0
6.0
94.0
6.6
93.4
Delivered too quickly
36.5
63.5
49.6
50.4
Transportation
17.3
82.7
8.4
91.6
Cost
9.4
90.6
8.2
90.8
Facility Not Open
2.6
97.4
1.2
98.8
Distrust of healthcare facility
1.0
99.0
3.1
96.9
No female provider
0.6
99.4
0.4
99.6
Attitude of healthcare professional
0.1
99.9
0.7
99.3
83
Table 11: Among primigravida women, weighted percents of reasons why
women did not deliver at a healthcare facility stratified by area of
residence
Rural
Urban
Primigravida
(n=1461)
Primigravida
(n=299)
Yes
No
Yes
No
Not Necessary
32.7
67.3
22.7
77.3
Husbands family didn't allow
9.2
90.8
7.1
92.9
Not Customary
8.1
91.9
3.4
96.6
Delivered too quickly
36.7
63.3
57.0
43.0
Transportation
18.0
92.0
11.2
88.8
Cost
10.4
89.6
9.1
90.9
Facility Not Open
3.3
96.7
1.6
98.4
Distrust of healthcare facility
0.8
99.2
2.7
97.3
No female provider
0.7
99.3
0.6
99.4
Attitude of healthcare
professional
9.2
90.8
7.1
92.9
84
Comparison of Cesarean Section Results Across Samples
Because of the uniqueness of both datasets, different variables were included in
the models used to explore the socioeconomic and medical risk factors associated with
having CS (see Tables 12 and 13). However, both models included mother’s age, area of
residence and education levels. In the full sample, crude models demonstrated similar
results between the HBI and the DHS for mother’s age, area of residence, and education.
As mother’s age and education level increased so did her odds of having a CS. Women
living in rural settings had a decrease in the odds of having a CS compared to those living
in urban locations. This relationship was maintained in the adjusted model for area of
residence and education but not for mother’s age. In the HBI, adjusted model
demonstrated an increase in the odds of having a CS as a woman aged. This relationship
was not demonstrated in the DHS dataset. In the crude model of the HBI cohort, infant’s
gender was associated with having a CS with males having higher odds of being born via
CS than females. This variable was not included in DHS analysis because this
relationship was not found in the original chi-square (see Table 7).
Primigravida women displayed similar results to the full sample. Both samples
demonstrated statistically significant lower odds of having a CS among women living in
rural settings compared to those living in urban settings. Although the crude models of
HBI were not significant, they showed a similar pattern to DHS in that as age and
education increased, so too did the odds of having a CS. Sample size differences between
HBI and DHS dataset likely explain this difference in the statistical significance in results
between these analyses.
85
Because of the independent nature of the studies, numerous study variables did
not overlap between the HBI and DHS dataset, including: religion, wealth index,
difficulty accessing a healthcare facility, health insurance, prenatal care provider, malaria
parasitemia, iron supplementation, region, and employment status. Wealth index was not
included as part of HBI; therefore, marital status was utilized as an attempt to control for
wealth index. Likewise, past CS was not included in the HBI but was included in the
DHS. Because having a CS in previous pregnancies is known to predict current CS,
gravida and number of people in the household were included in the HBI as an attempt to
control for past CS. Malaria parasitemia was included in the HBI. The DHS did not have
information on malaria parasitemia and instead had information on whether the women
took an anti-malarial during pregnancy. It is unknown if women were taking anti-malarial
medication as part of preventative treatment or because they had symptoms associated
with malaria. Therefore, a comparison of these two variables is difficult. Two variables
included in the DHS, religion and region, were used as inclusion criteria for the HBI
cohort. The HBI recruited women based on their religious affiliation with the majority of
women recruited being Catholic. The DHS demonstrated lower odds of having a CS
among Muslim women compared to Catholic. Women in HBI reported similar rates of
CS to Catholic women in the DHS (Full sample: 7% vs 5%; Primigravida: 8% vs 9%,
respectively).
86
Table 12: Comparison of the logistic regression models for Aim 4 and Aim 6 among the full sample
Enugu State, Nigeria (HBI)
All Nigeria (DHS)
Adjusted
Adjusted
N=1669
N=17932
Mother's Age
Mother's Age
15-24 Ref.
15-24 Ref.
25-34 2.01(1.04-3.90)*
25-34 0.85 (0.61-1.18)
35-45 2.73(1.26-5.92)*
35-49 1.08 (0.76-1.54)
Area of Residence
Area of Residence
Urban Ref.
Rural 0.58(0.38-0.89)*
Education
Urban Ref.
Rural 0.67 (0.51-0.93)*
Education
None Ref.
Primary 1.20 (0.76-1.90)
Secondary 1.54 (0.98-2.42)
Higher 2.71 (1.58-4.63)*
None/Primary Ref.
Secondary 1.27(0.73-2.30)
Higher 2.91(1.54-5.53)*
Religion
Religion
Catholic N/A
Other Christian N/A
Islam N/A
Marital Status
Catholic Ref.
Other Christian 0.80 (0.55-1.16)
Islam 0.46 (0.28-0.73)*
Wealth index
Other 0.93(0.32-2.71)
Married Ref.
Poorest Ref.
Poorer 0.83 (0.44-1.53)
Middle 0.76 (0.42-1.39)
Richer 0.87 (0.46-1.65)
Richest 1.50 (0.77-3.90)
Difficulty Accessing a Healthcare Facility
No N/A
Yes N/A
Difficulty Accessing a Healthcare Facility
No Ref.
Yes 0.90 (0.62-1.30)
Health Insurance
Health Insurance
No N/A
Yes N/A
No Ref.
Yes 1.78 (1.18-2.67)*
Prenatal Care Provider
No Prenatal Care N/A
Unskilled birth attendant N/A
Skilled birth attendant N/A
Prenatal Care Provider
No Prenatal Care Ref.
Unskilled birth attendant 1.35 (0.59-3.08)
Skilled birth attendant 3.00 (1.51-5.96)*
87
Continued Table12: Comparison of the logistic regression models for Aim 4 and Aim 6 among the full sample
Enugu State, Nigeria (HBI)
All Nigeria (DHS)
Adjusted
Adjusted
N=1669
N=17932
Malaria Parasitemia
High 1.53(1.03-2.27)*
Low Ref
Gravidity
Took Anti-Malaria Medication
No Ref.
Yes 1.28 (0.96-1.70)
Past CS
Primigravida 1.03(0.55-1.96)
Multigravida Ref.
No Ref.
Yes 28.97 (15.31-54.81)*
Iron Supplementation for at Least Half of Pregnancy Iron Supplementation for at Least Half of Pregnancy
No N/A
No Ref.
Yes N/A
Yes 1.20 (0.89-1.63)
Region
Region
North Central N/A
North East N/A
North West N/A
South East N/A
South Central N/A
South West N/A
Infant Gender
North Central Ref.
North East 0.90 (0.54-1.50)
North West 0.56 (0.32-0.97)*
South East 0.78 (0.50-1.23)
South Central 1.03 (0.67-1.59)
South West 0.95 (0.65-1.37)
Infant Gender
Male 1.18(0.80-1.75)
Female Ref.
Male N/S
Female N/S
Number of People in Household
1-2 Ref.
3-4 0.94(0.49-1.79)
5+ 0.58(0.29-1.16)
Number of People in Household
1-2 N/I
3-4 N/I
5+ N/I
Employment status
Employment status
Full-time Ref.
Full-time N/A
Part-time 0.56(0.32-0.97)*
Part-time N/A
None 0.80(0.52-1.25)
None N/A
Notes: *Significance based on weighted logistic regression pvalue <0.05
N/A=not available in dataset; N/S=not significant based on Pearson's chi-square or Fisher's exact therefore not
included in logistic regression; N/I=not included-variable was used in Aim 4 to control for previous C-section
88
Table 13 : Comparison of the logistic regression models for Aim 4 and Aim 6 among primigravida women
Enugu State, Nigeria (HBI)
All Nigera (DHS)
Adjusted
Adjusted
N=256
N=3580
Mother's Age
Mother's Age
15-24 Ref.
15-24 Ref.
25-34 0.85(0.23-3.10)
25-34 1.26 (0.74- 2.16)
35-45 1.54(0.22-10.75)
34-49 4.24(1.78-10.14)*
Area of Residence
Urban Ref.
Rural 0.27(0.09-0.82)*
Education
Area of Residence
Urban Ref.
Rural 0.55 (0.32-0.94)*
Education
None Ref.
Primary 0.67 (0.27-1.69)
Secondary 1.15 (0.50-2.63)
Higher 1.54 (0.61-3.84)
None/Primary Ref.
Secondary 0.57(0.13-2.58)
Higher 0.89(0.16-4.86)
Religion
Religion
Catholic N/A
Other Christian N/A
Islam N/A
Marital Status
Catholic Ref.
Other Christian 0.54 (0.30-0.98)*
Islam 0.43 (0.19-0.96)*
Wealth index
Other 0.67(0.12-3.61)
Married Ref.
Poorest Ref.
Poorer 1.37 (0.50-3.75)
Middle 0.76 (0.26-2.19)
Richer 0.55 (0.17-1.74)
Richest 0.87 (0.25-3.04)
Difficulty Accessing a Healthcare Facility
No N/A
Yes N/A
Difficulty Accessing a Healthcare Facility
No Ref.
Yes 0.66 (0.37-1.18)
Health Insurance
Health Insurance
No N/A
Yes N/A
No Ref.
Yes 4.11(1.97-8.54)*
Prenatal Care Provider
No Prenatal Care N/A
Unskilled birth attendant N/A
Skilled birth attendant N/A
Prenatal Care Provider
No Prenatal Care Ref.
Unskilled birth attendant 0.72 (0.18-2.93)
Skilled birth attendant 2.93 (0.96-8.90)
89
Continued Table 13: Comparison of the logistic regression models for Aim 4 and Aim 6 among primigravida women
Enugu State, Nigeria (HBI)
All Nigeria, (DHS)
Adjusted
Adjusted
N=256
N=3580
Malaria Parasitemia
High 0.67(0.22-2.06)
Low Ref
Took Anti-Malaria Medication
No Ref.
Yes 1.41 (0.94-2.13)
Iron Supplementation for at Least Half of Pregnancy
N/A
N/A
Iron Supplementation for at Least Half of Pregnancy
No Ref.
Yes 1.07(0.68-1.68)
Region
Region
North Central N/A
North East N/A
North West N/A
South East N/A
South Central N/A
South West N/A
Infant Gender
North Central Ref.
North East 0.68(0.29-1.64)
North West 0.58(0.26-1.30)
South East 0.71(0.35-1.44)
South Central 1.21(0.65-2.27)
South West 0.92(0.51-1.67)
Infant Gender
Male 0.86(0.32-2.32)
Female Ref.
Number of People in Household
1-2 Ref.
3-4 1.38(0.49-3.87)
5+ 0.37(0.04-3.14)
Male N/S
Female N/S
Number of People in Household
1-2 N/I
3-4 N/I
5+ N/I
Employment status
Employment status
Full-time Ref.
Full-time N/A
Part-time 1.72(0.43-6.85)
Part-time N/A
None 1.42(0.42-4.87)
None N/A
Notes: *Significance based on weighted logistic regression pvalue <0.05
N/A=not available in dataset; N/S=not significant based on Pearson's chi-square or Fisher's exact therefore not
included in logistic regression; N/I=not included-variable was used in Aim 4 to control for previous C-section
90
CHAPTER 4
DISCUSSION
In the following sections I will discuss each of the Specific Aims. Aims 1 and 2 of
this dissertation were designed to establish the prevalence of malaria parasitemia during
pregnancy and explore the person-level risk factors associated with malaria parasitemia
in the Enugu State, Nigeria. Aims 3-6 focused on estimating the incidence of CS among
pregnant women and determining the socioeconomic and medical risk factors associated
with having a CS in Nigeria. The HBI and DHS datasets were utilized to analyze these
Aims and develop three unique manuscripts. The results will be discussed in 3 separate
sections, and an overall discussion will follow.
Malaria Parasitemia in Pregnancy
This dissertation demonstrated that over 99% of pregnant women in Enugu State,
Nigeria showed at least low levels of malaria parasitemia, with 38% showing high levels
of malaria parasitemia. For each additional person in the household, pregnant women in
Enugu State had 6% lower odds of having high malaria parasitemia. Estimates presented
in this paper are consistent with hospital-based estimates of malaria in pregnant women
in the southeastern region of Nigeria [193]. With nearly 110 million clinical cases of
malaria occurring a year, this disease places a heavy burden on Nigeria’s already fragile
healthcare system and accounts for approximately 60% of outpatient visits and 30% of
hospital admissions [170]. Malaria is estimated to cost Nigeria $8.6 billion USD per year
in hospital care and lost wages [194].
91
In order to reach Millennium Development Goal 6, improved access to prenatal
care is needed [12, 13]. The Roll Back Malaria program recommends that pregnant
women receive intermittent preventative treatment with the inclusion of sulphadoxinepyrimethamine (IPTp-SP) as part of antenatal care, and recommends that pregnant
women sleep under insecticide-treated nets (ITN). Although Nigeria has adopted these
recommendations, with only 13.2% of pregnant women receiving IPTp-SP, and 33.7% of
pregnant women sleeping under an ITN, more work is required to achieve these goals
[170, 173]. Based on the high prevalence of malaria in this study, education about best
practices to prevent malaria during pregnancy and resources in support of these practices
are urgently needed. Increases in obstetric services during delivery are also needed; this
will be discussed further in the following two sections.
Cesarean section in Enugu State, Nigeria
Information presented in this part of the discussion was collected in Enugu State,
Nigeria, located in the southeastern part of Nigeria. Increasing access to emergency
obstetric care, including CS, decreases maternal and infant morbidity and mortality [12,
13]. However, women in SSA struggle to obtain adequate obstetric care during
pregnancy. Nigeria, one of the fastest growing populations in the world with a crude birth
rate of 38.03 births per 1,000 women, is a key location to study access to healthcare in
pregnancy [1]. This dissertation showed that 7.2% of women in Enugu State, Nigeria had
a CS, while 92.8% had a vaginal delivery. Compared to women who had full-time
positions, women who worked part-time had 44% lower odds of having a CS after
adjusting for potential confounders. Likewise, significantly lower odds of having a CS
92
was observed among women who lived in rural settings compared to those who resided in
urban settings. This was true for both the full sample and for the sample of primigravida
women. This dissertation demonstrated 53% higher odds of having a CS if participants
had high peripheral malaria parasitemia compared to those with lower peripheral malaria
parasitemia, after adjusting for potential confounding.
The present dissertation showed that utilization of CS increased with maternal age
and education, such that in older women and women with more education were more
likely to have had a CS. In SSA, education has been shown to be a strong predictor of
using professionally assisted delivery services [130, 137]. Older and more educated
women in SSA are considered more confident and influential in their household decisionmaking, including the use of healthcare services [130, 142]. Likewise, women with more
education or who are employed often have greater control over family resources and play
a larger part in reproductive decision-making [23, 142, 143]. Maternal age and education
may be proxies of a woman’s ability to access healthcare, thereby increasing her chances
of having had a CS.
The relationship between infant gender and having a CS has been welldocumented in developed countries, but has only recently been studied in Africa [195]. In
Libya, male fetuses were associated with higher odds of maternal diabetes mellitus,
preterm delivery, needing instruments when a vaginal delivery was performed, and
having CS compared to female fetuses [196]. In the present study, being pregnant with a
boy may have been associated with these pregnancy complications; however, sex was
unknown during gestation, as women in this part of Nigeria were unlikely to have an
ultrasound to determine the gender of their infants. Therefore, the finding of the current
93
work that male infants were associated with a higher odds of CS suggests that the
relationship between CS and male infants is biologically and not culturally based [196].
The biological basis of the relationship between being pregnant with a male fetus and
having a CS is unclear and warrants further attention in future research [196].
Although the analyses herein did not find an association between distance to
nearest health facility and having had a CS, a statically significant relationship was
demonstrated between living in rural vs urban environments and having had a CS. In
rural settings, distance has consistently been an important barrier to seeking healthcare [2,
4, 197]. It is possible that in this self-report data, area of residence (i.e., rural vs urban)
was an indirect assessment of the ease of reaching a healthcare facility for childbirth.
Like women in other rural areas, women living in rural parts of Enugu State, Nigeria may
have had difficulty accessing facilities that can perform a CS because of limited
transportation options, poor road conditions, and poverty [2, 4, 23]. In order to reach
Millennium Development Goal 5 by end of 2015, improved access to emergency
obstetric care, such as CS, is needed [12, 13].
The relationship between malaria parasitemia and the need for emergency
obstetric care has not been well established. To the authors’ knowledge, this dissertation
is the first epidemiological investigation to report that high malaria parasitemia is
associated with higher odds of CS; although there are some case studies [16, 160, 161]. A
biological pathway assessing the relationship between malaria parasitemia and the
increased need to have a CS has not been established; however, there is some evidence to
indicate that malaria parasitemia puts stress on the fetus. Malaria parasitemia is believed
to produce adverse fetal outcomes via systemic effects such as maternal anemia,[26, 64,
94
65] and local effects such as placental infection [65-68]. Maternal anemia decreases
erythropoiesis[30, 69] and increases red blood cell apoptosis[30, 70], ultimately leading
to a maternal hypoxic state. During this hypoxic state, impaired growth and
vascularization occur within the pregnant woman, which in turn can lead to fetal hypoxia
[71]. Decreased maternal vascularization leads to a reduction in the exchange of
important nutrients and gases across the placenta, including oxygen, which can also lead
to a fetal hypoxic state [66, 72, 73]. Due to fetal hypoxia and decreased nutrient uptake,
intrauterine growth retardation (IUGR) can occur [72]. Malaria infection is also thought
to disrupt cytokine activity, resulting in an increase in placental infection; this is
especially seen during the first or second pregnancy and can result in preterm infants with
IUGR [67, 68, 74-80]. The maternal hypoxia and inflammatory response often caused by
maternal malaria puts stress on the fetus and makes it difficult for the fetus to get the
nutrients needed to grow often leading to a preterm delivery of a LBW infant [63].
Therefore, an increased need to have a CS may be due to an increase in fetal stress caused
by high rates of malaria parasitemia. The relationship between malaria parasitemia and
CS warrants further attention.
The relationship between sickle cell disease (SCD) and CS also warrants further
attention. Some evidence has suggested that women with sickle cell disease (SCD) are
more likely to have a CS in SSA [198, 199]. However, because both SCD and CS are
related to high risk of adverse maternal and neonatal outcomes in SSA, it is difficult to
determine whether women with SCD would benefit from having a CS [199-201]. Also,
SCD and malaria are both associated with anemia during pregnancy [18, 30, 69, 202].
This further complicates the relationship between SCD and CS as anemia is related to an
95
increase in maternal morbidity and mortality in developing countries [114]. Also related
to an increase in maternal morbidity and mortality is HIV [36].
This dissertation is consistent with a meta-analysis that found HIV+ women were
no more likely to have a CS than those not infected [36]. Evidence from resourceunconstrained areas suggests that having a CS is beneficial if a woman’s HIV–RNA level
is above 1000 copies/ml near delivery [38]. However, women in resource-constrained
areas are often unaware of their viral load before delivery; thus, having a CS may or may
not be beneficial for HIV-infected women [158]. Nonetheless, in resource-constrained
areas, CS are often unavailable and unsafe; therefore, the WHO guidelines do not
currently recommend HIV+ women in resource constrained regions have an elective CS
[159]. Instead the WHO recommends that HIV+ women take 3 or more antiretroviral
medications in order to decrease mother-to-child transmission of HIV [93]. The WHO
also recommends that infants born to HIV+ mothers receive antiretrovirals during the
post-natal period [93].
The sensitivity analysis assessing the association between participant’s baseline
characteristics and being lost to follow-up demonstrated that testing positive for HIV did
not deter women from completing a follow-up questionnaire. As stigma related to HIV
testing has been demonstrated to deter women from partaking in HIV testing, it is
surprising that this dissertation did not demonstrate a statistically significant relationship
between HIV status and being lost to follow-up [203]. Women who were younger and
unemployed had higher proportions of being lost to follow-up than older and employed
women. This may occur because older and employed women in SSA may be more
influential in household decision-making, including whether to attend follow-up
96
interviews [23, 130, 142, 143]. A larger proportion of urban dwelling women were lost to
follow-up than those living in rural areas. This may be reflective of a difference in
consistent church attendance in rural vs. urban areas in SSA; however, this cannot be
confirmed in this dissertation, and remains understudied in the literature. Lastly, a larger
proportion of primigravida women were lost to follow-up than multigravida. Perhaps this
difference in being lost to follow-up reflects an adjustment to having a newborn child;
therefore primigravida women were less likely to attend church.
Information presented in this part of the discussion was collected in Enugu State,
Nigeria, located in the southeastern part of Nigeria. The following section will discuss
data obtained from the Nigerian Demographic and Health Survey, a cross-sectional study
conducted throughout Nigeria.
Cesarean Sections in Nigeria
Nigeria has the second highest maternal mortality ratio in the world, in part
because of barriers women encounter accessing adequate healthcare during pregnancy. In
order to reach Millennium Development Goal 5 by end of 2015, improved access to
emergency obstetric care—such as CS—needed to be provided [12, 13]. The aims for this
study were to estimate the incidence of CS in Nigeria and to determine the
socioeconomic, demographic, and medical risk factors associated with having a CS in
Nigeria. In the overall sample, including both multi- and primigravida births, only 2.3%
of women had a CS. Women living in rural areas had 33% lower odds of having a CS
compared to women living in urban areas. Religion was also significantly associated with
having had a CS; Muslim women (54%) had significantly lower odds of having a CS
97
compared to Catholic women. Women with health insurance had a 78% higher odds of
having a CS compared to women without health insurance; while those offered HIV
testing as part of prenatal care had a 96% increase in the odds of having a CS compared
to women who were not.
Lower frequencies of CS among women living in rural environments have
consistently been reported because of barriers to accessing treatment, such as limited
transportation options and poor road conditions [2, 4, 23, 197]. Poverty plays a
substantial role in a woman’s ability to access a healthcare facility during delivery. In
rural areas, costs associated with having a CS, as well as costs associated with
transportation are common reasons for not accessing a healthcare facilities during
delivery [2, 28, 147]. In this sample, approximately 10% of all women reported costs as a
deterrent to accessing a healthcare facility during delivery. Furthermore, 17.3% of rural
Nigerian women sampled indicated that they did not deliver at a healthcare facility
because of transportation difficulties, compared to less than 8.4% of urban women. It is
likely that women in rural settings do not actively choose to deliver outside of healthcare
facilities—thereby decreasing their rates of CS—but are instead forced to deliver outside
of healthcare facilities because of the barriers associated with living in a rural setting.
The present work also demonstrated higher odds of having a CS if women had a
tertiary education or more compared to those with no education. Although no relationship
was observed in the odds of having a secondary education or higher and having a CS,
increasing education in woman was an important step in achieving Millennium
Development Goal 5. Generally, as education increases, access to healthcare facilities
grows, and maternal mortality tends to decrease [2, 204, 205]. Women with more
98
education possess greater control over family resources and play a larger role in their
reproductive decision-making [23, 142, 143]. Karlsen et al., [205] demonstrated higher
maternal mortality among those with low education levels. This relationship persisted
even after controlling for potential confounders [205]. The importance of increasing
access to primary school education (Millennium Development Goal 2) and eliminating
gender inequalities in education (Millennium Development Goal 3) are both substantial
steps toward achieving Millennium Development Goal 5.
To improve healthcare, the Nigerian government implemented the National
Health Insurance Scheme in 1999 [206]. However, numerous studies have demonstrated
that Nigerians continue to rely on direct payment to finance their healthcare needs [207].
Less than 1% of women in this sample had health insurance. It is possible that those who
stated they had health insurance were more likely to have privately funded health
insurance and, therefore, possessed the ability to financially afford a CS even if the their
insurance did not cover all the associated costs.
Ethnic and cultural diversity in Nigeria often vary by geographical region [208].
The interconnectedness of geographical region and religion in Nigeria is difficult to tease
apart as the northern areas of Nigeria are predominately Muslim, while the middle and
southern regions are predominately Christian [208]. This dissertation demonstrated lower
odds of having a CS among Muslim women compared to Catholic women, and that
women in the northwestern part of Nigeria had lower odds of having had a CS compared
to the north-central area. This may be in part because of a lack of access to skilled health
providers in northern regions of Nigeria [23, 208]. Having a skilled birth attendant
available at delivery is necessary to perform a CS. Furthermore, previous research has
99
demonstrated that women living in northern parts of Nigeria have lower rates of prenatal
care and higher rates of home delivery [209]. With the percentage of home deliveries
ranging from 12% in southwest Nigeria to 86% in northwest Nigeria, women in northern
areas of Nigeria receive significantly less support from a skilled birth attendant than their
counterparts in southern Nigeria [209]. The vast majority of these women have friends or
relatives assisting with their delivery [209]. Cultural and religious norms may dictate this
relationship—as some women in northern areas have restrictions in seeking health-related
assistance during childbirth, especially from male providers [208]. Attaining the
Millennium Development Goals is especially difficult in the Northern parts of Nigeria
where poverty, illiteracy, and early marriage rates remain high among women, and
reproductive health and family planning are not historically women’s decisions [208].
Therefore, it is likely that women in the northern areas of Nigeria need better access to
reproductive health education and trained birth attendants and community health workers,
so the symptoms associated with potential obstetric complications can be detected before
infant and/or maternal mortality ensues.
It is well documented in the literature that skilled birth attendants are associated
with a decrease in maternal mortality [210]. This dissertation demonstrated that compared
to women who received no prenatal care, the odds of having a CS were increased if a
women received prenatal care from a skilled birth attendant. No significant relationship
was demonstrated between receiving prenatal care from an unskilled birth attendant and
having a CS. Additional research has indicated that traditional birth attendants can be
effective at implementing interventions that reduce neonatal mortality in rural areas [211214]. Further developing the skills of traditional births attendants and community health
100
workers in recognizing early warning signs of life threatening obstetric complications
could reduce maternal mortality in Nigeria, especially in Northern Nigeria.
Overall Discussion
The results of this dissertation indicate that Nigeria is not on target to achieve
Millennium Development Goals 5 or 6 by the end of 2015. First, this dissertation
demonstrated high rates of peripheral malaria parasitemia (>99%) in pregnant women
living in Enugu State, Nigeria (Aim 1). Previous reports estimated that malaria is
responsible for 11% of all maternal deaths within Nigeria [194]. Therefore, decreasing
malaria in Nigeria is essential to reducing its high rates of maternal mortality. Next, we
demonstrated that Nigeria has 2–3 times lower rates of CS than the WHO estimated is
needed within Nigeria to decrease maternal mortality (Aims 3 and 5) [154]. Therefore,
high rates of malaria parasitemia and low rates of CS are expected to continue to
contribute a large portion to Nigeria’s maternal mortality.
These results were consistent with previous research in Nigeria. Aim 1
demonstrated high rates of malaria parasitemia (>99%) during pregnancy in women from
southeastern Nigeria. Agan, et al. [193] demonstrated that 95.4% of pregnant women in a
hospital-based population in southeastern Nigeria tested positive for malaria parasitemia.
The parent study for Aims 1 and 2 took place approximately five years later, but high
rates of malaria parasitemia in pregnant women remained. Thus, little to no effective
improvements had been made to reduce the burden of malaria in pregnant women in this
region of Nigeria during that time period.
101
Aims 3 and 5 both estimated the incidence of CS among pregnant women in
Nigeria. The WHO estimated that 15.5% of pregnancies in Nigeria need to be delivered
by CS [154]. Both Aims 3 and 5 demonstrated low rates of CS in Nigeria compared to the
need estimated by the WHO (7% and 2%, respectively). Geographical location may have
resulted in the different rates of CS reported in this dissertation. The HBI was a
congregational-based randomized control trial in southeastern Nigeria, while the DHS
was a country wide cross-sectional study. Because data for both aims were collected no
more than two years apart, it is less likely that the different rates of CS demonstrated
between these two studies are a result of time trend differences. The HBI solely relied on
data collected in southeastern Nigeria, which have become relatively politically stable in
the last few years [208]. Political stability often offers economic growth as well as
educational and infrastructure improvements—such as hospitals [208]. The northern parts
of Nigeria have not displayed political stability in recent years and continually distort
national trends—because of the region’s high poverty, high illiteracy, low family
planning, and other reproductive health measures—compared to the rest of the county
[208, 215]. This may explain the different rates of CS demonstrated in the HBI and the
DHS.
Both studies demonstrated that women living in rural areas struggled to access a
health care facility during delivery, as demonstrated in lower odds of having a CS among
women living in rural areas compared to urban areas. With the DHS dataset, this
dissertation demonstrated that women did not deliver in a healthcare facility because they
faced cultural, economic and physical barriers while attempting to access perinatal care.
Tables 9 and 10 both demonstrated that women living in rural areas struggle with finding
102
adequate transportation to a healthcare facility to deliver. Decreasing the barriers women
face when attempting to access both prenatal care and services for delivery are imperative
to decreasing maternal mortality in Nigeria and achieving Millennium Development Goal
5 and 6.
Strengths and Limitations
There are numerous strengths and limitations to this dissertation. Over 99% of the
pregnant women in the HBI tested positive for malaria parasitemia. This information is
essential to advocating for malaria prevention programs in Enugu State, Nigeria. The HBI
cohort was also used to explore the relationship between CS and socio/demographic
variables as well as different disease statuses. This allowed us to capture a holistic
understanding of risk factors associated with CS in Enugu State, Nigeria. However, the
HBI was not without limitations. It was not possible to establish the effects of malaria
parasitemia on the fetus because adequate birthweights and gestational age were not able
to be established. This information would have been an important contribution to the
literature, as the relationship between malaria parasitemia levels and perinatal outcomes
are not well established. Also in the HBI, the reasons a woman had a CS were not
established, nor was prior use of CS. An attempt was made to control for prior CS by
using the number of people in the household as well as gravidity as proxies for prior CS;
however, it is unknown if these control methods were adequate. A sensitivity analysis
was also performed using only primigravida women; however, the number of women
(n=26) that had a CS for their first pregnancy was small. Therefore, significant
relationships between CS and other variables may not have been present in this analysis
103
because of lack of power. Also, no follow-up occurred when women did not attend postnatal interviews; therefore, it was not possible to determine the rate of maternal mortality.
In the HBI, 3002 people filled out the initial baseline questionnaire; however, only 2317
(77.2%) individuals returned for follow-up and completed information regarding mode of
delivery. This relatively high rate of being lost to follow-up may have resulted in an
inadequate estimate of the CS in Enugu State, Nigeria. If all women who were lost to
follow-up had a CS, than the estimate for CS in Enugu State would be much higher
(28.4%); likewise, if all women who were lost to follow-up had a vaginal delivery, the
estimate for CS in Enugu State would be lower (5.6%). Therefore, women lost to followup may have had substantial influences on the CS estimates in this dissertation. Finally,
it is unknown from the HBI data whether women in rural settings truly had difficulty
accessing a healthcare facility. It is possible that more women in urban settings elected to
have a CS. Answering these questions is essential to understanding the barriers that
women face when seeking adequate perinatal care in Nigeria. Some of these questions
were answered by utilizing the DHS dataset, as it provided information on previous CS
and the reasons why women did not attend a healthcare facility for delivery.
Like the HBI, the results from the DHS are unique to the literature in that the
relationships between CS and socio/demographic variables, as well as medical risk
factors, were explored. As the DHS includes data across Nigeria, I also controlled for
geopolitical region. The DHS contained information regarding the reasons women did not
deliver at a healthcare facility. Therefore, I was able to get a better understanding of the
barriers women face while attempting to access healthcare while in labor. A sensitivity
analysis was performed using only primigravida women. In the unadjusted models,
104
primigravida women showed similar trends in the OR as the full sample. However, after
adjustment, statistical significance in the primigravida model diminished. It is possible
that this analysis lacked statistical power because either over-adjustment occurred in the
primigravida model, or a relatively small number of women (n=170) had a CS for their
first pregnancy.
The Aims based on the DHS are not without their limitations. Although more
women who were offered HIV testing as part of prenatal care had a CS, the data do not
permit us to determine if this was from high rates of HIV among these women, or if it
was from access to robust prenatal care. Likewise, it is unknown if women were taking
iron supplementation because of anemia or because they attended prenatal care. Many
socio/demographic and economic variables were significantly correlated but did not have
high correlation coefficients. Although this indicates no collinearity between these
variables in this dataset, it is still difficult to determine if all models were over adjusted
by including variables that are typically related—such as education and wealth. Although
all Aims had their own unique strengths and limitations, they all added to the literature
indicating that women in Nigeria face numerous barriers to accessing healthcare during
pregnancy and delivery.
Practice and Policy
This dissertation demonstrated that >99% of pregnant women in Enugu State,
Nigeria had malaria parasitemia. This is aligned with other research indicating that in
Nigeria, only13.2% of pregnant women receive IPTp-SP and 33.7% of pregnant women
sleep under an ITN [170, 173]. Based on the high prevalence of malaria in the HBI data,
105
education on best practices to prevent malaria during pregnancy, and resources in support
of these practices are urgently needed. Increases in obstetric services during delivery are
also needed.
When medically necessary, CS is frequently a lifesaving procedure; however,
risks associated with CS are often highest within African countries where medical
personnel may lack the training or proper equipment and supplies [4, 155]. In general,
better perinatal health outcomes have been associated with CS rates between 5%–15%
[151-154, 216], and the WHO has estimated that in 15.5% of pregnancies in Nigeria, a
CS is medically necessary [154]. This is 2-3 times the rate found in the HBI and the DHS
(7% and 2% respectively). Therefore, unlike in other parts of the world where discussion
centers on overutilization of CS [154], it is likely that in this area of Nigeria an overall
underutilization of CS occurs. This may explain why Nigeria accounts for half of the
global burden of incident obstetric fistulas, which is caused by prolonged labor and can
be prevented with access to emergency obstetric services such as a CS [204].
Although many countries in SSA have healthcare facilities that can perform CS,
the quality of care within these clinics is neither consistent nor reliable [217]. It is
estimated that less than 1% of individuals in western SSA have access to surgical care
that is safe, affordable and can be performed in a timely manner [218]. Countries in SSA
suffer from an overall shortage of facilities equipped to perform such specialized
treatment; additionally, countries in SSA also suffer from a lack of skilled workers
capable of performing specialized medicine [2]. Because previous research within
Nigeria showed that only 1 in 21 health facilities was equipped to perform CS [138], it is
likely that even if access to health clinics was increased, most clinics would not be
106
equipped to perform CS. In a survey of 77 hospitals in SSA only 6% reported the ability
to provide safe anesthesia for a CS [157]. The anesthesiologist in these facilities reported
that only 19% operated in facilities were electricity was always available [157]. Only
56% of the facilities reported always having access to running water and only 23%
reported having access to blood for transfusion [157]. Because many facilities lack water,
electricity, medication, equipment and trained personnel to perform CS, the operation is
often associated with unacceptably high rates of sepsis, hemorrhage, and maternal death
[149]. Therefore, increasing access to healthcare facilities alone would not improve
medical care for pregnant women, vast improvements in infrastructure and training of
skilled obstetricians needs to be made within SSA.
Future Directions
The Millennium Development Goals were developed to reduce poverty, hunger,
illiteracy, gender inequality, and diseases while also attempting to increase environmental
sustainability and access to healthcare [14]. Although no goal has been achieved thus far,
great improvements have been demonstrated. It is this author’s opinion that continuing to
develop global goals emphasizes our responsibility as global citizens. However, change
within individual countries should reflect local customs and be sustainable from within.
Results from this dissertation indicate that there are both needs and opportunities
for improvements in access to proper prenatal care in Nigeria. This will not be an easy
task to achieve. The infrastructure needed to achieve the Millennium Development Goals,
such as schools and hospitals, remains underdeveloped in Nigeria and most of SSA [208].
Additionally, previous research has demonstrated that even if access to health clinics
107
were increased, most skilled birth attendants would not have the proper equipment to
perform a lifesaving obstetric procedures [149]. Because many healthcare facilities in
SSA lack water, electricity, medication, equipment and trained personnel, it is likely that
in Nigeria malaria during pregnancy will persist at high rates and most women will delay
seeking treatment at healthcare facilities until dire complications develop [149]. Further
education of traditional birth attendants and community health workers in the
administration of prenatal medications and recognizing signs and symptoms of pregnancy
complication may decrease the burden of diseases associated with pregnancy in Nigeria,
ultimately leading to a decrease in maternal mortality. This approach has been successful
in other parts of the world and may prove to be beneficial in Nigeria [211-214]. By
utilizing preexisting infrastructure, such as the congregational based infrastructure
utilized by the HBI, women who would not regularly attend a healthcare facility for
prenatal care or delivery services, could be screened for early warning signs of high risk
pregnancy and for disease such as HIV and malaria. Women who are told they have a
high risk pregnancy could then be encouraged to attend a healthcare facility or a mobile
clinic prior to expected delivery date. Mobile clinics in SSA have demonstrated a
decrease in the burden of diseases in rural areas by: increasing adherence to medications
for both communicable and non-communicable disease; providing antenatal care;
providing child immunizations; and decreasing the burden of costs associated with
attending a healthcare facility outside of women’s local region [219, 220]. More
innovated programs that aim to decrease the burden of malaria and increase access to
obstetric services in Nigeria are needed. Programs, such as Riders for Health[221], that
utilize motorbikes to provide healthcare to individuals living in rural places in SSA may
108
be beneficial. Studies assessing the efficacy of programs targeting increasing access to
care in rural villages are also needed.
Other studies that address the questions raised by this dissertation are needed.
More in-depth studies that establish the causes of maternal mortality in Nigeria are
essential. Based on Nigeria’s maternal mortality ratio of 560 maternal deaths per
100,000 live births, it is estimated that 17 women in the HBI died [2]. Knowing the
reasons women die is essential to understand how to decrease maternal mortality in
Nigeria. Also, a future study assessing the relationship between having a CS in Nigeria
and future maternal and infant morbidity and mortality is essential to understanding the
safety of having a CS in Nigeria. As neither the HBI nor the DHS could answer questions
pertaining to causes of maternal mortality or the efficacy of having a CS, future studies
are essential.
Conclusion
In summary, the goals of this dissertation were to investigate common pregnancy
complications of Nigerian women. This dissertation demonstrated substantially high rates
of malaria during pregnancy and lower rates of CS in Nigeria than have been
recommended, indicating an overall lack of access to proper obstetric care and
demonstrates that Millennium Development Goal 5 has not been achieved in Nigeria
[154].
The results from this dissertation are concordant with other research establishing
the prevalence of malaria in Nigeria. In hospital samples, Agan et al, demonstrated 95%
of pregnant women in southeastern Nigeria had malaria parasitemia [193]; in a
109
community sample, this dissertation demonstrated that over 99% of pregnant women had
malaria parasitemia. The results should call attention to the need for further effective
strategies to reduce the burden of malaria in southeastern part of Nigeria [193]. Malaria
places a heavy burden on Nigeria’s healthcare system, accounting for up to 60% of
outpatient visits, 30% of hospital admissions and accounts for 11% of all maternal deaths
in Nigeria [170]. As post-Millennium Development Goals are created, reducing the
burden of malaria in Nigeria is essential. The prevention and treatment of malaria is
crucial for the further development of Nigeria and any other country with high malaria
transmission rates.
This dissertation verified that women in Nigeria continue to face barriers that
delay their seeking perinatal care. Two unique datasets were analyzed and both
demonstrated lower rates of CS than the WHO recommends within Nigeria to decrease
maternal mortality [154]. Both datasets also demonstrated that women living in rural
areas struggled to access health care facilities during delivery, and that as education
increased, so too did the odds of having a CS. The increase in CS as education increased
further calls to attention the need to promote gender equality in access to
education(Millennium Development Goal 2 and 3). This dissertation also demonstrated
that women did not deliver in a healthcare facility because they face cultural, economic
and physical barriers while attempting to access perinatal care. It is apparent that women
in Nigeria are delaying seeking treatment, not out of ignorance, but because they
encounter real barriers that delay seeking treatment, such as cost and limited
transportation. This was particularly important in rural areas where women had
consistently lower odds of having a CS compared to women in urban settings.
110
Furthermore, these studies revealed that women in this part of SSA are not following
global trends and over-utilizing CS, but instead are struggling to obtain adequate
perinatal healthcare, ultimately perpetuating the cycle of high maternal mortality and
gross health deficiencies that are common in SSA. Ultimately, results from this
dissertation indicate that in Nigeria there exists great need for improvement in access to
proper perinatal care.
111
REFERENCES
1.
CIA, The World Factbook. Retrieved May 7, 2015. Available from:
https://www.cia.gov/Library/publications/the-world-factbook/fields/2054.html.
2.
Thaddeus, S. and D. Maine, Too far to walk: Maternal mortality in context. Social
Science & Medicine, 1994. 38(8): 1091-1110.
3.
World Health Organization, Antenatal Care. Retrieved May 20, 2015. Available
from:
http://www.who.int/gho/maternal_health/reproductive_health/antenatal_care_text/
en/.
4.
Gabrysch, S. and O.M. Campbell, Still too far to walk: Literature review of the
determinants of delivery service use. BMC Pregnancy and Childbirth, 2009. 9(1):
34.
5.
World Health Organization, Maternal Mortality Fact Sheet. Retrieved May 5,
2015. Available from: http://www.who.int/mediacentre/factsheets/fs348/en/.
6.
Hogan, M.C., et al., Maternal mortality for 181 countries, 1980–2008: A
systematic analysis of progress towards Millennium Development Goal 5. The
Lancet, 2010. 375(9726): 1609-1623.
7.
WHO, UNICEF, UNFPA, The World Bank, and United Nations Population
Division, Trends in maternal mortality: 1990 to 2013. Geneva: World Health
Organization, 2014. 1-56.
8.
UNICEF, Maternal and Child Health. Retrieved June 23, 2015. Available from:
http://www.unicef.org/nigeria/children_1926.html.
9.
Adebami, O.J., et al., Associations between placental and cord blood malaria
infection and fetal malnutrition in an area of malaria holoendemicity. Am J Trop
Med Hyg, 2007. 77(2): 209-13.
10.
Kitui, J., S. Lewis, and G. Davey, Factors influencing place of delivery for
women in Kenya: An analysis of the Kenya Demographic and Health Survey,
2008/2009. BMC Pregnancy and Childbirth, 2013. 13(1): 40.
11.
Mbouzeko, R., Cameroon: Promoting Skilled Attendance at Child Birth to Avert
Maternal and Newborn Deaths. Retrieved July 3, 2015. Available from:
http://www.unicef.org/wcaro/english/media_5122.html.
12.
Cross, S., J.S. Bell, and W.J. Graham, What you count is what you target: The
implications of maternal death classification for tracking progress towards
reducing maternal mortality in developing countries. Bulletin of the World Health
Organization, 2010. 88(2): 147-153.
112
13.
Bhutta, Z.A., et al., Countdown to 2015 decade report (2000–10): Taking stock of
maternal, newborn, and child survival. The Lancet, 2010. 375(9730): 2032-2044.
14.
United Nations, Millennium Development Goals and Beyond 2015. Retrieved
May 5, 2015. Available from: http://www.un.org/millenniumgoals/.
15.
Briand, V., C. Badaut, and M. Cot, Placental malaria, maternal HIV infection and
infant morbidity. Annals of Tropical Paediatrics: International Child Health, 2009.
29(2): 71-83.
16.
National Guideline Clearninghouse, The Diagnosis and Treatment of Malaria in
Pregnancy. Retrieved May 15, 2015. Available from:
http://www.guideline.gov/content.aspx?id=25670.
17.
Desai, M., et al., Epidemiology and burden of malaria in pregnancy. The Lancet
Infectious Diseases, 2007. 7(2): 93-104.
18.
Gilles, H., et al., Malaria anaemia and pregnancy. Annals of Tropical Medicine
and Parasitology, 1969. 63(2): 245-63.
19.
Say, L., et al., Global causes of maternal death: A WHO systematic analysis. The
Lancet Global Health, 2014. 2(6): e323-e333.
20.
WHO, UNICEF, UNFPA and The World Bank, Trends in maternal mortality:
1990 to 2008. Geneva: World Health Organization, 2010. 1-17.
21.
United Nations, Goal 6: Combat HIV/AIDS, malaria and other diseases.
Retrieved May 7, 2015. Available from:
http://www.un.org/millenniumgoals/aids.shtml.
22.
Ronsmans, C., W.J. Graham, and Lancet Maternal Survival Series steering group,
Maternal mortality: Who, when, where, and why. The Lancet, 2006. 368(9542):
1189-1200.
23.
Babalola, S. and A. Fatusi, Determinants of use of maternal health services in
Nigeria-looking beyond individual and household factors. BMC Pregnancy and
Childbirth, 2009. 9(1): 43.
24.
Okonofua, F.E., et al., Influence of socioeconomic factors on the treatment and
prevention of malaria in pregnant and non-pregnant adolescent girls in Nigeria.
The Journal of Tropical Medicine and Hygiene, 1992. 95(5): 309-315.
25.
Menendez, C., et al., The impact of placental malaria on gestational age and birth
weight. Journal of Infectious Diseases, 2000. 181(5): 1740-1745.
26.
Menendez, C., A. Fleming, and P. Alonso, Malaria-related anaemia. Parasitology
Today, 2000. 16(11): 469-476.
113
27.
Alvarez, J.R., A. Al-Khan, and J.J. Apuzzio, Malaria in pregnancy. Infect Dis
Obstet Gynecol, 2005. 13(4): 229-36.
28.
Onah, H. and M. Ugona, Preferences for cesarean section or symphysiotomy for
obstructed labor among Nigerian women. International Journal of Gynecology &
Obstetrics, 2004. 84(1): 79-81.
29.
Lindsay, S., et al., Effect of pregnancy on exposure to malaria mosquitoes. The
Lancet, 2000. 355(9219): 1972.
30.
Huddle, J., R. Gibson, and T. Cullinan, The impact of malarial infection and diet
on the anaemia status of rural pregnant Malawian women. European Journal of
Clinical Nutrition, 1999. 53(10): 792-801.
31.
Menéndez, C., et al., Malaria prevention with IPTp during pregnancy reduces
neonatal mortality. PLoS One, 2010. 5(2): e9438.
32.
World Health Organization, Malaria in pregnant women. Retrieved May 15, 2015.
Available from:
http://www.who.int/malaria/areas/high_risk_groups/pregnancy/en/.
33.
World Health Organization, Lives at risk: malaria in pregnancy. Retrieved May
14, 2015. Available from: http://www.who.int/features/2003/04b/en/.
34.
Schantz-Dunn, J. and N.M. Nour, Malaria and pregnancy: A global health
perspective. Reviews in obstetrics and gynecology, 2009. 2(3): 186.
35.
Brentlinger, P.E., C.B. Behrens, and M.A. Micek, Challenges in the concurrent
management of malaria and HIV in pregnancy in sub-Saharan Africa. The Lancet
Infectious Diseases, 2006. 6(2): 100-111.
36.
Calvert, C. and C. Ronsmans, HIV and the risk of direct obstetric complications:
A systematic review and meta-analysis. PloS one, 2013. 8(10): e74848.
37.
World Health Organization, HIV/AIDS: Mother-to-child transmission of HIV.
Retrieved May 15, 2015. Available from: http://www.who.int/hiv/topics/mtct/en/.
38.
Centers for Disease Control and Prevention, HIV Among Pregnant Women,
Infants, and Children. Retrieved April 4, 2015. Available from:
http://www.cdc.gov/hiv/risk/gender/pregnantwomen/facts/.
39.
UNICEF, Elimination of Mother-to-Child Transmission of HIV. Retrieved May
12, 2015. Available from: http://data.unicef.org/hiv-aids/emtct.
40.
Rueda, S., et al., Patient support and education for promoting adherence to highly
active antiretroviral therapy for HIV/AIDS. The Cochrane Library, 2006.
114
41.
Ware, N.C., et al., Explaining adherence success in sub-Saharan Africa: An
ethnographic study. PLoS medicine, 2009. 6(1): e1000011.
42.
Brabin, B.J., M. Hakimi, and D. Pelletier, An analysis of anemia and pregnancyrelated maternal mortality. The Journal of Nutrition, 2001. 131(2): 604S-615S.
43.
Hotez, P.J. and D.H. Molyneux, Tropical anemia: One of Africa's great killers and
a rationale for linking malaria and neglected tropical disease control to achieve a
common goal. PLoS Neglected Tropical Diseases, 2008. 2(7): e270.
44.
Noronha, J.A., et al., Anemia in pregnancy-consequences and challenges: A
review of literature. Journal of South Asian Federation of Obstetrics and
Gynecology, 2012. 4(1): 64-70.
45.
World Health Organization, Worldwide prevalence of anaemia 1993-2005: WHO
global database on anaemia. 2008.
46.
World Health Organization, Malaria. Retrieved January 5, 2015. Available from:
http://www.who.int/topics/malaria/en/.
47.
Yemadje, L.P., et al., Understanding the differences in prevalence of epilepsy in
tropical regions. Epilepsia, 2011. 52(8): 1376-1381.
48.
Kiszewski, A., et al., A global index representing the stability of malaria
transmission. Am J Trop Med Hyg, 2004. 70(5): 486-98.
49.
Murray, C.J., et al., Global malaria mortality between 1980 and 2010: A
systematic analysis. The Lancet, 2012. 379(9814): 413-431.
50.
World Health Organization, World Malaria Report 2013. Geneva: WHO, 2013.
51.
Holt, R.A., et al., The genome sequence of the malaria mosquito Anopheles
gambiae. Science, 2002. 298(5591): 129-149.
52.
ter Kuile, F.O., et al., The burden of co-infection with human immunodeficiency
virus type 1 and malaria in pregnant women in sub-saharan Africa. Am J Trop
Med Hyg, 2004. 71(2 suppl): 41-54.
53.
Rogerson, S.J., et al., Malaria in pregnancy: pathogenesis and immunity. Lancet
Infect Dis, 2007. 7(2): 105-117.
54.
Ansell, J., et al., Short-range attractiveness of pregnant women to Anopheles
gambiae mosquitoes. Trans R Soc Trop Med Hyg, 2002. 96(2): 113-116.
55.
Bray, R.S. and M.J. Anderson, Falciparum malaria and pregnancy. Transactions
of the Royal Society of Tropical Medicine and Hygiene, 1979. 73(4): 427-431.
115
56.
Brabin, B., et al., Failure of chloroquine prophylaxis for falciparum malaria in
pregnant women in Madang, Papua New Guinea. Annals of Tropical Medicine
and Parasitology, 1990. 84(1): 1-9.
57.
Nguyen-Dinh, P., et al., Rapid spontaneous postpartum clearance of Plasmodium
falciparum parasitaemia in African women. The Lancet, 1988. 332(8613): 751752.
58.
Bottero, J., et al., Spontaneous postpartum clearance of Plasmodium falciparum
parasitemia in pregnant women, Benin. The American Journal of Tropical
Medicine and Hygiene, 2011. 84(2): 267-269.
59.
Kortmann, H.F.C.M., Malaria and Pregnancy. Drukkerij Elinkwijk, 1972.
60.
Diagne, N., et al., Increased susceptibility to malaria during the early postpartum
period. New England Journal of Medicine, 2000. 343(9): 598-603.
61.
Ramharter, M., et al., Clinical and parasitological characteristics of puerperal
malaria. Journal of Infectious Diseases, 2005. 191(6): 1005-1009.
62.
Menéndez, C., et al., An autopsy study of maternal mortality in Mozambique: The
contribution of infectious diseases. PLoS medicine, 2008. 5(2): e44.
63.
Guyatt, H.L. and R.W. Snow, Impact of malaria during pregnancy on low birth
weight in sub-Saharan Africa. Clin Microbiol Rev, 2004. 17(4): 760-769.
64.
Le Hesran, J.Y., et al., Maternal placental infection with Plasmodium falciparum
and malaria morbidity during the first 2 years of life. Am J Epidemiol, 1997.
146(10): 826-831.
65.
Uneke, C.J., Impact of placental Plasmodium falciparum malaria on pregnancy
and perinatal outcome in sub-Saharan Africa: II: Effects of placental malaria on
perinatal outcome; malaria and HIV. The Yale Journal of Biology and Medicine,
2007. 80(3): 95.
66.
Lea, R.G. and A.A. Calder, The immunology of pregnancy. Current Opinion in
Infectious Diseases, 1997. 10(3): 171-176.
67.
Fried, M., et al., Malaria elicits type 1 cytokines in the human placenta: IFN-γ and
TNF-α associated with pregnancy outcomes. The Journal of Immunology, 1998.
160(5): 2523-2530.
68.
Malhotra, I., et al., Umbilical cord–blood infections with Plasmodium falciparum
malaria are acquired antenatally in Kenya. Journal of Infectious Diseases, 2006.
194(2): 176-183.
69.
Huch, R. and A. Huch, Erythropoietin in obstetrics. Hematology/oncology clinics
of North America, 1994. 8(5): 1021-1040.
116
70.
Abdalla, S., Hematopoiesis in human malaria. Blood cells, 1989. 16(2-3): 401-19.
71.
Ballew, C. and J.D. Haas, Hematologic evidence of fetal hypoxia among newborn
infants at high altitude in Bolivia. American Journal of Obstetrics and
Gynecology, 1986. 155(1): 166-169.
72.
Rogerson, S.J., V. Mwapasa, and S.R. Meshnick, Malaria in pregnancy: Linking
immunity and pathogenesis to prevention. The American Journal of Tropical
Medicine and Hygiene, 2007. 77(6 Suppl): 14-22.
73.
Murphy, J., et al., Relation of haemoglobin levels in first and second trimesters to
outcome of pregnancy. The Lancet, 1986. 327(8488): 992-995.
74.
Beeson, J.G., et al., Targets of protective antibodies to malaria during pregnancy.
J Infect Dis, 2005. 192(9): 1647-50.
75.
Beeson, J.G., et al., Parasite adhesion and immune evasion in placental malaria.
Trends in Parasitology, 2001. 17(7): 331-337.
76.
Bull, P.C. and K. Marsh, The role of antibodies to Plasmodium falciparuminfected-erythrocyte surface antigens in naturally acquired immunity to malaria.
Trends in Microbiology, 2002. 10(2): 55-58.
77.
Steketee, R.W., et al., Comparability of treatment groups and risk factors for
parasitemia at the first antenatal clinic visit in a study of malaria treatment and
prevention in pregnancy in rural Malawi. The American Journal of Tropical
Medicine and Hygiene, 1996. 55(1 Suppl): 17-23.
78.
Brabin, B.J., An analysis of malaria in pregnancy in Africa. Bulletin of the World
Health Organization, 1983. 61(6): 1005.
79.
Duffy, P.E. and M. Fried, Antibodies that inhibit Plasmodium falciparum
adhesion to chondroitin sulfate A are associated with increased birth weight and
the gestational age of newborns. Infection and Immunity, 2003. 71(11): 66206623.
80.
O'Neil-Dunne, I., et al., Gravidity-dependent production of antibodies that inhibit
binding of Plasmodium falciparum-infected erythrocytes to placental chondroitin
sulfate proteoglycan during pregnancy. Infection and Immunity, 2001. 69(12):
7487-7492.
81.
Agomo, C.O., et al., Prevalence of malaria in pregnant women in Lagos, SouthWest Nigeria. Korean J Parasitol, 2009. 47(2): 179-83.
82.
World Health Organization, WHO Evidence Review Group: Intermittent
Preventive Treatment of malaria in pregnancy (IPTp) with SulfadoxinePyrimethamine (SP). WHO Headquarters, Geneva, 9-11 July 2012. Meeting
report. Retrieved June 11, 2015. Available from:
117
http://www.who.int/malaria/mpac/sep2012/iptp_sp_erg_meeting_report_july2012
.pdf.
83.
Hill, J., et al., Factors affecting the delivery, access, and use of interventions to
prevent malaria in pregnancy in sub-Saharan Africa: A systematic review and
meta-analysis. PLoS medicine, 2013. 10(7): e1001488.
84.
Lengeler, C., Insecticide-treated bed nets and curtains for preventing malaria.
Cochrane Database Syst Rev, 2004. 2(2).
85.
Gamble, C., et al., Insecticide-treated nets for the prevention of malaria in
pregnancy: A systematic review of randomised controlled trials. PLoS medicine,
2007. 4(3): e107.
86.
CDA dLAlmeida, T., et al., Field evaluation of the intermittent preventive
treatment of malaria during pregnancy (IPTp) in Benin: Evolution of the coverage
rate since its implementation. 2011.
87.
Pulford, J., et al., Reported reasons for not using a mosquito net when one is
available: A review of the published literature. Malar J, 2011. 10(83): 10.1186.
88.
Launiala, A. and M.-L. Honkasalo, Ethnographic study of factors influencing
compliance to intermittent preventive treatment of malaria during pregnancy
among Yao women in rural Malawi. Transactions of the Royal Society of
Tropical Medicine and Hygiene, 2007. 101(10): 980-989.
89.
Chapman, R.R., Endangering safe motherhood in Mozambique: Prenatal care as
pregnancy risk. Social Science & Medicine, 2003. 57(2): 355-374.
90.
Zamawe, C.O., Factors that Affect Maternal Care Seeking Behaviour and the
Choice of Practitioner (s) during Complications: The Case of Mang’anja Tribe in
Malawi. Research on Humanities and Social Sciences, 2013. 3(18): 18-25.
91.
Van der Sijpt, E., Hiding or hospitalising? On dilemmas of pregnancy
management in East Cameroon. Anthropology & Medicine, 2013. 20(3): 288-298.
92.
National Institute for Allergies and Infectious Diseases. HIV/AIDS. Retrieved
June 22, 2015. Available from:
http://www.niaid.nih.gov/topics/HIVAIDS/Understanding/Pages/whatareHIVAID
S.aspx.
93.
World Health organization. HIV/AIDS. 2015. Retrieved May 14, 2015. Available
from: http://www.who.int/mediacentre/factsheets/fs360/en/.
94.
AVERT. HIV Transmission-Frequently Asked Questions (FAQs). 2014.
Retrieved June 22, 2015. Available from: http://www.avert.org/hiv-transmissionquestions-answers.htm.
118
95.
UNAIDS. 2013 Global Fact Sheet. 2013. Retrieved May 12, 2015. Available
from:
http://www.unaids.org/sites/default/files/en/media/unaids/contentassets/document
s/epidemiology/2013/gr2013/20130923_FactSheet_Global_en.pdf.
96.
Steketee, R.W., J.J. Wirima, and C.C. Campbell, Developing effective strategies
for malaria prevention programs for pregnant African women. American Journal
Tropical Medicine Hygiene, 1996. 55(1): 95-100.
97.
Kumar, R., S. Uduman, and A. Khurranna, Impact of maternal HIV-1 infection on
perinatal outcome. International Journal of Gynecology & Obstetrics, 1995. 49(2):
137-143.
98.
Brocklehurst, P. and R. French, The association between maternal HIV infection
and perinatal outcome: a systematic review of the literature and meta‐analysis.
BJOG: An International Journal of Obstetrics & Gynaecology, 1998. 105(8): 836848.
99.
Ataide, R., et al., Antibodies that induce phagocytosis of malaria infected
erythrocytes: effect of HIV infection and correlation with clinical outcomes. PLoS
One, 2011. 6(7): e22491.
100.
Expert Panel. Prevention of Mother-to-Child Transmission of HIV: Expert Panel
Report and Recommendations to the U.S. Congress and U.S. Global AIDS
Coordinator 2010. Retrieved June 12, 2015. Available from:
http://www.pepfar.gov/documents/organization/135465.pdf.
101.
Nathan Shaffer, W.H.O. Use of Antiretroviral Drugs for Treating Pregnant
Women and Preventing HIV Infection in Infants (PMTCT ARV Guidelines).
2010: World Health Organization.
102.
World Health Organization. Rapid advice: use of antiretroviral drugs for treating
pregnant women and preventing HIV infection in infants, version 2. 2009.
Retrieved October 5, 2015. Available from:
http://www.who.int/hiv/pub/mtct/rapid_advice_mtct.pdf.
103.
Kohler, P.K., et al., Shame, Guilt, and Stress: Community Perceptions of Barriers
to Engaging in Prevention of Mother to Child Transmission (PMTCT) Programs
in Western Kenya. AIDS Patient Care and STDs, 2014. 28(12): 643-651.
104.
Turan, J.M., et al., The role of HIV-related stigma in utilization of skilled
childbirth services in rural Kenya: A prospective mixed-methods study. PLoS
Medicine, 2012. 9(8): e1001295.
105.
Steinberg, M.H., et al., Disorders of hemoglobin: genetics, pathophysiology, and
clinical management. 2009: Cambridge University Press.
119
106.
Drabkin, D.L. and J.H. Austin, Spectrophotometric studies II. Preparations from
washed blood cells; nitric oxide hemoglobin and sulfhemoglobin. Journal of
Biological Chemistry, 1935. 112(1): 51-65.
107.
World Health Organziation. Development of indicators for monitoring progress
towards health for all by the year 2000. 1981: World Health Organization.
108.
Hotez, P.J., et al., Incorporating a rapid-impact package for neglected tropical
diseases with programs for HIV/AIDS, tuberculosis, and malaria. PLoS Medicine,
2007. 3(5): 576.
109.
Bates, I., S. McKew, and F. Sarkinfada, Anaemia: a useful indicator of neglected
disease burden and control. 2007. PloS Medicine 4(8): e231.
110.
Friedman, J.F., H.K. Kanzaria, and S.T. McGarvey, Human schistosomiasis and
anemia: the relationship and potential mechanisms. Trends in Parasitology, 2005.
21(8): 386-392.
111.
Hotez, P.J., et al., Hookworm:" the great infection of mankind". PLoS Medicine,
2005. 2(3): 187.
112.
Ccrompton, D.W.T., The public health importance of hookworm disease.
Parasitology, 2000. 121(S1): S39-S50.
113.
van den Broek, N.R. and E.A. Letsky, Etiology of anemia in pregnancy in south
Malawi. The American Journal of Clinical Nutrition, 2000. 72(1): 247s-256s.
114.
Bhutta, Z.A., et al., Community-based interventions for improving perinatal and
neonatal health outcomes in developing countries: a review of the evidence.
Pediatrics, 2005. 115(2): 519-617.
115.
Garn, S., et al. Maternal hematologic levels and pregnancy outcomes. in Seminars
in Perinatology. 1981. 5(2): 155-162.
116.
Scholl, T.O. and T. Reilly, Anemia, iron and pregnancy outcome. The Journal of
Nutrition, 2000. 130(2): 443S-447S.
117.
Haider, B.A., et al., Anaemia, prenatal iron use, and risk of adverse pregnancy
outcomes: systematic review and meta-analysis. BMJ: British Medical Journal,
2013. 346.
118.
Blankson, M.L., et al., The relationship between maternal hematocrit and
pregnancy outcome: black-white differences. Journal of the National Medical
Association, 1993. 85(2): 130.
119.
Singh, K., Y. Fong, and S. Arulkumaran, Anaemia in pregnancy--a crosssectional study in Singapore. European Journal of Clinical Nutrition, 1998. 52(1):
65-70.
120
120.
Uneke, C., et al., Impact of maternal Plasmodium falciparum malaria and
haematological parameters on pregnancy and its outcome in southeastern Nigeria.
Journal of Vector Borne Diseases, 2007. 44(4): 285.
121.
Abrams, E.T., et al., Malaria during pregnancy and foetal haematological status in
Blantyre, Malawi. Malar Journal, 2005. 4: 39.
122.
Berkley, J. A., et al., (2009). HIV infection, malnutrition, and invasive bacterial
infection among children with severe malaria. Clinical Infectious Diseases, 49(3),
336-343.
123.
De Cock, K.M., H.W. Jaffe, and J.W. Curran, The evolving epidemiology of
HIV/AIDS. AIDS, 2012. 26(10): 1205-1213.
124.
van Eijk, A.M., et al., Human immunodeficiency virus seropositivity and malaria
as risk factors for third-trimester anemia in asymptomatic pregnant women in
western Kenya. The American Journal of Tropical Medicine and Hygiene, 2001.
65(5): 623-630.
125.
Ayisi, J.G., et al., The effect of dual infection with HIV and malaria on pregnancy
outcome in western Kenya. AIDS, 2003. 17(4): 585-594.
126.
Ned, R.M., et al., Modulation of immune responses during HIV–malaria coinfection in pregnancy. Trends Parasitology, 2005. 21(6): 284-291.
127.
Ticconi, C., et al., Effect of maternal HIV and malaria infection on pregnancy and
perinatal outcome in Zimbabwe. Journal of Acquired Immune Deficiency
Syndromes (1999), 2003. 34(3): 289-294.
128.
Bloland, P.B., et al., Maternal HIV infection and infant mortality in Malawi:
Evidence for increased mortality due to placental malaria infection. AIDS, 1995.
9(7): 721-726.
129.
Sachs, J.D. and P.J. Hotez, Fighting tropical diseases. Sciences. 2006. 5767: 1521.
130.
Burgard, S., Race and pregnancy-related care in Brazil and South Africa. Social
Science & <edicine, 2004. 59(6): 1127-1146.
131.
Reynolds, H.W., E.L. Wong, and H. Tucker, Adolescents' use of maternal and
child health services in developing countries. International Family Planning
Perspectives, 2006: 6-16.
132.
Magadi, M.A., A.O. Agwanda, and F.O. Obare, A comparative analysis of the use
of maternal health services between teenagers and older mothers in sub-Saharan
Africa: Evidence from Demographic and Health Surveys (DHS). Social Science
& Medicine, 2007. 64(6): 1311-1325.
121
133.
McCarthy, J. and D. Maine, A framework for analyzing the determinants of
maternal mortality. Studies in Family Planning, 1992: 23-33.
134.
Bell, J., S.L. Curtis, and S. Alayón, Trends in delivery care in six countries.
2003. Demographic and Health Survey Analytical Study Number 7.
135.
Glei, D.A., N. Goldman, and G. Rodrıǵ uez, Utilization of care during pregnancy
in rural Guatemala: does obstetrical need matter? Social Science & Medicine,
2003. 57(12): 2447-2463.
136.
Buor, D. and K. Bream, An analysis of the determinants of maternal mortality in
sub-Saharan Africa. Journal of Women's Health, 2004. 13(8): 926-938.
137.
Mekonnen, Y. and A. Mekonnen, Factors influencing the use of maternal
healthcare services in Ethiopia. Journal of Health, Population and Nutrition, 2003:
374-382.
138.
Shah, A., et al., Cesarean delivery outcomes from the WHO global survey on
maternal and perinatal health in Africa. International Journal of Gynecology &
Obstetrics, 2009. 107(3): 191-197.
139.
Fosu, G.B., Childhood morbidity and health services utilization: cross-national
comparisons of user-related factors from DHS data. Social Science & Medicine,
1994. 38(9): 1209-1220.
140.
Gage, A.J., Barriers to the utilization of maternal health care in rural Mali. Social
Science & Medicine, 2007. 65(8): 1666-1682.
141.
Grosse, R.N. and C. Auffrey, Literacy and health status in developing countries.
Annual Review of Public Health, 1989. 10(1): 281-297.
142.
Jejeebhoy, S.J., Women's education, autonomy, and reproductive behaviour:
Experience from developing countries. OUP Catalogue, 1995.
143.
Nwakoby, B.N., Use of obstetric services in rural Nigeria. The Journal of the
Royal Society for the Promotion of Health, 1994. 114(3): 132-136.
144.
Tomlinson, M., et al., Multiple risk factors during pregnancy in South Africa: The
need for a horizontal approach to perinatal care. Prevention Science, 2014. 15(3):
277-282.
145.
Anyangwe, S.C. and C. Mtonga, Inequities in the global health workforce: the
greatest impediment to health in sub-Saharan Africa. International Journal of
Environmental Research and Public Health, 2007. 4(2): 93-100.
146.
Manongi, R.N., T.C. Marchant, and I.C. Bygbjerg, Improving motivation among
primary health care workers in Tanzania: A health worker perspective. Human
Resources for Health, 2006. 4(1): 6.
122
147.
Onoh, R.C., et al., A 10-year appraisal of cesarean delivery and the associated
fetal and maternal outcomes at a teaching hospital in southeast Nigeria.
International Journal of Women's Health, 2015. 7: 531.
148.
Asowa-Omorodion, F.I., Women's perceptions of the complications of pregnancy
and childbirth in two Esan Communities, Edo state, Nigeria. Social Science &
Medicine, 1997. 44(12): 1817-1824.
149.
Wylie, B.J. and F.G. Mirza, Cesarean delivery in the developing world. Clinics in
Perinatology, 2008. 35(3): 571-582.
150.
United States National Library of Medicine. Cesarean Section. 2015. Retrieved
June 25, 2015. Available from:
http://www.nlm.nih.gov/medlineplus/cesareansection.html.
151.
Althabe, F., et al., Cesarean section rates and maternal and neonatal mortality in
low‐, medium‐, and high‐income countries: An ecological study. Birth, 2006.
33(4): 270-277.
152.
Betrán, A.P., et al., Rates of caesarean section: Analysis of global, regional and
national estimates. Paediatric and Perinatal Epidemiology, 2007. 21(2): 98-113.
153.
Ronsmans, C., S. Holtz, and C. Stanton, Socioeconomic differentials in caesarean
rates in developing countries: A retrospective analysis. The Lancet, 2006.
368(9546): 1516-1523.
154.
Gibbons, L., et al., The global numbers and costs of additionally needed and
unnecessary caesarean sections performed per year: Overuse as a barrier to
universal coverage. World Health Report, 2010. 30: 1-31.
155.
Souza, J.P., et al., Caesarean section without medical indications is associated
with an increased risk of adverse short-term maternal outcomes: the 2004-2008
WHO Global Survey on Maternal and Perinatal Health. BMC Medicine, 2010.
8(1): 71.
156.
Pearson, L. and R. Shoo, Availability and use of emergency obstetric services:
Kenya, Rwanda, Southern Sudan, and Uganda. International Journal of
Gynecology & Obstetrics, 2005. 88(2): 208-215.
157.
Hodges, S., et al., Anaesthesia services in developing countries: defining the
problems. Anaesthesia, 2007. 62(1): 4-11.
158.
Buchanan, A.M. and C.K. Cunningham, Advances and failures in preventing
perinatal human immunodeficiency virus infection. Clinical Microbiology
Reviews, 2009. 22(3): 493-507.
123
159.
World Health Organization Consolidated guidelines on the use of antiretroviral
drugs for treating and preventing HIV infection. Geneva: World Health
Organization; 2013. 2013.
160.
Wong, R.D., et al., Treatment of severe falciparum malaria during pregnancy with
quinidine and exchange transfusion. The American Journal of Medicine, 1992.
92(5): 561-562.
161.
Samanta, S., S. Samanta, and R. Haldar, Emergency caesarean delivery in a
patient with cerebral malaria-leptospira co infection: Anaesthetic and critical care
considerations. Indian Journal of Anaesthesia, 2014. 58(1): 55.
162.
Malhotra, M., et al., Maternal and perinatal outcome in varying degrees of
anemia. International Journal of Gynecology & Obstetrics, 2002. 79(2): 93-100.
163.
Dane, B., et al., Does maternal anemia affect the newborn? Turkey Archives of
Pediatrics, 2013. 195-199.
164.
Nkwabong, E. and J. Fomulu, Outcome of Pregnancies among Cameroonian
Anemic Women: A Comparative Cohort Study. Journal of Pregnancy and Child
Health, 2014. 1(2): 117.
165.
Gonzales, G.F., et al., Association of hemoglobin values at booking with adverse
maternal outcomes among Peruvian populations living at different altitudes.
International Journal of Gynecology & Obstetrics, 2012. 117(2): 134-139.
166.
World Health Organization, WHO Africa Region: Nigeria. 2014, Retrieved May
17, 2015. Available from: http://www.who.int/countries/nga/en/.
167.
UNICEF. Africa's population could hit 4 billion by 2100. 2014. Retrieved May
16, 2015. Available from:
http://www.npr.org/sections/goatsandsoda/2014/08/13/340091377/unicef-reportafricas-population-could-hit-4-billion-by-2100.
168.
UNICEF, Economic and social statistics on the countries and territories of the
world, with particular reference to children’s wellbeing. UNICEF, Geneva, 2011.
169.
UNICEF. Table 8: Women. Retrieved May 7, 2015. Available from:
http://www.unicef.org/sowc2013/files/Table_8_Stat_Tables_SWCR2013_ENGLI
SH.pdf.
170.
National Population Commissioned. Nigeria Malaria Indicator Survey 2010.
2012: Abuja, Nigeria: NPC, NMCP, and ICF International. 2012. Retrieved
September 15, 2014. Available from:
https://dhsprogram.com/pubs/pdf/MIS8/MIS8.pdf
171.
United States Embassy. Nigeria malaria fact sheet. 2011. Retrieved August 20,
2014. Available from:
124
http://photos.state.gov/libraries/nigeria/231771/Public/DecemberMalariaFactSheet2.pdf.
172.
Arinaitwe, E., et al., Intermittent preventive therapy with sulfadoxinepyrimethamine for malaria in pregnancy: a cross-sectional study from Tororo,
Uganda. PLoS One, 2013. 8(9): e73073.
173.
Diala, C., et al., Barriers to uptake of malaria prevention and treatment during
pregnancy in Cross River and Nasawara States, Nigeria. Washington (District of
Columbia): C-Change/FHI, 2012. 360.
174.
UNICEF. At a glance: Nigeria. 2013. Retrieved August 7, 2014. Available from:
http://www.unicef.org/infobycountry/nigeria_statistics.html.
175.
National Agency for the Control of AIDS, Global AIDS response country
progress report: Nigeria GARPR 2014. 2014. Retrieved May 16, 2014. Available
from:
http://www.unaids.org/sites/default/files/en/dataanalysis/knowyourresponse/count
ryprogressreports/2014countries/NGA_narrative_report_2014.pdf
176.
Joint United Nations Programme on HIV/AIDS (UNAIDS), Together we will end
AIDS. 2012 Retrieved May 17, 2014. Available from:
http://www.unicef.org/aids/files/aids__togetherwewillendaids_en.pdf
177.
Maine, D., et al., Guidelines for monitoring the availability and use of obstetric
services. 1997.
178.
Haines, A. and A. Cassels, Can the millennium development goals be attained?
BMJ: British Medical Journal, 2004. 329(7462): 394.
179.
Prevention, C.f.D.C.a. CDC in Nigeria: Factsheet. 2012. Retrieved May 17th,
2015. Available from:
http://www.cdc.gov/globalhealth/countries/nigeria/pdf/nigeria.pdf.
180.
Ezeanolue, E.E., et al., Comparative effectiveness of congregation-versus clinicbased approach to prevention of mother-to-child HIV transmission: Study
protocol for a cluster randomized controlled trial. Implementation Science, 2013.
8(1): 62.
181.
Swanbrow, D. Study of worldwide rates of religiosity, church attendance. Ann
Arbor, MI: University of Michigan. 1997. Retrieved September 17, 2014.
Available from: http://ns.umich.edu/Releases/1997/Dec97/chr121097a.html.
182.
Iheanacho, T., et al., Integrating mental health screening into routine community
maternal and child health activity: experience from Prevention of Mother-to-child
HIV transmission (PMTCT) trial in Nigeria. Social Psychiatry and Psychiatric
Epidemiology, 2015. 50(3): 489-495.
125
183.
Organization, W.H. Basic laboratory methods in medical parasitology. 1991.
Retrieved September 1, 2014. Available from:
http://www.who.int/malaria/publications/atoz/9241544104_part1/en/.
184.
World Health Organization, Guidelines for appropriate evaluations of HIV testing
technologies in Africa. 2006: US Department of Health and Human Services,
Centers for Disease Control and Prevention.
185.
Piwowar-Manning, E.M., et al., Validation of rapid HIV antibody tests in 5
African countries. Journal of the International Association of Physicians in AIDS
Care (JIAPAC), 2010. 9(3): 170-172.
186.
Foglia, G., et al., Use of rapid and conventional testing technologies for human
immunodeficiency virus type 1 serologic screening in a rural Kenyan reference
laboratory. Journal of Clinical Microbiology, 2004. 42(8): 3850-3852.
187.
Galiwango, R.M., et al., Evaluation of current rapid HIV test algorithms in Rakai,
Uganda. Journal of Virological Methods, 2013. 192(1): 25-27.
188.
Nigeria Population Commission. Measure Demographic and Health Survey II.
Nigeria Demographic and Health Survey, 2013. 2013.
189.
Demographic and Health Survey. Data Collection. Retrieved May 1, 2015.
Available from: http://dhsprogram.com/data/data-collection.cfm.
190.
Demographic and Health Survey Using Datasets for Analysis. Retrieved May 1,
2015. Available from: http://dhsprogram.com/data/Using-DataSets-forAnalysis.cfm#CP_JUMP_14042.
191.
Safer, M.P., Making pregnancy safer: The critical role of the skilled attendant.
Retrieved May 5, 2014. Available from:
http://www.unscn.org/layout/modules/resources/files/Making_pregnancy_safer_th
e_critical_role.pdf
192.
ICF International, Survey Organization Manual for Demographic and Health
Surveys. ICF International, 2012.
193.
Agan, T., et al., Prevalence of anemia in women with asymptomatic malaria
parasitemia at first antenatal care visit at the University of Calabar Teaching
Hospital, Calabar, Nigeria. International Journal of Women's Health, 2010. 2:
229.
194.
United States Embassy in Nigeria. Nigeria malaria fact sheet. Retrieved July 1,
2014. Available from:
http://photos.state.gov/libraries/nigeria/231771/Public/DecemberMalariaFactSheet2.pdf
126
195.
Hall, M.H. and R. Carr-Hill, Impact of sex ratio on onset and management of
labour. BMJ, 1982. 285(6339): 401-403.
196.
Khalil, M.M. and E. Alzahra, Fetal gender and pregnancy outcomes in Libya: A
retrospective study. Libyan Journal of Medicine, 2013. 8(1).
197.
Say, L. and R. Raine, A systematic review of inequalities in the use of maternal
health care in developing countries: Examining the scale of the problem and the
importance of context. Bulletin of the World Health Organization, 2007. 85(10):
p. 812-819.
198.
Wilson, N.O., et al., Pregnancy outcomes among patients with sickle cell disease
at Korle-Bu Teaching Hospital, Accra, Ghana: Retrospective cohort study. The
American Journal of Tropical Medicine and Hygiene, 2012. 86(6): 936-942.
199.
Odum, C., et al., Pregnancy outcome in HbSS-sickle cell disease in Lagos,
Nigeria. West African journal of medicine, 2001. 21(1): 19-23.
200.
Muganyizi, P., Determinants of adverse pregnancy outcomes among Sickle Cell
Disease deliveries at a tertiary hospital in Tanzania from 1999 to 2011. Open
Journal of Obstetrics and Gynecology. 2013. 6: 6.
201.
Oteng-Ntim, E., et al., Adverse maternal and perinatal outcomes in pregnant
women with sickle cell disease: systematic review and meta-analysis. Blood,
2015. 125(21): 3316-3325.
202.
Organization, T.W.H. Sickle cell disease prevention and control. Retrieved April
29, 2015. Available from: http://www.afro.who.int/en/clusters-aprogrammes/dpc/non-communicable-diseases-managementndm/programmecomponents/sickle-cell-disease.html.
203.
E Rawizza, H., et al., Loss to Follow-Up within the Prevention of Mother-toChild Transmission Care Cascade in a Large ART Program in Nigeria. Current
HIV Research, 2015. 13(3): 201-209.
204.
UNFPA, E., Obstetric fistula needs assessment report: Findings from nine African
countries. 2003. New York: UNFPA Engender Health.
205.
Karlsen, S., et al., The relationship between maternal education and mortality
among women giving birth in health care institutions: Analysis of the cross
sectional WHO Global Survey on Maternal and Perinatal Health. BMC Public
Health, 2011. 11(1): 606.
206.
Scheme, N.H.I. National Health Insurance Scheme 2015; Retrieved June 5, 2015.
Available from:
http://www.nhis.gov.ng/index.php?option=com_content&view=article&id=47:we
lcome-note-from-executive-secretary&catid=34:home.
127
207.
Onwujekwe, O., et al., Willingness to pay for community-based health insurance
in Nigeria: Do economic status and place of residence matter? Health Policy and
Planning, 2010. 25(2): 155-161.
208.
Reed, H.E. and B.U. Mberu, Ethnicity, Religion, and Demographic Behavior in
Nigeria, in The International Handbook of the Demography of Race and
Ethnicity. 2015, Springer. 419-454.
209.
Erulkar, A. and M.V. Bello, The experience of married adolescent girls in
northern Nigeria. 2007, Population Council.
210.
Betrán, A.P., et al., National estimates for maternal mortality: an analysis based
on the WHO systematic review of maternal mortality and morbidity. BMC Public
Health, 2005. 5(1): 131.
211.
Gill, C.J., et al., Can traditional birth attendants be trained to accurately identify
septic infants, initiate antibiotics, and refer in a rural African setting? Global
Health: Science and Practice, 2014. 2(3): 318-327.
212.
Bang, A.T., et al., Simple clinical criteria to identify sepsis or pneumonia in
neonates in the community needing treatment or referral. The Pediatric Infectious
Disease Journal, 2005. 24(4): p. 335-341.
213.
Baqui, A.H., et al., Community‐based validation of assessment of newborn
illnesses by trained community health workers in Sylhet district of Bangladesh.
Tropical Medicine & International Health, 2009. 14(12): 1448-1456.
214.
Khanal, S., et al., Community health workers can identify and manage possible
infections in neonates and young infants: MINI—a model from Nepal. Journal of
Health, Population and Nutrition, 2011: 255-264.
215.
Olurodo, L., Impact of social change on reproductive choice in Nigeria: A study
of Muslim women in Purdah, in Proceedings of the International Conference on
Population and Reproductive Health in the Muslim World, G.I. Serour, Editor.
2000, Cairo: Al-Azhar University. 346–359.
216.
Althabe, F. and J.M. Belizán, Caesarean section: The paradox. The Lancet, 2006.
368(9546): 1472-1473.
217.
Kwast, B.E., Quality of care in reproductive health programmes: Concepts,
assessments, barriers and improvements—An overview. Midwifery, 1998. 14(2):
66-73.
218.
Alkire, B.C., et al., Global access to surgical care: A modelling study. The Lancet
Global Health, 2015. 3(6): e316-e323.
128
219.
Coleman, R., G. Gill, and D. Wilkinson, Noncommunicable disease management
in resource-poor settings: A primary care model from rural South Africa. Bulletin
of the World Health Organization, 1998. 76(6): 633.
220.
Tanser, F., et al., New approaches to spatially analyse primary health care usage
patterns in rural South Africa. Tropical Medicine & International Health, 2001.
6(10): 826-838.
221.
Riders for Health. Riders for Health. Retrieved August 5, 2015; Available from:
http://www.riders.org/.
129
APPENDIX A
MANUSCRIPT 1
TITLE: Population based prevalence of malaria among pregnant women in Enugu State,
Nigeria: The Healthy Beginning Initiative Cohort Study.
ABSTRACT
Background: Malaria adversely affects pregnant women and their fetuses or
neonates. Estimates of the malaria burden in pregnant women based on health facilities
often do no present a true picture of the problem due to the low proportion of women
delivering at these facilities in malaria endemic regions. Data for this study were obtained
from the Healthy Beginnings Initiative using community based sampling. Self-identified
pregnant women between the ages of 17-45 years were recruited from churches in Enugu
State, Nigeria. Malaria parasitemia was classified as high and low based on the malaria
plus system.
Findings: Of the 2069 pregnant women for whom malaria parasitemia levels were
recorded, over 99% tested positive for malaria parasitemia; 62% showed low parasitemia
and 38% high parasitemia. After controlling for confounding variables, odds for high
parasitemia were lower among those who had more people in the household (for every
one person increase in a household, OR=0.94, 95% CI 0.89-0.99).
Conclusion: Results of this study are consistent with hospital-based estimates of
malaria during pregnancy in southeastern Nigeria. Based on the high prevalence of
130
malaria parasitemia in our sample, education on best practices to prevent malaria during
pregnancy, and resources in support of these practices are urgently needed.
Key Words: Prevalence, pregnancy, malaria, Nigeria
131
BACKGROUND
Nigeria accounts for roughly 25% of the malaria burden in sub-Saharan
Africa [1,2]. Often undetected and untreated, malaria adversely affects pregnant women
and their fetus or neonate [2-4]. Current estimates of malaria parasitemia in Nigerian
pregnant women vary greatly among geographic regions. Hospital-based prevalence
percentages range from 5% in the northwestern region [5], 17% in the southwestern
region [6], to 95% in the southeastern region where Nigeria borders the Gulf of Guinea
[7].
In Nigeria, only an estimated 35% of pregnant women deliver at a
healthcare facility [8]. Therefore, health facility based estimates of the malaria burden in
pregnant women often do no present a true picture of the problem. This cohort study of
pregnant women in the community is likely to be a more representative sample and,
therefore, a more accurate estimate of the burden of malaria during pregnancy in
southeastern Nigeria. The aims of this study were two-fold, (1) to investigate the
population-based malaria parasitemia burden during pregnancy in Enugu State, Nigeria
(2) to explore person-level maternal risk factors that are associated with high malaria
parasitemia.
132
METHODS
Data for this study were obtained from the Healthy Beginnings Initiative
(HBI), which has previously been described in detail [9]. Briefly, self-identified pregnant
women between the ages of 17-45 years were recruited from 40 churches of varying
denominations in Enugu State, Nigeria where the population is more than 95% Christian.
Recruitment from churches was expected to provide a representative sample of pregnant
woman in Enugu State, Nigeria, as church attendance approaches 90% in the country
[9,10]. Pregnant women were given information on the study and, if interested, were
asked to read and sign a written consent form. Majority of participants were unable to
read the local language (Ibo) and preferred to have the study material in English. For
participants who could not read, a church-based health advisor or a research assistant read
the consent form aloud in English or Ibo; the participants gave their consent by affixing
thumb prints or using initials.
A structured questionnaire consisting of both validated and not validated
measures was implemented at a 6th grade reading level [9]. Trained research staff and
church-based health advisors administered the survey. Participants had the option of
reading the survey themselves or having study personnel read the questions to them in
either English or Ibo. Other survey questions and laboratory measures not discussed in
this paper can be found in the study protocol [9].
Parasitemia levels were assessed using the malaria plus system [11]. Thick
blood smears were examined using microscopy under oil immersion [11]. To ensure
quality control, each slide was examined by multiple laboratory technicians and random
checks were made by a hospital review panel. The malaria plus system was scored as
133
follows: 0 for no parasites, + for 1-10 parasites per 100 high power field, ++ for 11-100
parasites per 100 high power field, +++ for 1-10 parasites per high power field, ++++ for
over 10 parasites per high power field. Thus, levels of parasitemia increase as the scoring
moves from 0 through ++++.
Malaria parasitemia was classified as high and low based on the malaria
plus system. Those in the 0 and + group were classified as low parasitemia; while those
in the ++ and +++ groups were classified as high parasitemia. No participants showed
malaria parasitemia consistent with the ++++ group. Gravidity was dichotomized as > 3
previous pregnancies and <3 pregnancies. Associations between malaria parasitemia and
continuous variables were determined using ANOVA. Pearson's Chi-square test was used
to examine associations of malaria with categorical and dichotomous variables. Crude
and adjusted logistic regression models were used to determine the association between
participant characteristics and malaria parasitemia levels. Statistical significance was set
at p< 0.05. Data analyses were conducted using Stata version 12.0 [Stata Corporation,
College Station, TX]. The parent study was approved by the Institutional Review Board
of the University of Nevada, Reno, and the Nigerian National Health Research Ethics
Committee. This secondary data-analysis was considered exempt from human subjects
review by the Mel and Enid Zuckerman College of Public Health Research Office.
134
FINDINGS
Malaria parasitemia levels were recorded for 2069 pregnant women. Over
99% of the women in the study tested positive for malaria parasitemia (n=2052).
Categorized according to the malaria plus system, malaria parasitemia in our sample
included: less than < 1% no infection (n=17); 62% in the + group (n=1275); 36% in the
++ group (N=737); 2% in the +++group (n=40); with no one falling into the ++++ group
(n=0) (see Table 1). When malaria was categorized as low and high parasitemia, 62%
(n=1292) were classified as low parasitemia and 38% (n=777) as high parasitemia. As
shown in Table 2, no significant differences were found between high and low malaria
parasitemia and gravidity, area of residence, distance to nearest healthcare facility,
household size, or age of participants. Table 3 shows the results of logistic regression
analysis of the association between participant characteristics and malaria parasitemia.
After controlling for confounding variables, odds for high parasitemia were lower among
those who had more people in the household (For every one person increase in a
household, OR=0.94, 95% CI 0.89-0.99).
135
DISCUSSION
The results of our study demonstrated that over 99% of pregnant women
in Enugu, Nigeria showed some level of malaria parasitemia, with 38% showing high
levels of parasitemia. For each additional person in the household, a 6% lower odds of
high malaria parasitemia was found. Estimates presented in this paper are consistent with
hospital-based estimates of malaria during pregnancy in the southeastern region of
Nigeria [7].
Malaria places a heavy burden on Nigeria’s already fragile health care
system with nearly 110 million clinical cases occurring a year, accounting for up to 60%
of outpatient visits and 30% of hospital admissions[1]. The Roll Back Malaria program
recommends that pregnant women receive intermittent preventative treatment with the
inclusion of sulphadoxine-pyrimethamine (IPTp) as part of antenatal care and
recommends that pregnant women sleep under insecticide-treated nets (ITN). Although
Nigeria has adopted these recommendations, it has a long way to go in achieving these
goals with only 13.2% of pregnant women receiving IPTp and 33.7% of pregnant women
sleeping under an ITN [1,4]. Based on the high prevalence of malaria in our sample,
education on best practices to prevent malaria during pregnancy, and resources in support
of these practices are urgently needed.
Competing interests
The authors declare that they have no competing interests.
Authors’ contributions
136
JG wrote and conceptualized the frame work for the paper. EE is the principal
investigator for the grant. MO was the local investigator for HBI. CE assisted in the
conceptualization and development of the research protocol. AO was the research
coordinator in charge of participant recruitment, trial implementation and data collection.
JE, EJ, KE, SP, LK, SH, and EE provided input and feedback during the planning,
analyses and framework for the paper. All authors read and approved the final version of
the manuscripts.
Acknowledgments
The Healthy Beginning Initiative was funded by the Eunice Kennedy Shriver
National Institute of Child Health and Human Development (NICHD), the National
Institute of Mental Health (NIMH) and the President’s Emergency Plan for AIDS Relief
(PEPFAR) under award number R01HD075050 to Echezona Ezeanolue, MD. Additional
support for this study was provided by the Healthy Sunrise Foundation. The funding
agencies played no role in the study conception, design, data collection, data analysis,
data interpretation or writing of the report. We are grateful to the Catholic Bishop of
Awgu diocese, Anglican Bishop of Enugu; Catholic Bishop of Enugu; Anglican Bishop
of Oji-River. Their support was instrumental to the successful implementation of HBI.
HBI implementation would not have been possible without the support and tireless effort
of the priests in the participating churches. The church-based Volunteer Health Advisors
took ownership of the program and made the process of recruitment and implementation
smooth for our study team and participants. This study would have been impossible to
137
conduct without the support of PeTR-GS (our PEPFAR-supported partner) staff and
volunteers.
138
REFERENCES
1. National Population Commission (NPC) [Nigeria], National Malaria Control
Programme (NMCP) [Nigeria], and ICF International. 2012. Nigeria malaria
indicator survey 2010. Abuja, Nigeria: NPC, NMCP, and ICF International.
2. World Health Organization. World malaria report 2013. Available at:
http://www.who.int/malaria/publications/world_malaria_report_2013/en/.
Accessed May 1, 2015.
3. World Health Organization, 2013. Malaria entomology and vector control. Available
at: http://apps.who.int/iris/handle/10665/85890. Accessed May 1, 2015.
4. Diala CC, Pennas T, Choi P, Marin C, Belay K, 2013. Perceptions of intermittent
preventive treatment of malaria in pregnancy (IPTp) and barriers to adherence in
Nasarawa and Cross River States in Nigeria. Malar J 12:342.
5. Isah AY, Amanabo MA, Ekele BA, 2011. Prevalence of malaria parasitemia amongst
asymptomatic pregnant women attending a Nigerian teaching hospital. Ann Afr
Med 10(2): 171-174.
6. Uneke C, Sunday-Adeoye I, Iyare F, Ugwuja E, Duhlinska D, 2007. Impact of
maternal Plasmodium falciparum malaria and haematological parameters on
pregnancy and its outcome in southeastern Nigeria. J Vector Dis 44(4):285-290.
7. Agan T, Ekabua J, Udoh A, Ekanem E, Efiok E, Mgbekem M, 2010. Prevalence of
anemia in women with asymptomatic malaria parasitemia at first antenatal care
visit at the University of Calabar Teaching Hospital, Calabar, Nigeria. Int J
Womens Health 2:229-233.
8. Adebami OJ, Owa JA, Oyedeji GA, Oyelami OA, Omoniyi-Esan GO, 2007.
Associations between placental and cord blood malaria infection and fetal
malnutrition in an area of malaria holoendemicity. Am J Trop Med Hyg
77(2):209-213.
9. Ezeanolue EE, Obiefune MC, Yang W, Obaro SK, Ezeanolue CO, Ogedegbe GG
2013. Comparative effectiveness of congregation-versus clinic-based approach to
prevention of mother-to-child HIV transmission: study protocol for a cluster
randomized controlled trial. Implement Sci. 8(1):62.
10. Swanbrow D. 2014. Study of worldwide rates of religiosity, church attendance.
Available at: http://ns.umich.edu/Releases/1997/Dec97/chr121097a.html.
Accessed April 17, 2015.
11. World Health Organization 1991. Basic laboratory methods in medical parasitology.
Available at:
http://www.who.int/malaria/publications/atoz/9241544104_part1/en/. Accessed
May, 5, 2015.
139
Table 1: Malaria parasitemia frequency by the Malaria Plus System
Malaria Plus System
N(%)
0
17 (<1)
+
1275 (62)
++
737 (36)
+++
40 (2)
++++
0 (0)
Total
2069 (100)
Notes: Levels of parasitemia increase as the scoring moves from 0 through ++++
140
141
Table 3: Logistic regression models for malaria parasitemia and participant
level characteristics
a
Crude model
Adjusted
N OR(95% CI)
OR(95% CI)
Gravidity
Multigravida 1305
Ref.
Ref.
Primi/secundigravida
688 1.04(0.86-1.26) 0.93(0.75-1.16)
Residence
Ref.
Urban
513
Ref.
Rural 1548 1.07(0.87-1.31) 1.07(0.86-1.32)
Distance to Healthcare Facility
Ref.
0-5(km)
719
Ref.
5-10(km)
777 1.08(0.88-1.34) 1.08(0.87-1.34)
10+(km)
562 1.24(0.99-1.56) 1.23(0.98-1.56)
Household size
2050 0.96(0.91-1.00)
a
Notes: Overall model n=1970
b
Indicates significance at p<0.05
b
0.94(0.89-0.99)
142
APPENDIX B
MANUSCRIPT 2
The need for increased access to life saving obstetric procedures: A cohort study of
Caesarean-section in Enugu State, Nigeria
ABSTRACT:
Background: In order to meet the Millennium Development Goals to decrease
maternal mortality an increase in access to lifesaving obstetric measures such as
Cesareans is needed. Nigeria contributed the second largest percent of the global number
of maternal deaths in 2013. In this analysis, we aim to establish the rates of Cesareans
and determine socioeconomic or medical risk factors associated with having a Cesarean
in Enugu State, Nigeria.
Methods: Data for this study were derived from the Healthy Beginnings Initiative
cohort. Participant demographic characteristics were obtained from 2317 women at
baseline via a semi-structured questionnaire. Only singleton deliveries of women between
the ages of 17-45 at baseline were retained for this analysis. Post-delivery questionnaires
were used to ascertain the mode-of-delivery. Crude and adjusted logistic regressions with
Cesareans as the main outcome are presented.
Results: In this sample, 7.2% women had Cesarean. Adjusted logistic regression
models demonstrated that compared to women aged 15-24, the odds of having a CS were
higher when the mother was aged 25-34 years (adjusted OR (aOR): 2.01; 95% CI: 1.043.90) and when the mother was aged 35-45 years (aOR: 2.73;1.26-5.92). Compared to
those with a primary school education or less, the odds of having a CS were higher if the
143
mother had a tertiary education (aOR: 2.91; 1.54-5.53), but not if she had a secondary
education (aOR: 1.27; 0.73-2.30). The odds of having a CS were significantly lower if
participants were employed part-time compared to full-time (aOR: 0.56; 0.32-0.97).
Compared to women who lived in an urban setting, those who lived in a rural setting had
a significant reduction in the odds of having a CS (aOR: 0.58; 0.38-0.89). Significantly
higher odds of having a CS were seen among those with high peripheral malaria
parasitemia compared to those with low parasitemia (aOR: 1.53; 1.03-2.27).
Conclusion: Findings from this study reveal that women in this part of Nigeria are
not following global trends and over-utilizing Cesareans, but are instead, struggling to
obtain adequate perinatal healthcare. Increasing access to safe and affordable obstetric
services is needed in this area of Nigeria to reduce the high maternal mortality.
Keywords: Nigeria, Cesarean, maternal mortality, malaria, education
144
BACKGROUND
Globally, the number of Caesarean sections (CS) has been on the rise over the last
decade (1, 2). The adverse maternal and perinatal outcomes when a CS is not medically
necessary have become a major public health concern and the associated expenses
decrease the resources available for other issues (3, 4). According to the World Health
Organization (WHO), CS rates between 5-15% are considered optimal as a lifesaving
intervention for mothers and their neonates (1, 5, 6). Lower rates suggest an overall lack
of access to health care, and higher rates indicate an overutilization of the procedure (1).
Of particular concern in most of Africa is underutilization of CS, with regional estimates
varying from 1.8% in Central Africa, 1.9% in Western Africa, 2.3% in Eastern Africa,
7.6% in Northern Africa, and 14.5% in Southern Africa (5). Low percentages in central,
western, and eastern Africa indicate difficulty accessing adequate maternal health care.
Although most African countries have hospitals with surgical services available to
perform CS, a plethora of individual and health system characteristics impede access and
contribute to the delay in women seeking services during pregnancy. Thaddeus and
Maine (1994) developed the “three-delay” model that has been widely accepted as a
framework to explain the obstacles in obtaining adequate healthcare during pregnancy
(7). This three-tiered framework includes: delay in decisions to seek care, delays in
arrival at a healthcare facility, and delays in receiving adequate treatment for obstetric
complications.
In sub-Saharan Africa (SSA), delayed access to healthcare services during
pregnancy and delivery can be influenced by multiple factors. Lack of knowledge of the
importance of perinatal care and an inability to pay for healthcare services are common
145
reasons for delaying healthcare utilization (7). Women also delay seeking treatment
during pregnancy because of poverty, gender inequalities in household decision-making,
cultural barriers, and geographical and transport barriers (7). Increased age, education and
wealth are all positively associated with deciding to have a doctor present at delivery
within SSA (8, 9). When life threatening complications occur during labor, delays in
seeking adequate care can increase maternal mortality even when lifesaving CS is
utilized.
In 2013, Nigeria contributed the 2nd largest proportion of the global number of
maternal deaths and had the 11th highest crude birth rate- making it an important country
in which to study the barriers to obtaining adequate obstetric care (10, 11). More than
75% of all CS in Nigeria are linked to obstetric emergencies that could have been
prevented by earlier medical care (12). Even with birth plans in place, many Nigerian
women opt to deliver with an unskilled birth attendant in a setting other than a hospital
because of barriers to seeking treatment, such as cost and geographical/transportation
difficulties (7, 12, 13). Cultural factors such as gender inequalities and the cultural
acceptance of home deliveries compared to hospital deliveries also influence a woman
delivering at a healthcare facility (14). Delays in seeking treatment results in women
attempting to access care at healthcare facilities only after life-threatening complications
develop. Increasing access to obstetrics care, such as CS, decreases maternal and infant
morbidity and mortality (15, 16). However, fears associated with having a CS further
delay a woman’s decision to seek treatment. Common fears associated with having a CS
in Nigeria include: cultural beliefs that vaginal birth is a confirmation of womanhood,
stigma from fear of being mocked by other women, death, violation of religious beliefs,
146
post-operative pain, future infertility, expense, and medical incompetence (17-19). A
woman’s socioeconomic status also influences access to CS, with the richest women, as
measured by wealth index, having better access to CS compared to the poorest
women(6). Education and age are also strong predictors of a woman’s willingness to have
a CS in Nigeria [14, 15]. Women who are either younger or less educated are more likely
to refuse a CS even when it is medically necessary from concerns about the expense (9,
20, 21).
Even women who do attempt to access healthcare facilities during delivery, often
encounter untrained personnel and a lack of proper equipment and supplies (9). Most
studies evaluating pregnancy outcomes in Nigeria equate having a doctor present at
delivery to having access to quality healthcare. However, this metric may not be an
accurate predictor of the facility’s ability to perform a CS. Many healthcare facilities
within Nigeria cannot offer a CS, and ambulance services are virtually non-existent (22).
In fact, one study demonstrated that only 1 in 21 health facilities in Nigeria is equipped to
perform CS (23). This complicates the ability of pregnant women to obtain adequate
healthcare during pregnancy.
In 2013, Nigeria contributed 14% (n=40,000) of the global number of maternal
deaths (10). In order to meet the Millennium Development Goals to decrease maternal
mortality an increase in access to lifesaving obstetric measures such as CS is needed (15,
16, 24). Examining factors associated with having a CS will help provide insight into
ways to increase access to healthcare during pregnancy. In addition, socioeconomic and
comorbid conditions are often not examined together when exploring the factors
associated with CS in Nigeria. Therefore, the aims of this paper were two-fold: 1) to
147
establish the rates of CS in Enugu State, Nigeria; and 2) to determine socioeconomic or
medical risk factors associated with having a CS in Enugu State, Nigeria.
148
METHODS
Survey: Data for this study were derived from the Healthy Beginnings Initiative
(HBI) cohort, which has been described in detail elsewhere (25). In Nigeria,
approximately 35% of pregnant women deliver at a healthcare facility; therefore, a
community-based sampling technique was employed to obtain a more representative
sample of pregnant women (26). Pregnant women were recruited from churches in Enugu
State, Nigeria. This strategy was expected to provide a representative sample of pregnant
women in the state, as the population is more than 95% Christian and church attendance
approaches 90% (25). Women interested in the study were asked to read and sign a
consent form in either English or the local language, Ibo. If the participant was illiterate,
the consent form was read aloud to her in the local language; then, the participant gave
her consent by affixing her thumb print, as an indication of consent to participate in the
study (25). Participant demographic characteristics were obtained from 2317 women at
baseline via a semi-structured questionnaire written at a 6th grade reading level (25).
Trained research staff and church-based health advisors administered the survey.
Participants had the option of reading the survey themselves or having study personnel
read to them. Because of inherent risks associated with having multiples (i.e. twins,
triplets etc.), only singleton deliveries of women between the ages of 17-45 at baseline
were retained for this analysis. Post-delivery questionnaires were used to ascertain the
mode of delivery, i.e., CS or vaginal birth, and the infant’s gender. Gravidity was
dichotomized as primigravida and multigravida.
Laboratory Measures: Variables assessed by laboratory tests were hemoglobin,
malaria parasitemia, human immunodeficiency virus (HIV), and sickle cell disease/trait
149
(SCD). Participants were tested for each laboratory measure either at baseline following
recruitment into the study or during their prenatal visits, whereupon records were
obtained from the participant’s corresponding hospital.
Hemoglobin was assessed using the standard cyanmethemoglobin method (27).
Drabkins solution (Ranjo Medix Laboratories, Lagos, Nigeria) with a pH of 7-7.4 was
measured at 5 ml and dispensed into a glass test tube. Whole blood was pipetted into the
Drabkins solution and allowed to sit at room temperature away from sunlight for 5
minutes. The Drabkins fluid was then read using 540 nm in a spectrophotometer to
estimate the hemoglobin concentration. WHO guidelines for anemia were employed (28),
and pregnant woman were classified as anemic if they had a hemoglobin level below
11g/dl.
Peripheral parasitemia levels were assessed using the malaria plus system (29).
Thick blood smears were examined via oil immersion under microscopy (29). Each slide
was carefully read by two experienced laboratory technicians; a third technician was
utilized to rectify any disparate results. Because results indicated that 99% of this sample
showed malaria parasitemia, malaria parasitemia was reclassified as low and high based
on the malaria plus system with those in the 0 and + group classified as low parasitemia
and those in the ++ and +++ groups classified as high parasitemia.
HIV testing was performed using the Rapid Testing Serial Algorithm II
(30). For this procedure, two concurrent HIV rapid tests, Uni-Gold Recombigen (UniGold; Trinity Biotech, Inc., Wicklow, Ireland) and Stat Pak (Chembio Diagnostic
Systems Inc., Medford, New York, USA) were used. Both Uni-Gold and Stat Pak are
single-use immunochromatographic tests that detect HIV antibodies. Uni-Gold is used for
150
the detection of HIV-1; while Stat Pack can detect HIV-1 and -2. Both tests are
performed by collecting whole blood from a finger stick that is placed on a test strip.
Next, the test strip was placed in the testing device and a wash solution that is unique to
each test, was added. Uni-Gold was set aside for 10-12 minutes and then read by a
technician; Stat-Pak was read after 15-20 minutes. If both tests were positive for HIV, the
individual was considered HIV positive; if both tests were negative, the individual was
considered HIV negative. When the tests showed conflicting results, they were both
repeated and the results were read by another technician, who did not know the results of
the first series of tests.
EDTA-treated venous blood samples were used to screen for SCD. Cellulose
acetate electrophoresis at pH 8.5 – 9.0 was used. Hemolysates were prepared by lysing
saline-washed, packed red cells in 13mM EDTA, 10.7mM KCN solution using a 1:4
ratio. Tris-EDTA-borate buffer with cellulose acetate strips were used to perform
electrophoresis. Each strip contained one microliter of a patient hemolysate and a
microliter of a control hemolysate containing hemoglobin A, S, and C. Electrophoresis
was performed at a constant power of 350V for 30 minutes or longer if maximum band
separation was not observed. Each strip’s band separations were compared to the control
genotypes: AA, AS, SS, and SC. To decrease the chances of a false positive or negative
of SCD, each sample was tested twice. If incongruent results occurred, the test was
rerun.
Statistical Methods: Univariate analyses were based on Pearson's Chi-square test
for comparison of proportions for all variables. Fisher's exact tests for contingency tables
were used to test for significance in proportions when the expected cell counts were less
151
than 5. Chi-square analyses with p<0.10 were further analyzed using crude and adjusted
logistic regression with CS as the main outcome. Having a CS in previous pregnancies is
known to predict current CS; therefore, gravida was included in logistic regression
models. Because no information was collected specifically regarding previous CS, a
sensitivity analysis was performed among those experiencing their first pregnancy.
Statistical significance was set at p< 0.05. An adjusted trend in the Odds Ratio (OR) was
conducted to determine whether an increasing trend in the odds of having a CS occurred
as a participant’s age and education level increased by using the “tabodds” function in
Stata [Stata Corporation, College Station, TX]. Participant’s age was categorized as 1524, 25-34, and 35-45. Only one women who had a CS had no formal education; therefore,
education was categorized as none/primary, secondary and tertiary and above. Age and
education were retained as categorical variables for inclusion in multivariable models.
Birthweight was collected as part of the parent study; however, because it was selfreported and most newborns were not weighed at birth, birthweight was not deemed
reliable. Therefore, birthweight was not included in this analysis. Data analyses were
conducted using Stata version 12.0. The parent study was approved by the Institutional
Review Board of the University of Nevada, Reno, and the Nigerian National Health
Research Ethics Committee. This secondary data-analysis was considered exempt from
human subjects review by the Mel and Enid Zuckerman College of Public Health
Research Office.
152
RESULTS
As shown in Table 1, 167 (7.2%) women had CS and 2150 (92.8%) had vaginal
deliveries. A woman’s age was statistically associated with having a CS (p<0.01), with a
greater percentage of women aged 35-45 having had a CS (11.1%) than women aged 2534 (7.5%) or 15-24 (3.2%). Education was statistically associated with having a CS
(p<0.01), with a greater percentage of women with tertiary education having had a CS
(15.1%) than those with a secondary education (6.0%) or a primary education or less
(4.9%). Employment status was also statistically associated with having a CS (p=0.03);
women with full-time employment had higher percentages of CS than women who
worked part time or who did not indicate they were currently employed (8.7%, 5.0, and
7.1%, respectively). Area of residence (i.e., rural vs urban), was significantly related to
having a CS (p<0.01) with more women in urban settings having a CS (12.2%) compared
to women in rural settings (5.5%). A mother’s baseline malaria parasitemia was
significantly associated with having a CS (p=0.02); higher percentages of women who
had high malaria parasitemia at baseline had a CS than women who displayed low levels
of malaria parasitemia (8.9% vs 6.0%, respectively). Infant’s gender was statistically
associated with CS (p=0.01), with a higher rate of CS occurring when mothers delivered
male (8.6%) than female infants (5.9%). No significant relationship was observed
between CS and number of people in the household, gravidity, distance to nearest
healthcare facility, marital status, HIV, sickle cell disease (SCD), or anemia. When
analyses were restricted to women who had not had a prior pregnancy (n=334), 7.8%
(n=26) had CS and 92.2% (n=308) had vaginal deliveries (Table 1). Among primigravida
women, living in an urban environment was significantly related to having a CS (p<0.01)
153
with 14.3% of urban women having a CS compared to only 5.1% of rural women. No
other participant characteristics were significant predictors of having a CS among
primigravida women.
Table 2 presents the crude and adjusted odds ratios (95% CIs) for having had a
CS or a vaginal birth by participant characteristics. The adjusted models showed that,
compared to women aged 15-24, the odds of having a CS were higher when the mother
was aged 25-34 years (adjusted OR (aOR): 2.01; 95% CI: 1.04-3.90) and when the
mother was aged 35-45 years (aOR: 2.73; 95% CI: 1.26-5.92; p-trend <0.01). Compared
to those with a primary school education or less, the odds of having a CS were higher if
the mother had at least a tertiary education (aOR: 2.91; CI: 1.54-5.53), but not if she had
a secondary education (aOR: 1.27; CI: 0.73-2.30; p-trend <0.01). The odds of having a
CS were significantly lower if participants were employed part-time compared to fulltime (aOR: 0.56; CI: 0.32-0.97). Compared to women who lived in an urban setting,
those who lived in a rural setting had a significant reduction in the odds of having a CS
(aOR: 0.58; CI: 0.38-0.89). Significantly higher odds of having a CS were seen among
those with high peripheral malaria parasitemia compared to those with low parasitemia
(aOR: 1.53; CI: 1.03-2.27). After adjustment for confounders, no relationship was found
between CS and number of people in the household, gravidity, marital status and not
being employed. Among primigravida women, adjusted logistic regression models
showed a significant relationship between woman living in an urban vs rural environment
and having a CS (aOR: 0.27; CI: 0.09-0.82). No other significant relationships were
found among primigravida women between having a CS and a woman’s baseline
characteristics or the gender of her infant.
154
DISCUSSION
Women in SSA continually face struggles in obtaining adequate obstetric care
during pregnancy. Increasing access to emergency obstetrics care, such as CS, decreases
maternal and infant morbidity and mortality (15, 16). Nigeria has one of the fastest
growing populations in the world, making it a key location to study access to healthcare
in pregnancy. Overall results indicate that 7.2% of women in Enugu State, Nigeria had a
CS while 92.8% had a vaginal delivery. Percentages of CS increased as maternal age
and/or education increased. Compared to women who had a full-time position, women
who worked part-time had 44% lower odds of having a CS after adjustment for potential
confounders. Likewise, significantly lower odds of having a CS was observed among
women who live in a rural setting compared to those who reside in an urban setting in
both the full sample and among primigravida women. After adjustment for confounding,
this study demonstrated 53% higher odds of having a CS if participants had high
peripheral malaria parasitemia compared to those with lower peripheral malaria
parasitemia.
The present work demonstrated higher percentages of CS in older women and
those with more education. In SSA, education has been shown to be a strong predictor of
using professionally-assisted delivery services (8, 31). Older and more educated women
in SSA are thought to be more confident and influential in their household decisionmaking, including the use of healthcare services (8, 32). Likewise, women with more
education and/or women who are employed often have greater control over family
resources and play a larger part in reproductive decision-making (14, 32, 33). These
155
variables may be a proxy of a woman’s ability to access healthcare, thereby increasing
her chances of having had a CS.
The relationship between infant gender and having a CS has been well
documented in developed countries and has only recently been studied in Africa (34). In
Libya, male fetuses were associated with higher odds of maternal diabetes mellitus,
preterm delivery, needing instruments when a vaginal delivery was performed, and
having CS compared to female fetuses (35). In our study, being pregnant with a boy may
have been associated with these pregnancy complications; however, these variables were
not measured in our survey. Nonetheless, because women in this part of Nigeria were
unlikely to have an ultrasound to determine the gender of their infants, the results of our
study add to the literature that suggests that the relationship between CS and male infants
is not culturally based (35). The biological basis of the relationship between being
pregnant with a male fetus and higher odds of having a CS is unclear and warrants further
attention (35).
Although the results herein did not demonstrate an association between distance
to nearest health facility and having had a CS, a statically significant relationship between
living in rural vs urban environments was demonstrated. In rural settings, distance has
consistently been an important barrier to seeking healthcare (7, 9, 36). It is possible that
in this self-report study, area of residence (i.e., rural vs urban) was an indirect assessment
of the ease of reaching a healthcare facility for childbirth. Women living in rural parts of
Enugu State, Nigeria - like women in other rural areas - may have had increased
difficulty accessing facilities that can perform a CS because of limited transportation
options, poor road conditions and poverty (7, 9, 14).
156
To the authors’ knowledge, this study is the first epidemiological investigation to
report that high malaria parasitemia is associated with higher odds of CS. The literature
and current guidelines are based on case studies (37-39). It is not known if a biological
pathway exists underlying this relationship or if women with higher malaria parasitemia
lack adequate health care overall, which inherently makes their pregnancies higher risk.
The relationship between malaria parasitemia and CS warrants further attention.
In SSA, some evidence has suggested that women with SCD are more likely to
have a CS (40, 41). However, it is difficult to determine whether those with SCD receive
any benefits from having a CS, because both SCD and CS are related to high risk of
adverse maternal and neonatal outcomes in SSA (41-43). It has been established that
malaria and SCD are associated with anemia during pregnancy (44-47). There has been
much debate in the literature whether anemia is related to an increase in maternal
morbidity and mortality in the context of developing countries (48). Having a CS would
complicate this relationship and warrants further attention.
Our study is consistent with a meta-analysis that found HIV-infected women were
no more likely to have a CS than those not infected (49). Evidence from resource
unconstrained areas suggests that having a CS is beneficial if a woman’s HIV-RNA level
is above 1000 copies/ml near delivery (50). Because women in resource-constrained
areas are often unaware of their viral load before delivery, having a CS could be
beneficial for HIV-infected women (51). However, in resource-constrained areas, CS are
often unavailable and unsafe; therefore, the WHO guidelines do not currently recommend
HIV positive women in resource constrained regions have an elective CS (52). Instead
the WHO recommends that HIV positive women take 3 or more antiretroviral
157
medications in order to decrease mother to child transmission of HIV (53). The WHO
also recommends that infants receive antiretrovirals during the post-natal period if their
mother is HIV positive(53).
Practice and Policy
When medically necessary, CS are frequently lifesaving procedures;
however, risks associated with CS are often highest within African countries as medical
personnel may lack the training to perform a safe CS and lack proper equipment and
supplies (4, 9). In general, better perinatal health outcomes have been associated with CS
rates between 5%-15% (1, 3, 5, 6, 54). Although the rate of CS in our sample, 8.8%, fell
within the lower end of these parameters, the WHO has estimated that in 15.5% of
pregnancies in Nigeria, a CS is medically necessary (1). This is almost double the rate
found in our sample. Therefore, unlike in other parts of the world where discussion
centers on overutilization of CS (1), it is likely that in this area of Nigeria an overall
underutilization of CS occurs, particularly in rural settings where only 5.5% of all births
were delivered via CS.
Although many countries in SSA have healthcare facilities that can perform CS,
the quality of care within these clinics is neither consistent nor reliable (55). It is
estimated that less than 1% of individuals in western SSA have access to surgical care
that is safe, affordable and can be performed in a timely manner (56). Countries in SSA
suffer from an overall shortage of facilities equipped to perform such specialized
treatment; additionally, countries in SSA also suffer from a lack of skilled workers
capable of performing specialized medicine (7). Because previous research within
158
Nigeria showed that only 1 in 21 health facilities was equipped to perform CS (23), it is
likely that even if access to health clinics was increased, most clinics would not be
equipped to perform CS. Increasing access to doctors and nurses who can identify and
perform life-saving obstetric procedures is needed, especially in rural areas of Nigeria.
Strengths, Weaknesses and Future Research
This study is unique to the literature on CS in SSA, in that it explored the
relationship between CS and socio/demographic variables as well as different disease
statuses. This allowed us to capture a holistic understanding of risk factors associated
with CS in Nigeria. This study was not without its limitations. In the overall sample, the
reasons a woman had a CS were not established, nor was prior use of CS. An attempt
was made to control for prior CS by using the number of people in the household as well
as gravidity status as proxies for prior CS; however, it is unknown if this control method
was adequate. A sensitivity analysis was also performed using only primigravida women;
however, the number of women (N=26) that had a CS for their first pregnancy was small.
Therefore, significant relationships between CS and other variables may not have been
present in this study because of lack of power. Also, no follow-up occurred when women
did not attend post-natal interviews; therefore, it was not possible to determine the rate of
maternal mortality. Finally, it is unknown whether women in rural settings truly had
difficulty accessing a healthcare facility; perhaps more women in urban settings elected
to have a CS. Answering these questions is essential to understanding the barriers that
women face when seeking adequate perinatal care in Nigeria.
159
In conclusion, rates of CS remain substantially lower in Nigeria than WHO
estimates is needed (1). Findings from this study reveal that women in this part of SSA
are not following global trends and over-utilizing CS, but are instead, struggling to obtain
adequate perinatal healthcare, ultimately perpetuating the cycle of high maternal
mortality and gross health disparities seen in SSA.
Competing interests
The authors declare that they have no competing interests.
Authors’ contributions
JG wrote and conceptualized the frame work for the paper. EE is the principal
investigator for the grant. MO was the local investigator for HBI. CE assisted in the
conceptualization and development of the research protocol. AO, AO and NM were
research coordinators in charge of participant recruitment, trial implementation and data
collection. JE, EJ, KE, SP, and EE provided input and feedback during the planning,
analyses and framework for the paper. All authors read and approved the final version of
the manuscripts.
Acknowledgments
The Healthy Beginning Initiative was funded by the Eunice Kennedy Shriver
National Institute of Child Health and Human Development (NICHD), the National
Institute of Mental Health (NIMH) and the President’s Emergency Plan for AIDS Relief
(PEPFAR) under award number R01HD075050 to Echezona Ezeanolue, MD. Additional
160
support for this study was provided by the Healthy Sunrise Foundation. The funding
agencies played no role in the study conception, design, data collection, data analysis,
data interpretation or writing of the report. We are grateful to the Catholic Bishop of
Awgu diocese, Anglican Bishop of Enugu; Catholic Bishop of Enugu; Anglican Bishop
of Oji-River. Their support was instrumental to the successful implementation of HBI.
HBI implementation would not have been possible without the support and tireless effort
of the priests in the participating churches. The church-based Volunteer Health Advisors
took ownership of the program and made the process of recruitment and implementation
smooth for our study team and participants. This study would have been impossible to
conduct without the support of PeTR-GS (our PEPFAR-supported partner) staff and
volunteers.
161
REFERENCES
1. Gibbons L, Belizán JM, Lauer JA, Betrán AP, Merialdi M, Althabe F. The global
numbers and costs of additionally needed and unnecessary caesarean sections
performed per year: overuse as a barrier to universal coverage. World health
report. 2010;30:1-31.
2. Roberts CL, Nippita TA. International caesarean section rates: the rising tide. The
Lancet Global Health. 2015;3(5):e241-e2.
3. Althabe F, Belizán JM. Caesarean section: the paradox. The Lancet.
2006;368(9546):1472-3.
4. Souza JP, Gülmezoglu A, Lumbiganon P, Laopaiboon M, Carroli G, Fawole B, et al.
Caesarean section without medical indications is associated with an increased risk
of adverse short-term maternal outcomes: the 2004-2008 WHO Global Survey on
Maternal and Perinatal Health. BMC medicine. 2010;8(1):71.
5. Betrán AP, Merialdi M, Lauer JA, Bing‐Shun W, Thomas J, Van Look P, et al. Rates
of caesarean section: analysis of global, regional and national estimates.
Paediatric and perinatal epidemiology. 2007;21(2):98-113.
6. Ronsmans C, Holtz S, Stanton C. Socioeconomic differentials in caesarean rates in
developing countries: a retrospective analysis. The Lancet. 2006;368(9546):151623.
7. Thaddeus S, Maine D. Too far to walk: maternal mortality in context. Social science &
medicine. 1994;38(8):1091-110.
8. Burgard S. Race and pregnancy-related care in Brazil and South Africa. Social science
& medicine. 2004;59(6):1127-46.
9. Gabrysch S, Campbell OM. Still too far to walk: literature review of the determinants
of delivery service use. BMC pregnancy and childbirth. 2009;9(1):34.
10. WHO U. UNFPA, The World Bank, United Nations Population Division. Trends in
maternal mortality: 1990 to 2013. Estimates by WHO, UNICEF. UNFPA, The
World Bank and the United Nations Population Division. Geneva: World Health
Organization; 2014.
11. Bank TW. Birth rate, crude (per 1,000 people) 2015 [June 2, 2015]. Available from:
http://data.worldbank.org/indicator/SP.DYN.CBRT.IN?order=wbapi_data_value_
2013+wbapi_data_value+wbapi_data_value-last&sort=desc.
12. Onoh RC, Eze JN, Ezeonu PO, Lawani LO, Iyoke CA, Nkwo PO. A 10-year
appraisal of cesarean delivery and the associated fetal and maternal outcomes at a
teaching hospital in southeast Nigeria. International Journal of Women's Health.
2015;7:531.
162
13. Onah H, Ugona M. Preferences for cesarean section or symphysiotomy for obstructed
labor among Nigerian women. International Journal of Gynecology & Obstetrics.
2004;84(1):79-81.
14. Babalola S, Fatusi A. Determinants of use of maternal health services in Nigerialooking beyond individual and household factors. BMC Pregnancy and
Childbirth. 2009;9(1):43.
15. Cross S, Bell JS, Graham WJ. What you count is what you target: the implications of
maternal death classification for tracking progress towards reducing maternal
mortality in developing countries. Bulletin of the World health Organization.
2010;88(2):147-53.
16. Bhutta ZA, Chopra M, Axelson H, Berman P, Boerma T, Bryce J, et al. Countdown
to 2015 decade report (2000–10): taking stock of maternal, newborn, and child
survival. The Lancet. 2010;375(9730):2032-44.
17. Sunday-Adeoye I, Kalu C. Pregnant Nigerian women’s view of cesarean section.
Nigerian journal of clinical practice. 2011;14(3):276-9.
18. Olofinbiyi B, Olofinbiyi R, Aduloju O, Atiba B, Olaogun O, Ogundare O. Maternal
views and experiences regarding repeat Caesarean section. Nigerian journal of
clinical practice. 2015;18(4):489.
19. Jeremiah I, Nonye-Enyidah E, Fiebai P. Attitudes of antenatal patients at a tertiary
hospital in Southern Nigeria towards caesarean section. Journal of Public Health
and Epidemiology. 2011;3(13):617-21.
20. Aziken M, Omo-Aghoja L, Okonofua F. Perceptions and attitudes of pregnant women
towards caesarean section in urban Nigeria. Acta obstetricia et gynecologica
Scandinavica. 2007;86(1):42-7.
21. Olusanya B, Alakija O, Inem V. Non-uptake of facility-based maternity services in an
inner-city community in Lagos, Nigeria: an observational study. Journal of
biosocial science. 2010;42(03):341-58.
22. Akinola OI, Fabamwo AO, Tayo AO, Rabiu KA, Abisowo OY, Alokha ME.
Caesarean section-an appraisal of some predictive factors in Lagos Nigeria. BMC
pregnancy and childbirth. 2014;14(1):217.
23. Shah A, Fawole B, M'Imunya JM, Amokrane F, Nafiou I, Wolomby J-J, et al.
Cesarean delivery outcomes from the WHO global survey on maternal and
perinatal health in Africa. International Journal of Gynecology & Obstetrics.
2009;107(3):191-7.
24. Wylie BJ, Mirza FG. Cesarean delivery in the developing world. Clinics in
perinatology. 2008;35(3):571-82.
163
25. Ezeanolue EE OM, Yang W, Obaro SK, Ezeanolue CO, Ogedegbe GG. Comparative
effectiveness of congregation-versus clinic-based approach to prevention of
mother-to-child HIV transmission: study protocol for a cluster randomized
controlled trial. Implementation Science 2013;8(1):62.
26. Adebami OJ, Owa JA, Oyedeji GA, Oyelami OA, Omoniyi-Esan GO. Associations
between placental and cord blood malaria infection and fetal malnutrition in an
area of malaria holoendemicity. The American journal of tropical medicine and
hygiene. 2007;77(2):209-13.
27. Drabkin DL, Austin JH. Spectrophotometric studies II. Preparations from washed
blood cells; nitric oxide hemoglobin and sulfhemoglobin. Journal of Biological
Chemistry. 1935;112(1):51-65.
28. Organization WH. Development of indicators for monitoring progress towards health
for all by the year 2000. 1981.
29. Organization WH. Basic laboratory methods in medical parasitology 1991
[September 1, 2014]. Available from:
http://www.who.int/malaria/publications/atoz/9241544104_part1/en/.
30. Organization WH. Guidelines for appropriate evaluations of HIV testing technologies
in Africa: US Department of Health and Human Services, Centers for Disease
Control and Prevention; 2006.
31. Mekonnen Y, Mekonnen A. Factors influencing the use of maternal healthcare
services in Ethiopia. Journal of health, population and nutrition. 2003:374-82.
32. Jejeebhoy SJ. Women's education, autonomy, and reproductive behaviour:
Experience from developing countries. OUP Catalogue. 1995.
33. Nwakoby BN. Use of obstetric services in rural Nigeria. The Journal of the Royal
Society for the Promotion of Health. 1994;114(3):132-6.
34. Hall MH, Carr-Hill R. Impact of sex ratio on onset and management of labour. BMj.
1982;285(6339):401-3.
35. Khalil MM, Alzahra E. Fetal gender and pregnancy outcomes in Libya: a
retrospective study. Libyan Journal of Medicine. 2013;8(1).
36. Say L, Raine R. A systematic review of inequalities in the use of maternal health care
in developing countries: examining the scale of the problem and the importance of
context. Bulletin of the World Health Organization. 2007;85(10):812-9.
37. Clearninghouse NG. The diagnosis and treatment of malaria in pregnancy. 2013.
Available from: http://www.guideline.gov/content.aspx?id=25670.
164
38. Wong RD, Murthy ARK, Mathisen GE, Glover N, Thornton PJ. Treatment of severe
falciparum malaria during pregnancy with quinidine and exchange transfusion.
The American journal of medicine. 1992;92(5):561-2.
39. Samanta S, Samanta S, Haldar R. Emergency caesarean delivery in a patient with
cerebral malaria-leptospira co infection: Anaesthetic and critical care
considerations. Indian journal of anaesthesia. 2014;58(1):55.
40. Wilson NO, Ceesay FK, Hibbert JM, Driss A, Obed SA, Adjei AA, et al. Pregnancy
outcomes among patients with sickle cell disease at Korle-Bu Teaching Hospital,
Accra, Ghana: retrospective cohort study. The American journal of tropical
medicine and hygiene. 2012;86(6):936-42.
41. Odum C, Anorlu R, Dim S, Oyekan T. Pregnancy outcome in HbSS-sickle cell
disease in Lagos, Nigeria. West African journal of medicine. 2001;21(1):19-23.
42. Muganyizi P. Determinants of adverse pregnancy outcomes among Sickle Cell
Disease deliveries at a tertiary hospital in Tanzania from 1999 to 2011. 2013.
43. Oteng-Ntim E, Meeks D, Seed PT, Webster L, Howard J, Doyle P, et al. Adverse
maternal and perinatal outcomes in pregnant women with sickle cell disease:
systematic review and meta-analysis. Blood. 2015:blood-2014-11-607317.
44. Huch R, Huch A. Erythropoietin in obstetrics. Hematology/oncology clinics of North
America. 1994;8(5):1021-40.
45. Huddle J, Gibson R, Cullinan T. The impact of malarial infection and diet on the
anaemia status of rural pregnant Malawian women. European journal of clinical
nutrition. 1999;53(10):792-801.
46. Organization TWH. Sickle cell disease prevention and control [April 29, 2015].
Available from: http://www.afro.who.int/en/clusters-a-programmes/dpc/noncommunicable-diseases-managementndm/programme-components/sickle-celldisease.html.
47. Gilles H, Lawson J, Sibelas M, Voller A, Allan N. Malaria anaemia and pregnancy.
Annals of tropical medicine and parasitology. 1969;63(2):245-63.
48. Bhutta ZA, Darmstadt GL, Hasan BS, Haws RA. Community-based interventions for
improving perinatal and neonatal health outcomes in developing countries: a
review of the evidence. Pediatrics. 2005;115(Supplement 2):519-617.
49. Calvert C, Ronsmans C. HIV and the risk of direct obstetric complications: a
systematic review and meta-analysis. PloS one. 2013;8(10):e74848.
50. Prevention CfDCa. HIV Among Pregnant Women, Infants, and Children 2014 [April
4, 2015]. Available from:
http://www.cdc.gov/hiv/risk/gender/pregnantwomen/facts/.
165
51. Buchanan AM, Cunningham CK. Advances and failures in preventing perinatal
human immunodeficiency virus infection. Clinical microbiology reviews.
2009;22(3):493-507.
52. Organization WH. Consolidated guidelines on the use of antiretroviral drugs for
treating and preventing HIV infection. Geneva: World Health Organization; 2013.
2013.
53. Organization WH. HIV/AIDS 2015 [cited May 14, 2015]. Available from:
http://www.who.int/mediacentre/factsheets/fs360/en/.
54. Althabe F, Sosa C, Belizán JM, Gibbons L, Jacquerioz F, Bergel E. Cesarean Section
Rates and Maternal and Neonatal Mortality in Low‐, Medium‐, and High‐Income
Countries: An Ecological Study. Birth. 2006;33(4):270-7.
55. Kwast BE. Quality of care in reproductive health programmes: Concepts,
assessments, barriers and improvements—an overview. Midwifery.
1998;14(2):66-73.
56. Alkire BC, Raykar NP, Shrime MG, Weiser TG, Bickler SW, Rose JA, et al. Global
access to surgical care: a modelling study. The Lancet Global Health. 2015.
166
Table1: Comparison of a participants baseline characterstics and infants gender with mode of delivery
Full Sample
Primigravida
C-Section
Vaginal Birth
C-Section
Vaginal Birth
N
%
N
%
P*
N
%
N
%
Total
167
7.2
2150
92.8
3.2
7.5
11.1
479
1317
354
96.8
92.5
88.9
4.9
6.0
15.1
578
1241
327
8.7
5.0
7.1
P*
26
7.8
308
92.2
0.00 a*
9
15
2
5.8
9.3
11.8
146
147
15
94.2
90.7
88.2
0.34 a
95.1
94.0
84.9
0.00 a*
3
11
12
6
5.5
14.1
47
188
73
94
94.5
85.9
0.053 a
781
536
818
91.4
95.0
93.1
0.03 a*
6
6
14
5.8
9.4
8.5
97
58
150
94.2
90.6
91.5
0.64
12.2
5.5
528
1617
87.9
94.5
0.00 a*
14
12
14.3
5.1
84
224
85.7
94.9
0.00*
High 59
Low 66
8.9
6.0
604
1027
91.1
94.0
0.02
a*
5
14
5.3
8.3
90
155
94.7
91.7
0.36
Male 102
Female 64
8.6
5.9
1085
1028
91.4
94.1
0.01
a*
13
13
7.8
7.8
153
152
92.2
92.2
0.99
8.7
8.2
5.8
324
845
967
91.3
91.9
94.2
0.07
14
11
1
7.5
11.6
2.1
174
84
46
92.6
88.4
97.9
0.15
7.8
7.0
308
1797
92.2
93.0
0.62
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
7.5
3.4
2010
140
92.5
96.6
0.07
3
23
5
8.4
57
251
95
91.6
0.59 a
753
817
872
93.3
93.1
91.8
0.52
9
10
7
8.1
8.5
6.7
102
108
97
91.9
90.8
93.3
0.88
3.3
7.2
59
1757
96.7
92.8
0.32
0
21
0
7.4
8
263
100
92.6
1.0 a
7.3
6.5
1273
357
92.7
93.5
0.62
5
14
9.4
6.6
48
197
90.6
93.4
0.55 a
Yes 53
8.3
589
91.7 0.16
7
7.2
90
No 72
6.5
1042 93.5
12
7.2
155
Notes: *Significance based on Pearson's Chi-square for Fisher's Exact, p<0.05 significant
a: Indicates p-value based on Fishers Exact
92.8
92.8
0.99
Mother's Age
15-24 16
25-34 107
35-45 44
Education
None /Primary 30
Secondary 79
Tertiary 58
Employment Status
Full-time 74
Part-time 28
None 61
Residence
Urban 73
Rural 94
Malaria Parasitemia
Infants Gender
Number of People in Household
1-2 31
3-4 75
5+ 60
a
Gravidy
Primigravida 26
Multigravida 136
Marital Status
Married 162
Other 5
Distance to Healtcare Facility
0-5km 54
9.7
5-10km 61
7.0
10+km 51
8.2
HIV status
Postive 2
Negative 137
Sickle Cell Status
AA-normal 100
AS/AC-carrier 25
Anemia
167
Table 2: Crude and logistic regression models of the odds of C-Section vs vaginal birth
Full Sample
Among Primigravida
Crude
Adjusted
Crude
N=1669
Mother's Age
15-24 Ref
Ref
Ref
25-34 2.43(1.42-4.16)*
2.01(1.04-3.90)*
1.65(0.70-3.90)
35-45 3.72(2.07-6.70)*
2.73(1.26-5.92)*
2.16(0.43-10.95)
Education
None/Primary Ref
Ref
Ref
Secondary 1.22(0.80-1.89)
1.27(0.73-2.30)
0.92(0.25-3.42)
Tertiary 3.42(2.15-5.42)*
2.91(1.54-5.53)*
2.58(0.69-9.61)
Employment Status
Full-time Ref
Ref
Ref
Part-time 0.55(0.35-0.86)*
0.56(0.32-0.97)*
1.67(0.52-5.43)
None 0.79(0.55-1.12)
0.80(0.52-1.25)
1.51(0.56-4.06)
Adjusted
N=256
Ref
0.85(0.23-3.10)
1.54(0.22-10.75)
Ref
0.57(0.13-2.58)
0.89(0.16-4.86)
Ref
1.72(0.43-6.85)
1.42(0.42-4.87)
Residence
Urban Ref
Rural 0.42(0.30-0.58)*
Ref
0.58(0.38-0.89)*
Ref
0.32(0.14-0.72)*
Ref
0.27(0.09-0.82)*
Malaria Parasitemia
High 1.52(1.05-2.19)*
Low Ref
1.53(1.03-2.27)*
Ref
0.62(0.21-1.76)
Ref
0.67(0.22-2.06)
Ref
1.18(0.80-1.75)
Ref
0.99(0.45-2.21)
Ref
0.86(0.32-2.32)
Ref
Ref
0.94(0.49-1.79)
0.58(0.29-1.16)
Ref
1.63(0.71-3.74)
0.27(0.03-2.11)
Ref
1.38(0.49-3.87)
0.37(0.04-3.14)
1.03(0.55-1.96)
Ref
N/A
N/A
N/A
N/A
0.57(0.17-1.98)
Ref
0.67(0.12-3.61)
Ref
Infants Gender
Male 1.51(1.09-2.09)*
Female Ref
Number of People in Household
1-2 Ref
3-4 0.93(0.60-1.43)
5+ 0.65(0.41-1.02)
Gravidity
Primigravida 1.15(0.72-1.73)
Multigravida Ref
Marital Status
Other 0.44(0.18-1.10)
0.93(0.32-2.71)
Married Ref
Ref
Notes: Models adjusted for other variables in the table
* Indicates significance at p<0.05
168
APPENDIX C
MANUSCRIPT 3
ABSTRACT
Background: Millennium Development Goal (MDG) 5 aims to reduce maternal
mortality. Nigeria has the second highest number of maternal deaths in the world.
Increasing access to emergency obstetric care, such as Cesarean Section (CS) , is largely
considered necessary to achieving MDG 5. Therefore, this paper aimed to estimate the
incidence of CS in Nigeria and to determine the socioeconomic and medical risk factors
that are associated with having a CS in Nigeria.
Methods: The Nigerian Demographic and Health Survey was utilized to carry out
this analysis. Weighted crude and adjusted logistic regression models were used to
explore factors that influence CS in Nigeria. Two separate analysis were performed, one
among all women in the dataset and one including only primigravida women.
Results: In the full sample, 2.3% of Nigerian women had CS; this rate was almost
double when the data was restricted to primigravida women (4.4%). In both groups,
women living in rural areas had significantly lower odds of having had a CS compared to
women living in urban areas. Also in both groups, Muslim women showed significantly
lower odds of CS compared to Catholic women (full sample OR 0.43: 0.28-0.73;
primigravida aOR 0.43: 0.19-0.96). Overall, 11,954 (67%) women did not deliver at a
healthcare facility. Cultural beliefs and barriers often influenced women not access a
healthcare facility during delivery in Nigeria.
169
Discussion: Rates of CS remain substantially lower in Nigeria than is
recommended by the World Health Organization, indicating an overall lack of access to
proper obstetric care. Our study demonstrated that women often delay seeking treatment
because of an inability to reach healthcare facilities, poverty, gender inequality and
cultural beliefs. Overcoming these delays in seeking treatment is needed to reach the
Millennium Development Goals.
170
BACKGROUND
The United Nations’ Millennium Development Goal (MDG) 5 sets out to improve
maternal health [1]. Specifically, world leaders aimed to reduce maternal mortality by
75% from 1990 to 2015 and achieve worldwide access to reproductive health services by
2015 [1]. Although great strides have been made in reducing global maternal mortality
from 546,000 deaths in 1990, an estimated 289,000 women still died in 2013 from
pregnancy and childbirth complications that are largely considered preventable [2, 3].
This is in addition to nearly 15-20 million that suffer various debilitating consequences of
pregnancy [4].
Sub-Saharan Africa (SSA) has historically carried a disproportionate
burden of adverse maternal and child health related outcomes [1], and has the highest
maternal mortality ratio (MMR) in the world. The region recorded an estimated 510
deaths for every 100,000 live births among women aged 15-49 years in 2013 [2].
Although this was a vast improvement from the 1990 estimate of 990 deaths per 100,000
live births, it is still more than double the ratio for any other region of the world [2]. In
order to meet MDG5 in SSA, vast improvements in facilities, infrastructure, and training
of skilled attendants were needed.
In 2013, Nigeria comprised40,000 (14%))of the global number of
maternal deaths, trailing only India (17 %) [2]. In the same year, the MMR in Nigeria
was 560 deaths per 100,000 live births, a 52% decrease in MMR from 1990 [2]. Although
this decrease in MMR was a remarkable progress towards the MDG, in 2013 the lifetime
risk of a pregnancy-related maternal death in Nigeria was 1 in every 29 women [5].
171
Women in Nigeria face a variety of obstacles while trying to obtain
adequate healthcare during pregnancy. Thaddeus and Maine (1994) describe a “three
delay” framework to explain the obstacles women face, including: delay in decision to
seek care, delay in reaching a healthcare facility, and delay in receiving adequate
treatment for obstetric complications [6]. These delays are mediated by a range of
sociodemographic, cultural, and economic factors. For example, gender inequality and
cultural acceptance of home deliveries are common reasons women delay seeking
treatment at a healthcare facility [6-9]. Costs associated with use of healthcare as well as
costs associated with transportation to healthcare facilities, are deterrents to accessing
healthcare during pregnancy in Nigeria [10]. Some Nigerian women report that the
financial burden of obstetric care is associated with a bad omen for the family; therefore,
they may fail to seek treatment at a healthcare facility even when complications during
labor arise [10]. Therefore, women may ultimately attempt to access healthcare facilities
only after life-threatening complications develop. As a result of these delays
approximately 75% of all Cesarean sections (CS) in Nigeria result from obstetric
emergencies that could have been prevented by early intervention [7].
Decreasing delays and increasing access to emergency obstetric care, such
as CS, was considered necessary for achieving MDG 5 [11, 12]. However, in Nigeria,
fears associated with having a CS— death, violation of religious beliefs, post-operative
pain, future infertility, cost, and medical incompetence —are commonly reported as
deterrents to seeking obstetric care during pregnancy [13, 14]. Even when life-threatening
pregnancy complications occurred, two-thirds of Nigerian women preferred a
symphsiotomy over a CS because of the fears associated with complications of a CS [8].
172
Symphysiotomy is a procedure that involves making an incision through the cartilage and
ligaments of a pelvic joint or in some cases, cutting the pelvis bone to widen it and allow
a baby to be delivered unobstructed. Socioeconomic, demographic, and cultural variables
coupled with high rates of comorbid medical conditions and cultural perceptions of
hospitals are all reasons why Nigeria has the second largest proportion of the global
maternal deaths [2] . In developing countries such as Nigeria, rates of CS are a vital
measure of a woman’s access to emergency obstetric services as they are often associated
with a decrease in maternal mortality [15, 16]. The aims of this paper were twofold: 1) to
estimate the incidence of CS among pregnant women in Nigeria, and 2) to assess the
socioeconomic and/or medical risk factors that are associated with having a CS in
Nigeria.
173
METHODS
Data Source and population: The data from this study were obtained from the
Demographic and Health Survey (DHS) conducted in Nigeria in 2013. Information
regarding the collection and sampling techniques employed by the DHS data have been
previously published in detail [17]. In brief, DHS utilized a cross-sectional design to
obtain nationally representative data [17]. The sampling frame used for Nigeria’s survey
was prepared using the 2006 Population Census data from the Federal Republic of
Nigeria provided by the National Population Commission [18]. The DHS is designed to
collect information on demographic, health and family planning variables. Data were
collected on a standard core set of questions; however, some surveys were individually
tailored for a specific country. Survey data were collected by trained personnel, with
participants verbally consenting. In total, 98% of the eligible women in the sampling
households were interviewed [18]. Three main datasets are available from DHS:
individual survey data, HIV test results and geographical data [19]. The results reported
here were form the individual survey data. The DHS collects information regarding any
pregnancy in the five years prior to the survey. In total, 19,655 women aged 15-49 years
had information regarding the mode of delivery (vaginal vs. CS) of their most recent
pregnancy. Because of the inherent risks associated with multiple births, only singleton
deliveries were retained for this analysis. A skilled birth attendant was defined using the
World Health Organization’s standard as an accredited health professional including a
doctor, nurse, or midwife [20]. Otherwise, the attendant was classified as an unskilled
birth attendant.
174
Statistical Analysis. Because select populations were oversampled, individual
weights provided by DHS were used as recommended [21]. Using weights allowed for
adjustment for nonresponse to questions, and made the data representative of the
underlying population on a national level. All data manipulation and analyses were
conducted in STATA version 12.0 [Stata Corporation, College Station, TX] using the
‘svyset’ command. The outcome variable used for this analysis was whether the most
recent birth was reported as a CS or a vaginal delivery. Weighted univariate analyses
were based on Pearson's Chi-square test for comparison of proportions for all variables.
Weighted crude and adjusted logistic regression with mode of delivery, i.e., vaginal or
CS-as the main outcome was performed. Weighted percentages were also performed for
reasons why women did not deliver at a healthcare facility. A sensitivity analysis was
performed among those experiencing their first pregnancy in order to determine if there
were any major differences in accessing care during a woman’s first pregnancy (n=3596).
Statistical significance of all tests are presented at p<0.05.
175
RESULTS
The results of the weighted chi-square are reported in Table 1. During their last
pregnancy, 2.3% of women had a CS and 97.7% had a vaginal delivery in Nigeria during
2008-2013. A statistically significant relationship between having a CS and the following
variables was demonstrated: and mother’s age (p<0.01), area of residence (p<0.01),
education (p<0.01), religion(p<0.01) , wealth index, difficult accessing a healthcare
facility(p<0.01), health insurance(p<0.01), prenatal care provider (p<0.01), skill level of
birth attendant (p<0.01), taking antimalarial medication (p<0.01), taking medication of an
intestinal parasite (p<0.04), being offered an HIV tests as part of prenatal care (p<0.01),
having a previous CS (p<0.01), taking iron supplements for at least half of pregnancy
(p<0.01), and geographical region (p<0.01). No significant association between the
gender of the infant and having a CS (p=0.22). Similar relationships were found among
primigravida women with the exception that no significant association was demonstrated
between taking medication for a parasite and having had a CS (p=0.20).
Table 2 presents results from weighted crude and adjusted odds ratios (95% CIs)
for mode of delivery by participant characteristics. In the full sample including both
multigravida and primigravida births, the adjusted model demonstrated that compared to
women who live in urban areas, the odds of having a CS were lower if women who lived
in rural settings (adjusted OR [aOR] 0.67: 95% 0.51-0.93). Compared to those with a no
education, the odds of having a CS were higher if the mother had at least a tertiary
education (aOR 2.71: 1.58-4.63) but not if she had a primary or secondary education
(aOR1.20: 0.76-1.90 and 1.54: 0.98-2.42 respectively). Compared to women who
practice Catholicism, lower odds of having a CS were demonstrated if the woman was
176
Muslim (aOR 0.46: 0.28-0.73). Women who had health insurance had higher odds of
having a CS compared to those without insurance (aOR 1.78: 1.18-2.67). Women who
received prenatal care from a skilled birth attendant had higher odds of having a CS
compared to women who did not received prenatal care (aOR 3.00: 1.51-5.96). Also,
women who had a CS during previous pregnancies had higher odds of having a CS
during their current pregnancy compared to women who had a previous vaginal delivery
(aOR 28.97:15.31-54.81). Compared to women in North Central Nigeria, women in the
North West had lower odds of having a CS (aOR 0.56:0.32-0.97). In the adjusted model,
no relationship was found between CS and taking prophylaxis malaria medication and
iron supplementation. Among primigravida women, compared to women who practice
Catholicism, lower odds of having a CS were demonstrated if the woman was Muslim or
practiced an alternative form of Christianity (aOR 0.54: 0.30-0.98 and aOR 0.43: 0.190.96 respectively). Compared to those with no health insurance, those with health
insurance had higher odds of having a CS (aOR 4.11: 1.97-8.54). In the adjusted models,
no other significant relationships were demonstrated.
Table 3 demonstrates the cultural beliefs and barriers that influenced
women not access a healthcare facility during delivery in Nigeria. Overall, 11,954 (67%)
women did not deliver at a healthcare facility. Cultural beliefs influenced many women’s
decision not to deliver at a healthcare facility with 34.5% of women reporting that it was
not necessary to deliver at a healthcare facility;8.1% reported their husbands family did
not allow them to access healthcare; 9.3% reported it is not customary to deliver at a
healthcare facility; 1.4% reported distrust of the healthcare facility; 0.5% reported that no
female provider was available at the healthcare facility; and 0.2% reported the they did
177
not like the attitude of the healthcare professional at the health facility. Physical and
financial barriers that influenced a woman’s ability to deliver at a healthcare facility
included: delivering too quickly (39.2%).;inadequate transportation (15.5%); and costs
associated with delivering at a healthcare facility (9.3%). Among primigravida women,
1760 (49%) did not deliver at a healthcare facility (Table 3). Cultural beliefs and physical
barriers were associated with accessing a healthcare facility in primigravida women in a
similar manner to the full sample.
178
DISCUSSION
Nigeria has the second highest MMR in the world in part because of
barriers women encounter in accessing adequate healthcare during pregnancy. In order to
reach MDG 5 by end of 2015, improved access to emergency obstetric care such as CS
should be provided to women who need it [11, 12]. The aims of this study were to
estimate the incidence of CS in Nigeria and to determine the socioeconomic,
demographic and medical risk factors associated with having a CS in Nigeria. In the
overall sample including both multi- and primigravida births, only 2.3% of women had a
CS. Women living in rural areas had 33% lower odds of having a CS compared to
women living in urban areas. After adjusting for potential confounders, women with a
tertiary education or higher had greater odds of having a CS compared to those with no
education. Religion was also significantly associated with having had a CS; Muslim
women had a statistically significant 54% lower odds of having a CS compared to
Catholics. Women with health insurance had a 78% increase in the odds of having a CS
compared to women without health insurance; while those offered HIV testing as part of
prenatal care had a 96% increase in the odds of having a CS compared to women who
were not.
Lower rates of CS among women living in rural environments have
consistently been reported because of barriers to seeking treatment, such as limited
transportation options and poor road conditions [6, 9, 22, 23]. Poverty plays a substantial
role in a woman’s ability to access a healthcare facility during delivery. In rural areas,
costs associated with having a CS as well as costs associated with transportation are
common reasons for not accessing a healthcare facilities during delivery [6-8]. In our
179
study, approximately 10% of all women reported costs as a deterrent to accessing a
healthcare facility during delivery. Furthermore, in this study, 17.3% of rural Nigerian
women indicated that they did not deliver at a healthcare facility because of
transportation difficulties, compared to less than 8.4% of urban women It is likely that
women in rural settings do not actively choose to not deliver at a healthcare facilitythereby decreasing their rates of CS-but are instead forced to deliver outside of a
healthcare facilities because of the barriers associated with living in a rural setting.
The present work also demonstrated higher odds of having a CS if women
had a tertiary education or higher compared to those with no education. Increasing
education in woman is an important step in achieving MDG 5. As education increases,
access to healthcare facilities grows, and maternal mortality often decreases [6, 24, 25].
Women with more education possess greater control over family resources and play a
larger role in their reproductive decision-making [9, 26, 27]. Karlsen et al.,[25]
demonstrated that among women who delivered at a healthcare facility, a relationship
between low education levels and high maternal mortality existed even after controlling
for potential confounders [25]. The importance of increasing access to primary school
education (MDG2) and eliminating gender inequalities in education (MDG 3) are both
substantial parts to achieving MDG 5.
To improve healthcare, the Nigerian government implemented the
National Health Insurance Scheme in 1999 [28]. However, numerous studies have
demonstrated that Nigerians continue to rely on direct payment to finance their healthcare
needs [29]. Less than 1% of women in this sample had health insurance. It is thought that
those who stated they had health insurance were more likely to have privately funded
180
health insurance and therefore, possessed the ability to financially afford a CS even if the
their insurance did not cover all the associated costs.
Ethnic and cultural diversity in Nigeria often vary by geographical
region[30]. The inner connectedness of geographical region and religion in Nigeria is
difficult to tease apart as the northern areas of Nigeria are predominately Muslim, while
the middle and southern regions are predominately Christian[30]. Our study
demonstrated lower odds of having a CS among Muslim women compared to Catholic
women. Our study showed that women in the northwestern part of Nigeria had lower
odds of having had a CS compared to the north-central area. This may be in part due to a
lack of access to skilled health providers in northern regions of Nigeria [9, 30]. Having a
skilled birth attendant available at delivery is necessary to perform a CS. Furthermore,
previous research has demonstrated that women living in northern parts of Nigeria have
lower rates of prenatal care and higher rates of home delivery[31]. With the percentage of
home deliveries ranging from 12% in southwest Nigeria to 86% in northwest Nigeria,
women in northern areas of Nigeria receive significantly less support from a skilled birth
attendant than their counterparts in southern Nigeria [31]. The vast majority of these
women have friends or relatives assisting with their delivery[31]. Cultural and religious
norms may dictate this relationship as some women in northern areas have restrictions in
seeking health-related assistance during childbirth, especially from male providers[30].
Attaining the Millennium Development Goals is especially difficult in the Northern parts
of Nigeria where poverty, illiteracy, and early marriage rates remain high among women,
and reproductive health and family planning are not historically women’s decisions [30].
Therefore, it is likely that women in the northern areas of Nigeria need better access to
181
reproductive health education and trained birth attendants and community health workers,
so that the symptoms associated with potential obstetric complications can be detected
before infant and/or maternal mortality ensues.
It is well documented in the literature that skilled birth attendants are
associated with a decrease in maternal mortality [32]. This study demonstrated that
compared to women who received no prenatal care, the odds of having a CS were
increased if a women received prenatal care from a skilled birth attendant but not if she
received prenatal care from an unskilled birth attendant. Training unskilled birth
attendants to recognizing some symptoms associated with the need for future emergency
obstetric services is essential. This is far from a novel idea, other research has indicated
that traditional birth attendants can be effective at implementing interventions that reduce
neonatal mortality in rural areas [33-36]. Further developing traditional births attendants
and community health workers skills could be effective at reducing recognizing early
warning signs to life threatening obstetric complications. It may be an essential way of
reducing mortality, especially in Northern Nigeria.
Practice and Policy
In order to meet the Millennium Development Goals, a decrease in maternal
mortality and worldwide access to reproductive health needed to be obtained [1].
However, this study demonstrated that 62% of all vaginal births occurred outside of a
healthcare facility. Delivering outside of a health facility and with an unskilled birth
attendant increases a woman’s chance of maternal mortality. The World Health
Organization has estimated that 15.5% of pregnancies in Nigeria need to have a CS
182
[37]—more than triple the rates found in this study. Therefore, unlike in other parts of the
world where discussion centers on overutilization of CS [37], this study demonstrated an
overall gross underutilization of the procedure in Nigeria. This may explain why Nigeria
accounts for half of the global burden of incident obstetric fistulas, which is caused by
prolonged labor and can be prevented with access to emergency obstetric services such as
a CS [24].
Although having access to health facility decreases maternal mortality, it does not
always equate to having adequate healthcare. Countries in SSA suffer from acute
shortage of facilities equipped to perform specialized treatment. In a survey of 77
hospitals in SSA only 6% reported the ability to provide safe anesthesia for a CS [38].
The anesthesiologist in these facilities reported that only 19% operated in facilities were
electricity was always available [38]. Only 56% of the facilities reported always having
access to running water and only 23% reported having access to blood for transfusion
[38]. Among individuals in western Africa, it is estimated that less than 1% have access
to surgical care that is safe, affordable and can be performed in a timely manner [39]. In
Nigeria, previous research demonstrated that only 1 in 21 health facilities were equipped
to perform CS [40]. Therefore, even if access to health clinics were increased, most
skilled birth attendants would not have the proper equipment to perform a safe CS.
Because many facilities lack water, electricity, medication, equipment and trained
personnel to perform CS, the operation is often associated with unacceptably high rates of
sepsis, hemorrhage and maternal death [15]. Therefore, increasing access to healthcare
facilities alone would not negate the problem, vast improvements in infrastructure and
training of skilled obstetricians needs to be made within SSA.
183
Strengths and Limitations
This study is unique to the literature in that it explored the relationship
between CS and socio/demographic variables as well as diseases while controlling for
geopolitical region. A sensitivity analysis was performed using only primigravida
women. In the unadjusted models, primigravida women showed similar trends in the OR
as the full sample. However, after adjustment, statistical significance in the primigravida
model diminished. It is possible that this study lacked statistical power because either
over-adjustment occurred in the primigravida model, or because a relatively small
number of women (N=170) had a CS for their first pregnancy; therefore, significant
relationships between CS and other variables may not have been found in this study.
This study is however not without its limitations. Although more women
who were offered HIV testing as part of prenatal care had a CS, the data does not permit
us to determine if this was from high rates of HIV among these women or if it was from
access to robust prenatal care. Likewise, it is unknown if women were taking iron
supplementation because of anemia or because they attended prenatal care. Many
socio/demographic and economic variables were significantly correlated but not highly
correlated. Although this indicates no collinearity between these variables in this dataset,
it is still difficult to determine if all models were over adjusted by including variables that
historically are related such and education and wealth index.
Conclusion
184
In conclusion, rates of CS remain substantially low in Nigeria than needed,
indicating an overall lack of access to adequate obstetric care [37]. Our study
demonstrated that women often delay seeking treatment because of an inability to reach
healthcare facilities, poverty, gender inequality and cultural beliefs. Overcoming these
delays in seeking treatment was needed to reach the Millennium Development Goals.
However, it is still apparent that women in Nigeria are not delaying seeking treatment out
of ignorance but are encountering real barriers that delay seeking treatment.
185
REFERENCES
1. Nations, U. Millennium Development Goals and Beyond 2015. Available from:
http://www.un.org/millenniumgoals/.
2. WHO, U., UNFPA, The World Bank, United Nations Population Division. Trends in
maternal mortality: 1990 to 2013. Estimates by WHO, UNICEF. 2014, UNFPA,
The World Bank and the United Nations Population Division. Geneva: World
Health Organization.
3. Zureick-Brown, S., et al., Understanding global trends in maternal mortality.
International perspectives on sexual and reproductive health, 2013. 39(1).
4. USAID, Improving Health for Women and Girls. 2015.
5. UNICEF. Table 8: Women. May 7, 2015]; Available from:
http://www.unicef.org/sowc2013/files/Table_8_Stat_Tables_SWCR2013_ENGLI
SH.pdf.
6. Thaddeus, S. and D. Maine, Too far to walk: maternal mortality in context. Social
science & medicine, 1994. 38(8): p. 1091-1110.
7. Onoh, R.C., et al., A 10-year appraisal of cesarean delivery and the associated fetal and
maternal outcomes at a teaching hospital in southeast Nigeria. International
Journal of Women's Health, 2015. 7: p. 531.
8. Onah, H. and M. Ugona, Preferences for cesarean section or symphysiotomy for
obstructed labor among Nigerian women. International Journal of Gynecology &
Obstetrics, 2004. 84(1): p. 79-81.
9. Babalola, S. and A. Fatusi, Determinants of use of maternal health services in Nigerialooking beyond individual and household factors. BMC Pregnancy and
Childbirth, 2009. 9(1): p. 43.
10. Asowa-Omorodion, F.I., Women's perceptions of the complications of pregnancy and
childbirth in two Esan Communities, Edo state, Nigeria. Social science &
medicine, 1997. 44(12): p. 1817-1824.
11. Cross, S., J.S. Bell, and W.J. Graham, What you count is what you target: the
implications of maternal death classification for tracking progress towards
reducing maternal mortality in developing countries. Bulletin of the World health
Organization, 2010. 88(2): p. 147-153.
12. Bhutta, Z.A., et al., Countdown to 2015 decade report (2000–10): taking stock of
maternal, newborn, and child survival. The Lancet, 2010. 375(9730): p. 20322044.
186
13. Sunday-Adeoye, I. and C. Kalu, Pregnant Nigerian women’s view of cesarean
section. Nigerian journal of clinical practice, 2011. 14(3): p. 276-279.
14. Olofinbiyi, B., et al., Maternal views and experiences regarding repeat Caesarean
section. Nigerian journal of clinical practice, 2015. 18(4): p. 489.
15. Wylie, B.J. and F.G. Mirza, Cesarean delivery in the developing world. Clinics in
perinatology, 2008. 35(3): p. 571-582.
16. Maine, D., et al., Guidelines for monitoring the availability and use of obstetric
services. 1997.
17. Survey, T.D.a.H. Data Collection. May 1, 2015]; Available from:
http://dhsprogram.com/data/data-collection.cfm.
18. Commission, N.P., Measure DHS II. Nigeria Demographic and Health Survey, 2013.
2013.
19. Surveys, D.a.H. Dataset Types. May 10, 2015]; Available from:
http://dhsprogram.com/data/Dataset-Types.cfm.
20. Safer, M.P., Making pregnancy safer: the critical role of the skilled attendant. 2004.
21. Surveys, T.D.a.H. Using Datasets for Analysis. May 1, 2015]; Available from:
http://dhsprogram.com/data/Using-DataSets-for-Analysis.cfm#CP_JUMP_14042.
22. Gabrysch, S. and O.M. Campbell, Still too far to walk: literature review of the
determinants of delivery service use. BMC pregnancy and childbirth, 2009. 9(1):
p. 34.
23. Say, L. and R. Raine, A systematic review of inequalities in the use of maternal
health care in developing countries: examining the scale of the problem and the
importance of context. Bulletin of the World Health Organization, 2007. 85(10):
p. 812-819.
24. UNFPA, E., Obstetric fistula needs assessment report: Findings from nine African
countries. New York: UNFPA EngenderHealth, 2003.
25. Karlsen, S., et al., The relationship between maternal education and mortality among
women giving birth in health care institutions: analysis of the cross sectional
WHO Global Survey on Maternal and Perinatal Health. BMC Public Health,
2011. 11(1): p. 606.
26. Jejeebhoy, S.J., Women's education, autonomy, and reproductive behaviour:
Experience from developing countries. OUP Catalogue, 1995.
27. Nwakoby, B.N., Use of obstetric services in rural Nigeria. The Journal of the Royal
Society for the Promotion of Health, 1994. 114(3): p. 132-136.
187
28. Scheme, N.H.I. National Health Insurance Scheme 2015; Available from:
http://www.nhis.gov.ng/index.php?option=com_content&view=article&id=47:we
lcome-note-from-executive-secretary&catid=34:home.
29. Onwujekwe, O., et al., Willingness to pay for community-based health insurance in
Nigeria: do economic status and place of residence matter? Health Policy and
Planning, 2010. 25(2): p. 155-161.
30. Reed, H.E. and B.U. Mberu, Ethnicity, Religion, and Demographic Behavior in
Nigeria, in The International Handbook of the Demography of Race and
Ethnicity. 2015, Springer. p. 419-454.
31. Erulkar, A. and M.V. Bello, The experience of married adolescent girls in northern
Nigeria. 2007: Citeseer.
32. Betrán, A.P., et al., National estimates for maternal mortality: an analysis based on
the WHO systematic review of maternal mortality and morbidity. BMC Public
Health, 2005. 5(1): p. 131.
33. Gill, C.J., et al., Can traditional birth attendants be trained to accurately identify
septic infants, initiate antibiotics, and refer in a rural African setting? Global
Health: Science and Practice, 2014. 2(3): p. 318-327.
34. Bang, A.T., et al., Simple clinical criteria to identify sepsis or pneumonia in neonates
in the community needing treatment or referral. The Pediatric infectious disease
journal, 2005. 24(4): p. 335-341.
35. Baqui, A.H., et al., Community‐based validation of assessment of newborn illnesses
by trained community health workers in Sylhet district of Bangladesh. Tropical
Medicine & International Health, 2009. 14(12): p. 1448-1456.
36. Khanal, S., et al., Community health workers can identify and manage possible
infections in neonates and young infants: MINI—a model from Nepal. Journal of
Health, Population and Nutrition, 2011: p. 255-264.
37. Gibbons, L., et al., The global numbers and costs of additionally needed and
unnecessary caesarean sections performed per year: overuse as a barrier to
universal coverage. World health report, 2010. 30: p. 1-31.
38. Hodges, S., et al., Anaesthesia services in developing countries: defining the
problems. Anaesthesia, 2007. 62(1): p. 4-11.
39. Alkire, B.C., et al., Global access to surgical care: a modelling study. The Lancet
Global Health, 2015.
40. Shah, A., et al., Cesarean delivery outcomes from the WHO global survey on
maternal and perinatal health in Africa. International Journal of Gynecology &
Obstetrics, 2009. 107(3): p. 191-197.
188
Table 1: Weighted chi-square of the socio-economic and medical factors associated with mode of delivery
Full sample
Primigravida
Cesarean
Vaginal
P
Cesarean
Vaginal
N Weighted % Weighted %
N Weighted % Weighted %
Total sample
19665
2.3
97.7
3596
4.4
95.6
Age
15-24
5095
1.6
98.4 <0.01*
2521
2.6
97.3
25-34
9197
2.4
97.6
1000
7.7
92.3
34-49
5373
2.7
97.3
75
2.1
78.6
Area of Residence
Urban
6532
4.4
95.6 <0.01*
1324
7.7
92.3
Rural 13133
1.1
98.9
2272
2.3
97.7
Education
None
8997
0.5
99.5 <0.01*
1173
1.2
98.8
Primary
3989
2.0
98.0
519
2.6
97.4
Secondary
5379
3.6
96.4
1510
5.2
94.8
Higher
1300
11.1
88.9
394
14.3
85.8
Religion
Catholic
1602
4.9
95.1 <0.01*
360
9.5
90.2
Other Christian
6466
4.3
95.7
1431
6.5
93.5
Islam 11303
1.0
99.0
1770
2.0
98.0
Wealth index
Poorest
4308
0.5
99.5 <0.01*
587
1.1
98.9
Poorer
4513
0.9
99.1
762
2.8
97.2
Middle
3955
1.4
98.6
748
3.0
97.0
Richer
3668
2.4
97.6
740
3.4
96.7
Richest
3221
7.2
92.9
759
10.5
89.5
Difficulty accessing a healthcare facility
No 13327
2.8
97.2 <0.01*
2533
5.3
94.7
Yes
6259
1.1
98.9
1048
1.9
98.1
Infant's Gender
Male
9966
2.4
97.6 0.2159
1825
5.3
94.7
Female
9699
2.1
97.9
1771
3.4
96.6
Health Insurance
No 19235
2.1
97.9 <0.01*
3505
4.0
96.0
Yes
354
11.7
88.3
77
27.0
73.0
Prenatal Care Provider
No Prenatal Care
6496
0.4
99.6 <0.01*
954
0.8
99.2
Unskilled birth attendant
1710
0.9
99.1
291
1.4
98.6
Skilled birth attendant 11299
3.6
96.4
2335
6.4
93.6
Delivered by:
Unskilled birth attendant 17601
0.6
99.3 <0.01*
3069
1.2
98.8
Skilled birth attendant
1974
16.1
83.9
513
22.4
77.6
Took Anti-Malaria Medication
No
9797
1.3
98.7 <0.01*
1674
2.4
97.6
Yes
9463
3.3
96.7
1851
6.1
93.9
Intestinal Parasite Medication
No 16015
2.1
97.9
0.04*
2888
4.1
95.9
Yes
2922
2.9
97.1
571
5.5
94.5
Offered HIV Test as part of Prenatal Care
No
5709
1.5
98.5 <0.01*
1028
3.1
96.9
Yes
6477
5.2
94.8
1429
8.5
91.5
Past CS
No 19548
0.07
99.3 <0.01*
N/A
N/A
N/A
Yes
117
50.9
49.1
N/A
N/A
N/A
Iron Supplementation for at Least Half of Pregnancy
No 10081
2.7
97.3 <0.01*
1971
97.6
Yes
8650
1.7
98.3
1452
93.9
Region
North Central
3027
2.5
97.5 <0.01*
601
5.2
94.8
North East
3946
1.1
98.9
613
1.8
98.2
North West
6088
0.6
99.4
898
1.4
98.6
South East
1669
4.0
96.0
377
7.2
92.9
South Central
2436
4.6
95.4
570
7.1
92.9
South West
2499
5.0
95.0
537
7.8
92.2
Notes: *Significance based on weighted Chi-Square p<0.05
P
<0.01*
<0.01*
<0.01*
<0.01*
<0.01*
<0.01*
0.02
<0.01*
<0.01*
<0.01*
<0.01*
0.2
<0.01*
N/A
<0.01*
<0.01*
189
Table 2: Weighted logistic regression the socio-economic factors associated with mode of delivery
Full Sample
Primigravida
Unadjusted
Adjusted
Unadjusted
Adjusted
N=17932
n=3580
Age
15-24 Ref.
Ref.
Ref.
Ref.
25-34 1.53 (1.59-2.03)* 0.85 (0.61-1.18)
3.03 (2.04-4.52)* 1.26 (0.74- 2.16)
34-49 1.69 (1.23-2.32)* 1.08 (0.76-1.54)
9.95 (4.86-20.36)*4.24(1.78-10.14)*
Area of Residence
Urban Ref.
Ref.
Ref.
Ref.
Rural 0.25(0.19-0.33)*
0.67 (0.51-0.93)*
0.28 (0.20-0.42)* 0.55 (0.32-0.94)*
Education
None Ref.
Ref.
Ref.
Ref.
Primary 3.79 (2.50-5.73)* 1.20 (0.76-1.90)
2.18 (0.96-4.94) 0.67 (0.27-1.69)
Secondary 7.06 (4.96-10.06)* 1.54 (0.98-2.42)
4.40 (2.47-7.83)* 1.15 (0.50-2.63)
Higher 23.63(16.0-34.81)* 2.71 (1.58-4.63)*
13.38 (7.19-24.90)*
1.54 (0.61-3.84)
Religion
Catholic Ref.
Ref.
Ref.
Ref.
Other Christian 0.88 (0.64-1.20)
0.80 (0.55-1.16)
0.66 (0.39-1.12) 0.54 (0.30-0.98)*
Islam 0.19 (0.13-0.27)* 0.46 (0.28-0.73)*
0.19 (0.11-0.33)* 0.43 (0.19-0.96)*
Wealth index
Poorest Ref.
Ref.
Ref.
Ref.
Poorer 1.77 (0.98-3.19)
0.83 (0.44-1.53)
2.50 (0.98-6.38) 1.37 (0.50-3.75)
Middle 2.73 (1.54-4.83)* 0.76 (0.42-1.39)
2.77 (1.09-7.01)* 0.76 (0.26-2.19)
Richer 4.58 (2.65-7.94)* 0.87 (0.46-1.65)
3.08 (1.23-7.72)* 0.55 (0.17-1.74)
Richest 14.5 (8.66-24.13)* 1.50 (0.77-3.90)
10.34 (4.45-24.16)*
0.87 (0.25-3.04)
Difficulty accessing a healthcare facility
No Ref.
Ref.
Ref.
Ref.
Yes 0.37 (0.27-0.51)* 0.90 (0.62-1.30)
0.35 (0.20-0.60)* 0.66 (0.37-1.18)
Health Insurance
No Ref.
Ref.
Ref.
Ref.
Yes 6.12 (1.29-8.73)* 1.78 (1.18-2.67)*
8.95 (4.77-16.80)*4.11(1.97-8.54)*
Prenatal Care Provider
No Prenatal Care Ref.
Ref.
Ref.
Ref.
Unskilled birth attendant 2.51(1.25-5.03)*
1.35 (0.59-3.08)
1.72 (0.56-5.28)* 0.72 (0.18-2.93)
Skilled birth attendant 10.45 (6.26-17.44)* 3.00 (1.51-5.96)*
8.53 (3.59-20.29)*2.93 (0.96-8.90)
Took Anti-Malaria Medication
No Ref.
Ref.
Ref.
Ref.
Yes 2.49 (1.91-3.24)* 1.28 (0.96-1.70)
2.65 (0.79-3.92) 1.41 (0.94-2.13)
Past CS
No Ref.
Ref.
N/A
N/A
Yes 51.20 (32.00-91.90)*28.97 (15.31-54.81)* N/A
N/A
Iron Supplementation for at Least Half of Pregnancy
No Ref.
Ref.
Ref.
Ref.
Yes 0.64 (0.49-0.83)* 1.20 (0.89-1.63)
0.67 (0.44-1.04) 1.07(0.68-1.68)
Region
North Central Ref.
Ref.
Ref.
Ref.
North East 0.45 (0.28-0.73)* 0.90 (0.54-1.50)
0.34 (0.17-0.69)* 0.68 (0.29-1.64)
North West 0.25 (0.15-0.42)* 0.56 (0.32-0.97)*
0.25 (0.22-0.52)* 0.58 (0.26-1.30)
South East 1.65 (1.11-2.44)* 0.78 (0.50-1.23)
1.40 (0.79-2.50) 0.71 (0.35-1.44)
South Central 1.89 (1.19-3.00)* 1.03 (0.67-1.59)
1.39 (0.79-2.42) 1.21 (0.65-2.27)
South West 2.07 (1.42-3.03)* 0.95 (0.65-1.37)
0.54 (0.90-2.66) 0.92(0.51-1.67)
Notes: *Significance based on weighted logistic regression pvalue <0.05
190
Table 3: Weighted percents of reasons why women did not healthcare facility to deliver
Full sample (n=11954) Primigravida (n=1760)
Yes
No
Yes
No
Not Necessary
34.5
65.5
30.1
69.1
Husbands family didn't allow
8.1
91.9
8.8
91.2
Not Customary
9.3
90.7
7.3
92.8
Delivered too quickly
39.2
60.8
40.4
59.7
Transportation
15.5
84.5
16.8
83.2
Cost
9.3
90.7
10.2
89.8
Facility Not Open
2.3
97.7
3.0
97.0
Distrust of healthcare facility
1.4
98.6
1.2
98.8
No female provider
0.5
99.5
0.7
99.3
Attitude of healthcare professional
0.2
99.8
0.1
99.9
191
APPENDIX D
MOTHER QUESTIONNAIRE
Program ID
Study Location: _________________________Date: ________________
PRE-DELIVERY QUESTIONS (collect during enrollment)
Demographics
Date of birth
DD / MM / YYYY
Sex
Ⱥ Female
Telephone number
Telephone number of close
relative
ȺMarried ȺSingle ȺDivorced ȺSeparated
ȺNone ȺPrimary ȺSecondary ȺTertiary
ȺFull time ȺPart time
ȺUnemployed
Marital status
Education level
Employment status
Occupation
Household income
Number of people in household
Area of residence
Distance to closest health facility
ȺUrban
ȺRural
Ⱥ0-5 km Ⱥ5-10 km Ⱥ10-15 km Ⱥ15+ km
Background Information
Have you ever been tested for
HIV?
If yes: date
ȺYes
ȺNo
ȺYes
ȺFear of
ȺNo
ȺFear of spousal ȺFear of
knowing result
rejection
DD / MM / YYYY
If no: Are you willing to get
tested?
If you are unwilling to get tested
for HIV what are your reasons?
(Check all that apply)
Are you aware of your sickle cell
trait status?
If yes: what is your trait?
spousal abuse
ȺSocial stigma ȺRecently tested ofȺPerception
no risk
ȺFear of associated shame if
ȺOther
positive
ȺYes
ȺNo
ȺAA (Normal) ȺAS (Carrier) ȺSS (Disease)
192
Mother Questionnaire
Program IDBBBBBBBBBBBBBBB
Study Location: _________________Date: _____________
General Health Questionnaire
We want to know how your health has been in general over the last few weeks. Please read the questions
below and each of the four possible answers. Circle the response that best applies to you. Thank you for
answering all the questions.
Have you recently:
1
2
3
4
1. been able to concentrate
better than
same as usual
less than usual
much less than
on what you’re doing?
usual
usual
2. lost much sleep over
worry?
Not at all
No more than
usual
Rather more than
usual
much more than
usual
3. felt that you are playing a
useful part in things?
more so than
usual
same as usual
less so than usual
much less than
usual
4. felt capable of making
decisions about things?
more so than
usual
same as usual
less than usual
much less than
usual
5. felt constantly under
strain?
Not at all
No more than
usual
Rather more than
usual
much more than
usual
6. felt you couldn’t overcome
your difficulties?
Not at all
No more than
usual
Rather more than
usual
much more than
usual
7. been able to enjoy your
normal day to day activities?
more so than
usual
same as usual
less so than usual
much less than
usual
8. been able to face up to
your problems?
more so than
usual
same as usual
less than usual
much less than
usual
9. been feeling unhappy or
depressed?
Not at all
No more than
usual
Rather more than
usual
much more than
usual
10. been losing confidence in
yourself?
Not at all
No more than
usual
Rather more than
usual
much more than
usual
11. been thinking of yourself
as a worthless person?
Not at all
No more than
usual
Rather more than
usual
much more than
usual
12. been feeling reasonably
happy, all things considered?
more so than
usual
same as usual
less so than usual
much less than
usual
13. been optimistic about the
future?
Not at all
No more than
usual
Rather more than
usual
much more than
usual
193
Mother Questionnaire
Program IDBBBBBBBBBBBBBBB
Study Location: _________________Date: __________
Mother Specific Questions (Only ask female participants)
Age at first pregnancy
Number of previous pregnancies
Past breastfeeding
ȺYes
Last menstrual period
DD / MM / YYYY
Are you receiving antenatal care?
ȺYes
What is your due date?
DD / MM / YYYY
Are you aware of the types of
female contraception
ȺYes
ȺNo
If yes: Are you interested in using
contraception in the future?
ȺYes
ȺOral
ȺNo
ȺIUD
If yes: What type
ȺNo
ȺNo
ȺInjections
If other: Please specify
Are you planning to circumcise your
baby if it is a boy?
ȺYes
ȺNo
ȺOther
194
Mother Questionnaire
Program IDBBBBBBBBBBBBBBB
Study Location: _________________Date: _______________
Laboratory Testing
(office use only)
Ⱥ Normal
Ⱥ Positive
Ⱥ Positive
Ⱥ Positive
Ⱥ Positive
ȺAS
Hemoglobin level
Malaria
RPR (Syphilis)
Hepatitis B
Hepatitis C
ȺAA
Sickle Cell Genotype
Ⱥ low
ȺNegative
ȺNegative
ȺNegative
ȺNegative
ȺSS
Ⱥ Unknown
Ⱥ Unknown
Ⱥ Unknown
Ⱥ Unknown
Ⱥ Unknown
ȺOther
If other: Please specify
HIV Test
Repeat HIV Test
ART Therapy Received during
Pregnancy
If yes, When initiated
ART Therapy Received during Labor
ART Therapy Received during
Breastfeeding
Recorded in Access Database:
ȺYes
Ⱥ Positive
Ⱥ Positive
ȺYes
Ⱥ1st Trimester
ȺYes
ȺYes
Ⱥ
ȺNegative
ȺNegative
ȺNo
Ⱥ2nd Trimester
ȺNo
ȺNo
Ⱥ N/A
Ⱥ N/A
Ⱥ N/A
Ⱥ3rd Trimester
Ⱥ N/A
Ⱥ N/A
No
Date Recorded: __________________________________________________________________________
Recorded by: ____________________________________________________________________________
Verified by: ______________________________________________________________________________
195
APPENDIX E
POST-DELIVERY QUESTIONNAIRE
Mother’s Name: ________________________ Date of Birth: ___________
Church ID: _________________
Mother Information
Mothers Phone Number:
Did mother receive antenatal care
If Yes, Where
How many antenatal visits
Was blood drawn for HIV test?
ȺYes
ȺTBA
ȺOnly one
ȺYes
ȺNo
ȺHealth Center
Ⱥless than 4
ȺNo
Ⱥ Unknown
ȺHospital
ȺMore than 4
Ⱥ Don’t know
If yes: Where was screening done
Pregnancy Outcome
Total Number of Children Alive
HIV Test Result:
ȺMiscarriage
ȺNormal Birth
Ⱥ
Mother
Died
ȺMother Alive
1 2 3 4 5 6 7 8 9 10
Ƒ3RVLWLYHƑ1HJDWLYH
ƑUnknown
196
POST-DELIVERY QUESTIONNAIRE
Mother’s Name: ________________________ Date of Birth: ___________ Church ID: _________________
Infant Information
Name of infant
Date of Birth
Location of birth
Mode of delivery
Infant’s gender
Infant’s weight
Gestational weeks at birth
Ⱥ Hospital
Center
ȺC/S
ȺFemale
Kg
Ⱥ Full-term
Was infant screened for HIV?
Baby Outcome
Ⱥ Health
Ⱥ Your Home Ⱥ TBA
ȺVaginal
ȺMale
ȺSingle
Ⱥ Pre-term
ȺYes
ȺTwin
ȺNo
ȺAlive
Ⱥ Don’t know
ȺDead
Comments:
Father Name:
Fathers Phone Number:
Was HIV test done?
Date of Birth:
Ⱥ
Yes
Ⱥ
No
Ⱥ Don’t know
If yes: Where was screening done
HIV Test Result:
ƑPositive
Ƒ1HJDWLYHƑUnknown
197
APPENDIX )
/$%25$725<0$18$/
WĞdZ hE/Y 'K>> ^Zs/^ͬEEhE/d/KE ^W/>/^d,K^W/d>͕DE
Eh'h>KZdKZzWZdDEd
TEST NAME; One Step Hepatitis B Surface antigen
test strip(serum/plasma)
DATE DUE FOR DATE
OF
REVIEW:
15/5/2013
15/5/2014
SOP
ISSUE:
AUTHORISED BY: AUTHOR(S):CHIDI,BENEDICTA,
REV SR CHUKWU SYLVIA, SUSSAN, OGECHUKWU
C.C
STATUS:CONTRO
LLED DOCUMENT
NUMBER OF PAGES: 2
OPERATORS:BML
S, MLT, MLA
LOCATION:MICROBIOLOGY
(SEROLOGY)
PRINCIPLE: The HBsAg one Step Hepatitis B surface Antigen test strip
(serum/plasma) is a qualitative lateral flow immunoassay for the detection of
HBsAg in serum or plasma. The membrane is pre-coated with anti-HBsAg
antibodies on the test line region of the strip. During testing, the serum or
plasma specimen reacts with the particle coated with anti-HBsAg antibody. The
mixtures migrate upwards on the membrane and generate a coloured line.
TEST PROCEDURE:
1. Allow test strip, serum/plasma and controls to equilibrate to room
temperature (15 -30OC) prior to testing.
2. Bring the pouch to room temperature before opening it. Remove the test
strip from the sealed pouch and use it as soon as possible. Best results
will be obtained if the assay is performed within one hour.
3. Immerse the test strip vertically in the serum/plasma for at least 10 – 15
seconds.
Note: do not pass the maximum line (max) on the test strip when
immersing the strip.
198
/$%25$725<0$18$/
4. Place the test strip on a non- absorbent flat surface.
5. Start the timer and wait for the red line(s) to appear.
Note: the result should be read at 15minutes.
Do not interpret results after 30 minutes.
INTERPRETATION OF RESULTS:
1. POSITIVE two distinct red lines appear, one line should be in the control
region (C) and another line should be in rest region (T)
Note: the intensity of the red colour in the test line region (T) will vary
depending on the concentration of HBsAg present in the specimen.
Therefore any shade of red in the test region (T) should be considered
positive.
2. NEGATIVE: One red line appears on the control region (C), no apparent
red or pink line appears in the test region (T).
3. INVALID: Control line fails to appear.
Insufficient specimen volume or incorrect procedural techniques are the
most likely reasons for control line failure.
Note: Review the procedure and repeat the test with a new strip.
If the problem persists, discontinue using the test kit immediately. Report to
the HOD.
PeTR
GLOBAL
UNIQE
SERVICES
/
ANNUNCIATION
SPECIALIST
HOSPITAL,
EMENE ENUGU LABORATORY DEPARTMENT
TEST NAME: Syphilis ultra rapid test
strip(whole blood/serum/plasma)
DATE DUE FOR DATE OF SOP ISSUE: 15/5/2013
REVIEW:15/5/20
14
AUTHORISED
AUTHOR(S):REV.SR.CHUKWU.C.C.CH
BY: CHUKWU IDI,BENEDICTA, SYLVIA, SUSSAN,
C.C
OGECHUKWU
STATUS:CONTR
NUMBER OF PAGES: 2
199
/$%25$725<0$18$/
OLLED
DOCUMENT
OPERATORS:
LOCATION:MICROBIOLOGY
BMLS,
MLT, (SEROLOGY)
MLA
PRINCIPLE: The syphilis ultra rapid test strip (whole blood/serum/plasma)
is a qualitative membrane strip based immunoassay for the detection of
Treponema Pallidum TP antibodies (igG and igM) in whole blood, serum or
plasma. In this test procedure, recombinant syphilis antigen is immobilized
in the test line region of the strip. After a specimen is added to the specimen
pad it reacts with syphilis antigen coated to the particles that have been
applied to the specimen pad. This mixture migrates chromatographically
along the length of the test strip and interacts with the immobilized syphilis
antigen. The double antigen test format can detect both igG and igM in
specimen
PROCEDURES:
1. Remove the test strip from the sealed foil pouch.
2. Use it as soon as possible.
(Best result will be obtained if the assay is performed within one hour)
3. Peel off the tape from the test card.
4. Stick the test strip in the middle of the test card with the arrows pointing
downwards.
5. Transfer 2 drops (approximately 50ml) of serum/plasma onto the
specimen pad of the test strip.
6. Add 40ul (1 drop) of buffer.
7. Start the timer.
8. Wait for the red line(s) to appear.
9. Read the result at 10minutes.
Note: do not interpret result after 30minutes.
200
/$%25$725<0$18$/
INTERPRETATION OF RESULT
1. Positive: Two distinct red lines appear. One line should be in the control
line region (C) and another line should be in the test line region (T).
Note: The intensity of the red colour in the test line region (T) will vary
depending on the concentration of Treponema Pallidum antibodies present in
the specimen. Therefore, any shade of red in the test line region (T) should
be considered positive.
2. Negative: One red line appears in the control line region(C). No apparent
red or pink line appears in the test region (T).
3. Invalid: Control line fails to appear.
Insufficient specimen volume or incorrect procedural techniques are the most
likely reasons for control line failure.
Note: Review the procedure and repeat the test with a new test kit immediately
and report to the HOD.
PeTR
UNIQUE
GLOBAL
SERVICES/ANNUNCIATION
SPECIALIST HOSPITAL, ENUGU LABORATORY DEPARTMENT
TEST: Examination of Blood for Malaria Parasite in Thick Film USING
GIEMSA STAIN (CAPILLARY BLOOD, WHOLE BLOOD)
DATE FOR REVIEW: 12/4/2014
DATE OF SOP ISSUE: 12/4/2013
AUTHORISED BY: REV SR AUTHOR(S): REV SR CHUKWU
CHUKWU C.C
C.C,
CHIDI
BENEDICTA,
FRANCISCA.
STATUS:CONTROLLED
DOCUMENT
OPERATORS:
MLT,MLA
LOCATION: HAEMATOLOGY
BMLS, NUMBER OF PAGES: 2
PRICIPLE OF THE TEST
201
/$%25$725<0$18$/
Malaria parasites in thick blood film require staining at PH 7.1 – 7.2 using
Rowmanwsky stain. (Contains azure dyes and eosin) e.g Giemsa stain. Thick
film helps to concentrate the malaria parasite more than thin film.
Giemsa Stain is alcohol – based Rowmanwsky stain. It should be diluted to
PH 7.1 -7.2 buffered water before use. It stains thick film well provided they
are completely dry (overnight drying is recommended). The concentration of
the Giemsa should be increased to reduce the staining time.
PROCEDURE
BLOOD COLLECTION:
1. (a) collect venous blood using vacutainer needle into EDTA tube, mix
gently and thoroughly or if using a capillary blood then.
(b) Cleanse the lobe of the finger (or heel if an infant). Using a swab
moistened with 70% alcohol, allow the area to dry.
(c) Use a sterile lancet, Prick the finger or heel.
(d) Squeeze gently to obtain a large drop of blood.
THICK FILM MAKING:
2. Using a completely clean frosted end grease free microscope slide, add a
large drop of blood at the centre of the slide.
3. Without delay, (using the end of a stick/tube) spread the large drop of
blood to make thick smear.
Note: cover evenly an area about 15x15mm.
It should just be possible to see (but not read) newsprint through the film.
4. Using a grease pencil or black lead pencil, label the slide with the patient
lab number/name.
5. Allow the blood film to air-dry with slide in a horizontal position and
placed in a safe place.
THICK FILM STAINING:
1. Immediately before use, dilute the Giemsa stain.
Note (i) 3% SOLUTION FOR 30 MINUTES STAINING
202
/$%25$725<0$18$/
Measure 50ml of buffered water (PH 7.1-7.2)
Add 1.5ml of Giemsa stain and mix gently.
(ii) 10% solution for 10minutes staining
Measure 45ml of buffered water (PH 7.1 – 7.2) in a 50ml cylinder.
Add 5ml of Giemsa stain (to 50ml mark) and mix gently.
2. Place the slides in a staining rack.
3. Flood the thick film with diluted Giemsa stain
(10minutes if using 10% stain solution)
4. Wash off the stain using clean water
(Need not be distilled water)
Note: flushing the stain from the slides is necessary to avoid the films
being covered with a fine deposit of stain.
5. Wipe the back of each slide clean and place in a draining rack for the
preparation to air-dry.
REPORTING OF BLOOD FILM FOR MALARIA PARASITE:
1. When the thick film is completely dry, apply a drop of immersion oil to
an area of the film which appears mauve coloured (usually around the
edges)
2. Spread the oil to cover an area about 10mm in diameter, (there is no need
to add a cover glass).
3. First use 10x and 40x as preliminary objectives, these will guide you on
where to focus 100x objectives.
Note: Blood films should be examined microscopically using 100x oil
immersion objectives because; these give a brighter and cleaner image.
4. Examine for malaria parasites. Use the chart placed on the wall to help
identify the parasites.
5. Using the plus sign scheme given, report approximate numbers of
parasites (trophpzites, schizontes and gametocytes).
PLUS SIGN SCHEME:
1 -10 Parasite per 100 High power field
+
203
/$%25$725<0$18$/
11 – 100 Parasite per 100 High power field
1 – 10 Parasite per High power field
++
+++
Over 10 parasite per High power field
++++
PeTR UNIQUE GLOBAL SERVICES /ANNUNCIATION
SPECIALIST
HOSPITAL,
ENUGU.
LABORATORY
DEPARTMENT
TEST:Hemoglobin
Estimation
Method) Whole (Blood in EDTA)
DATE FOR
REVIEW:
12/4/2014
(Cyanmethemoglobin
DATE OF SOP
ISSUE:
12/4/2013
AUTHORISED BY: REV SR AUTHOR(S):REV
SR
CHUKWU C.C
CHUKWU
C.C,
CHIDI
,BENEDICTA, GERALDINE
STATUS:CONTROLLED
DOCUMENT
LOCATION:
HAEMATOLOGY
OPERATORS: BMLS, MLT, NUMBER OF PAGES: 1
MLA
PRINCIPLE OF THE TEST
Whole blood is diluted 1 in 201 in a modified Drabkins solution, which
contains potassium ferricyanide and potassium cyanide. The red cells are
haemolysed and the haemoglobin is oxidized by the ferry cyanide to
methaemoglobin. This is converted by the cyanide to stable haemiglobincyanide
204
/$%25$725<0$18$/
(HiCN). Absorbance of the HiCN solution is read in a
spectrophotometer at wavelength 540mm or in a colorimeter using
a yellow-green filter. The absorbance obtained is compared with
that of a reference HiCN standard solution.
TEST
PROCEDURES:
1.
Measure 5ml of Drabkins solution and dispense into a 7ml or 10ml
very clean glass test tube.
2.
Measure carefully by pipetting 20ul (0.02ml) of well mixed venous
whole blood and dispense into the Drabkins solution.
3.
Stopper the tube, mix and leave the diluted blood at room
temperature protected from sunlight for 5minutes.
Note: this time is adequate for conversion of hemoglobin to HiCN
when using a neutral PH (7.0 – 7.4) Drabkins reagents up to
20minutes is required when using an alkaline Drabkins reagent.
4.
Set the wavelength of the spectrophotometer at 540mm or place a
yellow-green filter in the colorimeter.
5.
Zero the spectrophotometer/colorimeter with Drabkins fluid and
read the absorbance of the patient’s sample.
6.
Using the table prepared from calibration graph read off the
patient’s hemoglobin value.
PeTR
GLOBAL
UNIQE
SPECIALIST
HOSPITAL,
DEPARTMENT
SERVICES/ANNUNCIATION
ENUGU
LABORATORY
TEST:HEMOGLOBIN Electrophoresis (Hb genotype) using
washed and lyzed Red cells
DATE
FOR
12/4/2014
REVIEW: DATE OF
12/4/2013
SOP
ISSUE:
AUTHORISEDBY: REV SR AUTHOR(S):
REV
SR
CHUKWU C.C BENEDICTA,
205
/$%25$725<0$18$/
CHUKWU C.C
CHIDI, REV SR CATE.
STATUS:CONTROLLED
DOCUMENT
OPERATORS:
MLT,MLA
LOCATION:
HAEMATOLOGY
BMLS, NUMBER OF PAGES: 2
PRINCIPLE OF THE TECHNIQUE:
The most important primary screening method for the presence of clinically
significant hemoglobin variants is cellulose acetate electrophoresis at PH 8.5 –
9.0. Hemoglobin electrophoresis exploits the observation that due to differences
in the amino acid composition of their Globin chains, hemoglobin variants
differ in their rate of travel across a cellulose acetate support when an electric
current is applied.
Hemoglobin electrophoresis does not provide unequivocal identification of
hemoglobin variants, it merely indicates their presence.
The position of hemoglobin variant band relative to HbA when compared
provides sufficient evidence for a likely diagnosis.
TEST PROCEDURE:
1. Add equal volumes about 100ml of TEB (Tris-EDTA-borate) buffer to
the anode and cathode compartments of an electrophoresis tank. Set the
bridge gap to about 7cm and place a thoroughly wetted filter paper wick
so that it rests on each support, but still is dripping into the buffer.
2. Place the cellulose acetate strip on the surface of the buffer and leave to
soak for several minutes.
Blot to remove excess buffer and set in place between the two supports
and resting on the wicks.
Ensure that the strip is taut.
3. Apply 2ul of the test and control haemolysates to the origin (about 2cm
from the cathode end of the cellulose acetate strip). This is best achieved
using an applicator designed for this purpose.
The control haemolysate(s) should include HbA, HbS, Cover the lid
firmly.
4. Electrophoresis at approximately 350V for 30 minutes. The strips should
be monitored during this period and the time altered to maximum
separation.
206
/$%25$725<0$18$/
5. Note the presence, location of the abnormal bands his may provide
sufficient information for a presumptive diagnosis, but confirmatory tests
are usually required.
Preparation of haemolysate from EDTA (Anticoagulated blood)
When testing a haemolysate within 1-2days
1. Lyse 1 volume of saline washed packed red cells in 4 volume of lysing
reagent (water).
Note: Lysing reagent
Dissolve 3.8g EDTA (ethylenediamine tetra acetic acid) and 0.7g
potassium cyanide in 1 Liter of distilled water.
For long term storage of haemolysate:
1. Centrifuge sample, remove the plasma and wash the red cells three times
in physiological saline.
After each wash, centrifuge the red cells at about 1000g for 5 minutes.
Remove the saline.
2. Lyze the red cells with 1.5 volume distilled water and 1 volume of
toluene.
Shake well for several minutes in a stopper tube or preferably vortex at
high speed for 1 minute. Centrifuge at about 1000g for 20minutes.
3. Transfer the clear supernatant haemolysate into a tube. Adjust the
haemoglobin content to about 100g/L (10g/dl) by adding distilled water.
Label clearly.
Note: HAEMOLYSATE WILL BE STABLE FOR SEVERAL WEEKS
AT 4-80C AND FOR UP TO 3 MONTHS WHEN STORED FROZEN.
207
/$%25$725<0$18$/
BLOOD COLLECTION TEAM
CHIDI IHESIABA,
BENEDICTA OZONWEKE,
FRANCES ODUENYI
NNAMDI MABIA STELLA
MADUBA ANASTESIA
UGWU AUGUSTINA
UGWUANYI PATRICIA
OKEKE
Was this manual useful for you? yes no
Thank you for your participation!

* Your assessment is very important for improving the work of artificial intelligence, which forms the content of this project

Download PDF

advertisement