MEDICAL STATISTICS:
A MICROSCOPE FOR
HEAL TH AND DISEASE
An Inaugural Lecture delivered
at the University of Ibadan
on Thursday, 7th December, 2006
by
.
ELIJAH AFOLABI BAMGBOYE
Professor of Medical Statistics,
Faculty of Public Health,
College of Medicine,
University of Ibadan,
Ibadan, Nigeria
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Ibadan University Press
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University of Ibadan
Ibadan, Nigeria
© University of Ibadan 2006
Ibadan, Nigeria
First Published 2006
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ISBN: 978 -121- 418 - X
978 - 978 - 121 - 418 - 9
Printed by: Ibadan University Printery
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The Vice-Chancellor, Deputy Vice-Chancellors (Administration
and Academic), The Registrar, The Librarian, Provost, College
of Medicine, Dean of the Faculty of Public Health, Dean of the
Postgraduate School, Deans of other Faculties and of Students,
Distinguished Guests, Ladies and Gentlemen.
I am grateful to God Almighty for the honour and privilege to be
selected to deliver the 2005/2006 inaugural lecture on behalf of
the Faculty of Public Health. The feeling of honour and
privilege stems from the fact that if the Faculty of Public Health
had not been created in 2002, I may never have had the
opportunity of giving an inaugural lecture before retirement
despite attaining the position of Professor 14 years ago.
This inaugural lecture is the fourth from the Faculty of Pubic
Health and the second from the Department of Epidemiology,
Medical Statistics and Environmental Health (EMSEH). The
first lecture was by Professor J. D. Adeniyi from the Department
of Health Promotion and Education, the second was from
Department of EMSEH by Professor M.C.K Shridhar, a
Professor of Environmental Health and the third was by
Professor O. O. Keshinro of the Department of Human Nutrition
while this fourth one is also from the Department of EMSEH by
a Professor of Medical Statistics. I can therefore predict with
95% confidence that the next inaugural lecturer from the
Department of EMSEH will be by a Professor of Epidemiology.
When I received the e-mail from the Dean of the Faculty of
Public Health, Prof. Olaolu Akinyele that I had been nominated
to give the 2005/2006 inaugural lecture on behalf of the faculty I
readily accepted. I was then at the John Hopkins University
School of Public Health as a visiting scholar. Since I was to send
a topic immediately, I started to ponder on the topic and that
night I had a dream in which I received the title of today's
inaugural lecture which is "Medical Statistics a Microscope for
Health and Disease".
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What really is Medical Statistics, one may ask?
Mr. Vice Chancellor sir, as I pondered on this title many days
later, I realized that Medical Statistics as the Science of counting
health and disease, making sense out of those counts and
foretelling what lies ahead is actually a microscope into health
and disease. Previously, Medical Statistics was only concerned
with enumerating those dying in relation to those living, but
there has been a paradigm shift as facts and impressions in
Medicine are now expressed in numerical forms. This includes
laboratory investigations, radiological investigations and clinical
observations. In short, the methods by which these numerical
facts on health and disease are collected, manipulated, sieved,
summarized and interpreted, making use of the whole
armamentarium of statistical theories is the subject known as
Medical Statistics (Chiang, 1985, Zellen, 1983).
The World Health Organization defined health "as a state of
complete physical, mental, spiritual and social well-being and
not only or merely the absence of disease". Therefore, the
question that comes to mind is: How does one know who
satisfies this definition of health? In other words, who is
healthy? Or can we assume that anyone who has not sought help
from any health care service is healthy? The answer is NO. Or
else how do you explain the case of a man who had never
complained of any sickness in the last 5 years or so, but
suddenly dropped dead after seeing off a visitor. We all know
that many people suffer from one kind of ailment or the other in
silence partly because they do not know that they are sick. The
truth of the matter is, there is a subtle difference between health
and ill-health that cannot be seen with the naked eye and this
suggests that we need a microscope to identify the ailment.
Medical Statistics utilizes relevant, reliable and valid
information to identify the significance of any difference at a
known probability and has been the most useful microscope in
this respect. Thus, the demographic information, medical
history, clinical signs and symptoms collected to aid the
diagnosis of any disease is germane to sound statistical
manipulation. Population Medicine informs that diseases or
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deaths do not occur at random. They are caused, though not by
witchcraft nor the 'worst' of the 'wicked'.
Mr. Vice-Chancellor sir, this inaugural lecture has been
carefully designed to focus not only on how best medical
statistics has acted as a microscope to detect health and disease
of people in the community but on the factors causing the
disease. Perhaps some of us who are familiar with Epidemiology
as the study of the frequency, distribution, determinants and
deterrents of diseases in human populations would wonder if
Medical Statistics is not taking up that definition. Suffice to say
that this microscope (medical statistics) is used for both the
community diagnosis of ill-health and the diagnosis of disease
of an individual. Both public health and clinical medicine need
accurate information to diagnose health and disease and of
course information is knowledge and knowledge is power
Medical Statistics and Epidemiology
Medical Statistics as a discipline in Public Health and Medicine
represents one of the major intellectual advances of the
twentieth-century. It has developed to initiate and strengthen the
collaboration of statisticians and health professionals
(particularly physicians) in any medical or health research.
Suffice to say that a medical statistician is at first a
mathematician who adapts his knowledge to the study of
disease. Although the study of disease could be said to be
mainly in the allied discipline of Epidemiology, the
epidemiologist and the statistician work together to the extent
that it is permissible to use the words "Statistical" and
"Epidemiological" interchangeably.
The epidemiologist is first of all (in most cases) skilled in
medicine, but adopts a mathematical approach to the study of
disease in the population. The working relationship of medical
statisticians and epidemiologists has resulted in the statistician
becoming a better epidemiologist and the epidemiologist a better
statistician both using numbers and their logic to unravel the
mystery behind diseases. According to Professor Healy of the
London School of Hygiene and Tropical Medicine, "the
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difference between epidemiologists and statisticians is a subtle
one ..... as it is one of emphasis" (Healy, 1977; Zeger, 1991).
While the epidemiologist is mainly interested in the results of
investigations, irrespective of the methods by which these
results were obtained, medical statisticians are also interested in
results but equally in the methodology of obtaining them. The
medical statistician, because of his mathematical background
often develops new and modified techniques for handling
specific medical data or results in a novel application of
methods developed in another field.
The University of Ibadan, since 1968, has employed a
medical statistician with background in mathematical statistics
in its medical school and this has improved tremendously, the
quality of medical research as collaboration between the medical
statistician and medical doctors become a routine affair. The
development and relevance of the discipline of medical statistics
as a component course in medicine is such that there is a full
department with its complement of medical statisticians in
Ibadan. It is not only that medical statistics is part of the
curriculum in both undergraduate and postgraduate medical
education, but people now acquire postgraduate degrees in
medical statistics and statistical epidemiology from the
University.
Medical Statistics and Community Diagnosis of Health
Public Health is concerned with the health of the entire
population as a whole, but the clinician is interested only in the
treatment of that individual who has approached him because of
ill-health. Public Health strategies are largely designed to
prevent ill-health, identify and treat promptly those with ill-
health, thus avoiding any serious consequences. As an
illustration of the main focus of public health and also of clinical
medicine, public health tends to find out why many sick people
from, say Oja-Oba in Ibadan come to the health centre with
diarrhea diseases and a very negligible number come from, say
Bodija with this condition. In this scenario, the clinician's
primary duty is to treat cases of diarrhea 'that come to his clinic
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on a 1-1 basis, but the public health person traces the people to
their community to find out possible risk factors present in the
areas they have come from. If he later discovers that people
from Oja-oba take their drinking water from a source polluted
by Ogunpa river and those from Bodija from well-treated pipe-
borne water, he can associate the higher prevalence of diarrhea
with the source of drinking water, more so if the difference in
the proportion with diarrhea between the two groups is
statistically significant. In fact, this is how John Snow linked
cholera to contaminated water and thousands of people are being
prevented from this deadly disease by providing them with good
portable water. One clear difference between the impact of the
strategies of clinical medicine and preventive medicine is the
number of people affected at a time. While the clinicians may
see an average of 10 patients a day in a medical out-patient
clinic, a preventive action may affect and safe the lives of
several millions of people.
Medical Statistics also develops mechanisms to find the
causes of diseases or at least locate modifiable and non-
modifiable risk factors, whether environmental, behavioral,
occupational hazards and other factors that could pre-dispose to
the occurrence of diseases. Imagine seeking for risk factors of
diseases in a population as large as Nigeria with over 130
million people. This is' like fishing in the dark and Medical
Statistics has provided the microscope for making correct
community diagnosis of ill-health and examining if those who
are apparently healthy may probably be so because they have
not shown any signs or symptoms of any disease or that they are
truly healthy. If they are healthy, the microscope examines
measurements of such factors that make them healthy. The
diseases are classified into communicable and non-
communicable diseases for ease of understanding and
presentation. This is further classified into seventeen categories
ranging from infectious and parasitic diseases to accidents and
ill-defined conditions.
The development of statistical indices of health such as
rates, with the four components - numerator (no of events of
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.nterest), denominator (population at risk of the event), time-
frame (the period the event occurs) and the standard form in
which it is expressed has found immense use in determining
health and disease status. The size or extent or magnitude of a
disease or any health problem in the community can be
measured by the prevalence rate. But the rapidity at which
. diseases occur in the population on the other hand. is measured
by the incidence rate. The census, a purely statistical exercise
. that is routinely conducted every ten years in any developed
nation provides sources of the denominator for most of our rates.
Tbe collection and analysis of records of vital events such as
births, marriages and deaths have been used to assess fertility,
nuptiality, mortality and growth of human population. Thus the
ability to measure is paramount (sine qua non) to understanding
health and disease and this has been facilitated by the science of
medical statistics. In fact as far back as 1889, Lord Kelvin had
written that "when you can measure what you are speaking
about, and express them in numbers, you know something about
it; but when you cannot measure it, when you cannot express
them in numbers, your knowledge is of a meager and
unsatisfactory kind" (Oldham, 1968).
Medical Statistics as a Microscope for Individual Diagnosis
Medical Statistics as a microscope for individual diagnosis of
disease, its prognostic factors and best treatment options was
resisted at its earlier debut in clinical· medicine ..The notion of
clinical doctors is that "patients are different and therefore
cannot be subjected to statistics." A clinician even said that if he
has done a study and requires statistics, then he knows he has
done a bad study. But can anyone in this audience tell if the
person sitting next to him or her is healthy? Do you know if a
healthy looking man has AIDS? Or can you say if that well-built
man next to you can be hypertensive? Is the woman on your left
side suffering from diabetes? The truth is that there is no
window to look into the system or heart of man to identify his
.health or disease status. This suggests that to identify a healthy
'man, or to know if a drug will cure a disease, or know the cause
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of a disease, or know who will die in the next minute demand
more than can be seen with the naked eye. The naked eye of the
doctor cannot tell if the social habit of a patient is responsible
for that damage in the liver. And neither can the naked eye of
the doctor nor nurse tell if the patient admitted for diabetic care
will survive the next 3 days. Neither could the naked eye see the
exact diagnosis of the illness of a peasant farmer from a village
in Ekiti State who suddenly jumped on the road, claiming
himself as the president of the USA and asking people and
relatives around him to take commands from him.
Mr. Vice-Chancellor sir, God created man to be different in
many respects from each other and one clear evidence is that no
two fingerprints of the over 6.5 billion people in the world are
the same. These inherent biological variations in man and the
differences in characteristics of individuals would have made it
more difficult to find the truth of the actual factors causing or
affecting ill-health and diseases' worst outcome-death. But
God so loved the world that He created the science of medical
statistics and medical statisticians to sort out the variations in
man and disease and thus able 'io identify the true causes or risk
factors of ill-health and death to specified degrees of confidence.
But it was initially difficult for clinicians to imbibe medical
statistics as a reliable and valid microscope to diagnose diseases.
However, by and large, the concept of medical statistics
realized ironically as far back as the 16th century by some people
has now become the norm rather than the exception in medical
practice. Leonards Da Vinci who lived in the 16th century (1452-
1519) said "No human investigation can be called true science
without passing through statistical test". Medicine has become
real science. The clinical issues of patient diagnosis, prognosis
of disease and treatment have benefited from medical statistics.
Diagnosis and assessment of prognostic factors depend largely
on patients' data on physical characteristics, laboratory
parameters, radiological information, clinical and personal
characteristics. The 3-stage process of science, observations,
building up a model to describe or explain the model and using
the model to predict future observations or events have found a
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strong place in medicine particularly in communicable diseases
where epidemics are dealt with. The use of models in describing
any epidemic and forecasting the spread in time if nothing is
done, 'is the telescopic use of Medical Statistics.
Normal Range of Values
The commonly used concept of normal range of values for
separating healthy people from those who are diseased has been
facilitated by the microscopic nature of medical statistics,
starting from its use of "mean plus or minus two standard
deviations" based on the assumption of a Gaussian distribution
for continuous variables. The diagnosis of most medical
ailments such as diabetes, hypertension, anemia and so on
depend much on the normal range of values of biochemical
parameters, blood pressure readings and hematological indices
obtained from the patients. Thus the doctor can classify as
hypertensive with a high degree of confidence, a 50-year old
man with 3 consecutive blood pressure readings of 180/100,
178/95, 181/100. Or as diabetic, a middle-aged woman with
fasting blood sugar of 180mg/dl and random blood sugar of
200mg/dl and a young man with CD4 count of 150 as suffering
from AIDS. Also the doctor can say that a woman with a white
blood cell count of 320,000 per ml may be suggestive of
myeloid leukaemia or a child with a temperature of 39.3 degrees
as .having a fever. The doctor can also diagnose a 20-year old
girl with a PCV of 10% as severely anemic.
But the so-called concept of normal range of values often
used, is developed on the normal distribution theory, an
important aspect of medical statistics that has been very useful
as a microscope to sort out patients into normal and abnormal
groups or healthy and disease group. This normal distribution
theory of continuous variables was described with a simple
mathematical model represented by an equation:
. 1 l.fx-I' \1
y= e-2\,,}
.J21!a2
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Using the properties of the model, the parameters were
calculated from observed values in an apparently healthy
population. Subsequently, confidence intervals for which
admissible values with 95% confidence are allowed are obtained
and consequently the construction of the normal range of values.
It suffices to say that this simple mathematical model is the
bedrock of parametric tests which have found immense. use
today in the testing of hypotheses. Clinicians have drunk so deep
of the statistical concept of hypothesis testing to have developed
a p-value syndrome to an extent that they have felt that any
research in Medicine cannot be published without an
accompanying p-value. This may not necessarily be so as some
studies are purely descriptive and do not test any hypothesis.
Evaluation of Treatments
Also, apart from identifying health and disease, Medical
Statistics or the Medical Statistician has always acted as a
policeman in medical practice. We are in a world of great
advancement in computer technology and the practice of
medicine- has become evidence based. The patients in the
hospital want know the treatment plan for them, at least to have
psychological satisfaction. Astute observations of regularities of
events often call for clinical or epidemiological studies. Mr. A
had this problem, received drug A and was relieved. But Mr. B
had the same problem, was given drug A but did not improve.
Medical statistics provides the path of explanation; first, it asks
if the disease condition is similar in both groups in terms of
onset before seeking treatment, and them finds out if the drug
works in the acute or chronic phase, or whether confounders in
terms of the persons of Mr. A and B have been removed. Thus,
clinicians are reminded that the measurements collected are
subject to variations and interpretations and can be marred by
confounding factors if these are not properly controlled for.
Factors masking the true diagnosis or the true efficacy of any
therapy are sorted out and removed through the use of Medical
Statistics, the powerful microscope for health and disease.
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This miscroscope is not only towards health and disease but
also to allied areas where the truth is needed. Such is the.
performance of students in the universities and their admission
criteria. My work in this area has been in examining the
University of Ibadan as a case study. This effort resulted in the
present admission guidelines for Post-UME screening referred
to as the Ibadan Model. (Bamgboye 1981; Bamgboye et aI.,
2001; Kale and Bamgboye, 1984; Ibadan Screening Committee,
2005).
Medical Statistics as a Microscope for the Truth
I was privileged to attend the 2002/2003 university lecture
delivered by Professor Oladele Kale, an icon in Public Health
and in particular filariasis, the foundation Dean of the Faculty of
Public Health who was my Head of Department (HOD) at
several points in the life of the Department of Preventive and
Social Medicine, including the period of 'distress'.. He
emphasized the need to seek the truth always in that lecture
titled "Nigeria in Distress! A Trilogy of the Nation's Health
Status". The apostle John said in 1 JohnLV;"Dear friends, do
not believe every spirit, but test the spirits to see whether they
are from God, because many false prophets have gone out into
the world". Indeed, in a similar· fashion, many false
(unscientific) researchers have flooded the health field and have
always capitalized on the psychology of the people to inflict
untold misery on them. I have watched several times on my
television, an advertisement of a magic drug (panacea) that can
treat typhoid, hypertension, appendicitis and any other disease
Gust name it) with a single dose!
Professor Kale used the Abalaka claim of a prophylactic and
therapeutic cure for HIV1AIDS as a case study. This is a well
known case circulated on the pages of newspapers a few years
ago. Because of the deadly nature of AIDS and the fact that no
cure is known, it is normal to draw attention to anyone who
announces he has found a cure. No doubt, a microscope is
needed to ascertain the minute details of the truth of any claim
to a cure of AIDS. And indeed, if you ask me the sample size
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required to assess the efficacy of a drug that could cure AIDS, I
would say one person. But then the one person must indeed be
diagnosed to truly have AIDS and all the facts must be
available.
As usual, the Abalaka drug issue was reviewed by Professor
Kale, and many people including myself ended up disappointed
at the methods of investigation by all the parties concerned. But
the Abalaka issue is a tip of the iceberg in the multitude of
malpractices involving the inappropriate use of Medical
Statistics that pervades our health service system. This is often
attributed to inadequate knowledge of the real health problem,
the root cause of which is the poor data gathering system,
method -of data analysis, and poor interpretation of findings.
This is the situation in which any nation will find itself when
there is a lack of reliable empirical evidence to aid decision
making and those trained to provide the mechanism to generate
this reliable data are either not available or are very few. It is not
surprising however, for one to grope in the dark when that
instrument to provide light and see minutest issues as a
microscope is missing. Our Lord Jesus Christ saw the crowd
following Him at one stage and had pity on them and declared in
Mathew 937; "The Harvest is plentiful but the workers are few".
For the multitude of health problems that need research all over
the world and in particular in Nigeria, there are very few
medical statisticians.
The advancement of computer technology and the
availability of statistical packages in the open market, with
piracy going on unchecked, have given birth to a number of do-
it-yourself statisticians. These people -who often 'hit their
thumbs with hammer' in their practice do more damage than I
will cause if I attempt a brain surgery. There is no amount of
formal education a health policy maker can acquire that he will
be able to draw up meaningful policies based on wrong data or
subjective reasoning. We, all know that the bane of our health
problems 'in Nigeria today is the lack of reliable health data .and
lack of professional medical statisticians in the health system
team. If this was not so, the Nigeria Institute of Pharmaceutical
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Research and Development( NIPRD) would have had at least
one medical statistician on their team, who would have advised
the director investigating the Abalaka claim based on two
patients, that they needed to include a control patient probably
on a placebo and see the natural course of the disease.
In clinical trials, a great deal of attention is directed at the
patient and they are much aware of this and subjects' condition
can change because of this and not necessarily because of any
treatment. This situation, known as the Hawthorne effect cannot
be separated from the treatment effect in uncontrolled trials as
carried out in NIPRD. God is wonderful; there is the natural
course of things and medical statisticians have studied this
situation to conclude obedience to the "Law of regression to the
mean". This explains why clinicians require a repeat of a
laboratory test of .an unexpectedly abnormally high value and
usually, the second test result is closer to normal values.
Anyway, a cure for a disease as deadly as AIDS may not attract
any large sample size as I said before, a sample size of one is
enough if people can truly attribute the cure of AIDS disease to
the 'curative agent' alone. The statistical methods for the
evaluation of treatments of diseases date back to the early life of
man. In the Holy Bible (Judges 636-40), Gideon wanted to know
if God would indeed support him in the task He put before him.
Then he carried out a trial by putting a fleece of wool on the
floor and asking God to make the fleece only wet and the earth
around it dry. It happened, but he reversed his allocation of
subject units and asked God to make the fleece of wool dry and
make the surrounding earth wet. This happened and he was
convinced beyond any reasonable doubt that God would support
him. This design can be taken as the beginning of the cross-over
design often used in clinical trials today.
Let me tell the story of the blind man and the dumb man
brought to Jesus. The dumb-man was demon- possessed and
could not talk and everyone in the crowd knew this and so also
the blind man. They deliberately brought them to Jesus,
probably to test-His power. The blind man regained his sight and
Jesus drove the demon out and the dumb man also regained his
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speech. According to Mathew 933, " •••.•••.• the crowd was
amazed and said nothing like this has ever been seen in Israel".
In spite of the several miracles using the same therapy, many
people were still skeptical about Jesus and His therapy. The
medical statistician is always a skeptical scientist.
Now, about Abalaka's drug trial, I reproduce in table 1 the
NIPRD result with permission from my former HOD. The
changes may simply be the whole concept of regression to the
mean.
Table 1: NIPRD Result on Abalaka's Drug Trial
Viral load (copies/ml) After two weeks of
immunotherapy
NIPRDIHIV/JAV/001 8.2 x 105 (12/1/2000) 2.4 x 103 (25/112000)
NIPRDIHIV/JAV/002 1.6 x 105 (12/1/2000) 1.6 x 103 (25/112000)
The medical statistician would have suggested the need for a
control group and asked many other questions if he were on the
research team. What is the viral load of the AIDS patient who
never took Abalaka's drugs? Are the patients truly comparable
or do they satisfy the same criteria for inclusion? Any ambiguity
in the definition of AIDS? Have they used the same selection
criteria or mechanism for counting the viral load? Are there
copying errors, transcription errors, measurement errors? and so
on. Apostle Paul said in John 8, verse 32; "if we know the truth
the truth shall set us free". Since the naked eye cannot see the
truth in health and disease and we must know the TRUTH, we
give Glory to God for the birth of the discipline of MEDICAL
STATISTICS to serve as a MICROSCOPE to tell the truth
about health and disease.
Let me at this point appreciate Professor Bamiduro who
defined Statistics in his inaugural lecture of 7th July 2005 "as the
science to detect the TRUTH". Several strategies have been put
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in place by man (preventive, curative) to ensure that everyone is
healthy. But the organization of these strategies has benefited
immensely from the use of the science of Medical Statistics.
That the psychiatrist is able to define variables associated with
manic depression, and the surgeon able to measure the degree of
burns or the probability of non-spread of bone cancer if the
affected part is amputated, is due to the use of medical statistics
as a microscope which has always been used on observed data to
separate the chaff from the wheat and indeed the diseased from
the healthy. Not that alone, it has been used to identify the risk
factors of diseases. Medical Statistics has made it possible to
associate with heart attack, the case of a 55 year old prospemus-
looking man who alighted from his new Mercedes Benz Jeep
which he drove by himself from his station of about 200 km
away, entered his father's compound safely and suddenly
slumped in the process of prostrating before his father and was
declared dead a few minutes later! Or else the witches in the
family could have been held responsible. The amount of
statistical jargon found in any medical journal today is an
eloquent testimony to the use of this science to understand
health and diseases.
Some Other Specific Applications of Statistical Concepts to
Medicine
Control of Communicable Diseases
Several hypotheses based on quantitative data have been
evaluated through the application of mathematical models. The
earlier area of mathematical application to the development of
medicine was in the area of communicable diseases. It will only
be important to mention a few in this lecture. Following the
successful fitting of the normal curve by William FaITin 1840 to
quarterly data on deaths from smallpox, further application was
for the description of epidemics. Notable is the work of Ronald
Ross on the transmission of malaria by female anopheles
mosquitoes. Simple mathematical assumptions already
postulated by Hammer in 1906 that the net rate of spread of
infection is proportional to the product of susceptibility and the
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density of infections of individuals, and that they are expressed
in a discrete time was all he needed to establish the popular
threshold theory for malaria, but after the modification of the
model to a continuous time frame (Bailey 1957, 1975). The only
snag in the application of mathematical models to disease and
health is the lack of empirical data and this has sometimes
defeated the whole exercise. .
In fact, a look at literature reveals that less than 10% of
published mathematical models in medicine have practical
applications due to lack of empirical observations. But more
data-oriented studies of diseases using mathematical theories are
coming up. For example the current public health policy on
diseases such as onchocerciasis and malaria has benefited from
the mathematical theories developed that were necessary and
sufficient to recommend effective methods of controlling the
sources of infection. In the earlier stage of my career, I was
introduced to the control of onchocerciasis (river blindness) and
my humble contribution was in the statistical analysis of the
drug trial. The analysis examined the relative efficacy of
Banocide and Suramin Injections on the disease (Bamgboye
1977). Studies later revealed that mathematical models can be
applied to determine the point of intervention for effective
control and I was invited to Ougadougou by WHO to participate
but the load of work in Ibadan prevented me from continuing
with them. However, today, the model developed by other
medical statisticians who finally worked on the research has led
to the effective control of this disease.
Decision making in medicine has benefited from
mathematical statistical theories appropriately facilitated by
Baye 's Theorem. It has been discovered that, no investigation
can be called true science without passing through mathematical
tests. Thus the reliability and validity of most diagnostic tests
commonly used in medicine today have been developed through
mathematical concepts of statistics. For example, the probability
that a patient has a particular disease if the diagnostic test is
positive given the prevalence of the disease in the population
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and the false positive rate, can only be calculated by statistical
methods.
Designs of various studies in medicine have benefited
through mathematical knowledge. Initially, Mathematicians or
Statisticians were used for technical service in the analysis of
data but in recent times, the notion has changed and the
collaborative role of statisticians in the development of
treatment strategies in medicine is now well recognized.
Observational studies are more common in medicine than real
experiments. But the medical domain is beginning to realize
that the only way to find out what will happen to a complex
system as in medicine is to disturb the system. Several
statistical methodologies have been developed to bring out the
scientific value of the popular observational studies, particularly
in identifying. risk factors of diseases or in studies of disease
etiology.
The present approach to the control of communicable
disease has emerged through the applications of mathematical
and statistical theories to the description of the process of
acquiring the disease. This has led to the suggestion that,
immunization, control of unanimated vehicles of infection,
control of insects and other living vectors and appropriate
therapy could be basic procedures that could subjugate
communicable diseases.
A lack of proper understanding of the host- parasite
relationship which expresses the genetic make-up of the system
has slowed down the control of many infectious diseases.
However, a model has been developed that is. essential to
describe, predict, and explain our health situations. That this is
possible has been through mathematical reasoning and logic. A
clear understanding of the transmission process of epidemics has
thus benefited from mathematical methods. Another basic
reasoning is the phenomenon developed by Reed Frost in 1928
and further explained by Greenwood in 1931. They both
stipulate that the probability of a given epidemic chain is the
product of probability terms from different binomial
distributions. This is the population chain binomial model which'
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has found immense use in the description and prediction of the
rates of infections and has led to the telescopic value of medical
statistics for predicting future occurrences of epidemics based
on observed facts now, if nothing is done.
A major contribution was the work of the first Ph.D
candidate produced in Medical Statistics in this University, Dr.
Bidemi Oyindamola Yusuf, who under my supervision applied
mathematical models to unravel the problem of anti-malarial
drug resistance which permeates the population (Yusuf, 2005).
The thesis developed a mathematical framework to explain and
describe the population dynamics of. drug resistance, using
stability analysis and simulations. It revealed that it was more
beneficial to prevent drug resistance than to cure it.
My Contributions
Mr. Vice-Chancellor sir, Let me at this point talk briefly about
the role of the medical statistician and my contributions to my
profession. It is a common mistake to assume that medical
statisticians need only be concerned with the analysis of already
collected medical data. This is of course the notion of many
other workers about medical statisticians working in a medical
milieu as in the College of Medicine. It is no doubt that the
medical statistician plays a major role as a data analyst but
he/she does equally well in study design and conduct. One of the
duties of a medical statistician is collaboration and his/her role
in such a situation is to ensure that both protocol design and
interpretation of study and trial findings conform to sound
principles of scientific investigation that will remind us that the
cause of humans' health and disease is such that cannot be easily
seen with the naked eye.
Apart from collaborative research, a good medical
statistician, as a scientist especially one who works in the
academia has his own special area where he should make novel
contributions. I will now describe where I have made novel
contributions as an individual or in collaboration with others.
This will also include my role in the development of medical
statistics education in the University of Ibadan.
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My Contribution as a Collaborative Scientist
Ever since I joined Professor Ayeni at the University of Ibadan
in 1975, I have used medical statistics as the instrument to
search for the truth of health and disease, a task tantamount to a
blind man looking for a black cat in a dark room. The first
aspect of my contribution was through collaborative research
and to date, I have collaborated with 177 medical persons or
researchers to solve or throw light on a number of medical
problems or issues both in Nigeria and Saudi Arabia. It is
interesting that I have only 8 non-medical people as
collaborators. I have also been involved in 27 national health
studies both in Nigeria and Saudi Arabia and over 5,000 on-the-
spot statistical consultations averaging one per day.
This aspect of my work brought some confusion to some
naive scientists saddled with the task of reviewing my
publications for professorship as to whether they should
recommend me for Professor of 'Obstetrics and Gynecology?,
Pediatrics? Medicine? Opthalmology? Psychiatry? Demo-
graphy? Medical Education? or Pathology?' (Name any area of
Medicine except Surgery which has just begun to have its doses
of the use of medical statistics). And this is simply because of
my numerous scientific publications with collaborators in these
specialties. But most importantly, what is medical about the
professional medical statistician that I am? This is that the
medical statistician has a fair amount of medical knowledge,
Medicine being the subject matter of his field. But the medical
statistician is no more a doctor manque than he is a
mathematician manquee, Since he is involved in collaborative
work, his collaboration shall not be wasted if the medical
member of the research team takes time to explain things taught
to medical students in their first pre-clinical years to him. The
new professional medical statistician will like to learn among
other things, in an apprentice fashion on the job, some of the
medical knowledge. In the code of conduct of the medical
statistician, no one is allowed to advice on a subject he does not
understand. This implies that the medical statistician obtains
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enough materials on any medical topic brought to him for
statistical advice and he is expected to have a fair knowledge of
this before offering any advice.
My collaborative role in the appfication of statistical
methodology to the design, analysis and interpretation of
medical studies underscores the good proportion of my
publications in various specialties of Medicine. As is well
known, my collaborators are medical people and I am happy to
say that my collaborative research work is not limited to the
shores of Nigeria but to far away Saudi Arabia where, during
my initial short stay of about 3 years at their first College of
Medicine, King Saud University, Riyadh (although I had an
aggregate romance close to 12 years), I was able to produce 30
publications. At this point Mr. Vice-Chancellor, I like to say that
the credit of authorship, according to the International
Committee of Medical Journals, should be based and it is based
on:
(1) Substantial contributions to conception and design of a
study, or acquisition of data, or analysis and
interpretation of data;
(2) Drafting the article or revising it critically for important
intellectual content; and
(3) Final approval of the version to be published.
Authors should meet conditions 1, 2, and 3. I recommend
considering these criteria of assessing contributions in multiple
author publications, in the University of Ibadan, new guidelines
for the promotion of academic staff.
I am bold to say that in all my collaborative work, regardless
of my position in the authorship list, I met all 3 criteria. In
Pediatrics, working in collaboration with others in Saudi Arabia,
a standard growth chart for monitoring the growth of children
was developed based on a national cross-sectional study to
replace the American Reference Standard which was found not
suitable for Saudi Arabian children (al-Frayh and Bamgboye
1992, 1995; al-Nuaim and Bamgboye, 1995, 1996; al-Sekait et
al., 1992). The curves were drawn using the Spline Polynomial
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Regression Method and it is used in all clinics in Saudi Arabia
to monitor the growth of children. Another contribution in
Peadiatrics was the identification of factors influencing linear
growth in children (al- Fawaz and Bamgboye 1994), the results
of which have helped in health promotion programmes. So also
was the study on the determinants of faltering growth in Saudi
Children (Bamgboye and al-Nahedh, 2003). Other studies
included 'Bronchial Asthma in Saudi Arabia' and the
determination of the risk factors of Coronary Artery Disease in
Nigeria and Saudi Arabia (Taylor et a1.,1996; al-Nozha et a1.
1994). Another area was in the determination of visual loss in
Saudi Arabia (Badr and Bamgboye 1990, 1992). Studies on the
causes of adult morbidity also provided a good benchmark for
planning preventive actions (aI-Balla, et al., 1993; Bahakim et
aI., 1993).
In Nigeria, basic data on morbidity showing the type and
pattern of disease in our children received my attention
(Bamgboye and Familusi, 1990). So also, was the utilization of
health services in the hospital (Bamgboye and Jegede, 1987;
Jegede et al 1990, al-Shammari et al., 1994 (Bamgboye and
Shoge, 1987; Bamgboye, 1985). This concept has been of help
to policy makers examining theburden of disease. Also hospital
administrators benefited from studies on waiting time of patients
in the hospital before seeing a doctor (Bamgboye, et aI., 1992;
Bamgboye and Jarallah 1994). I have also collaborated with
colleagues in Psychiatry to study the health problems of the
elderly (Baiyewu et aI., 1997; al-Shammari et al., 1994).
Indicators of morbidity in workers, using sickness absence
records, has also been analysed to produce relevant morbidity
statistics both in Nigeria and Saudi Arabia (Erinosho and
Bamgboye, 1988; Bamgboye and Adeleye, 1992; Bamgboye et
al., 1994; al-Shammari et aI., 1994).
Another area of my contribution is in the development of
health service research in Nigeria. The availability of reliable
morbidity and mortality data serve as evidence of good database
for better planning of health services and effective health policy.
In this respect, I have been involved in the national health
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information system and the development of techniques for
estimating the burden of disease in Nigeria. (Taylor and
Bamgboye 1979; Taylor et aI., 1992). Part of my contribution
has been to a number of national studies carried out by the
Federal Ministry of Health with support from numerous foreign
donors. These include National Health Surveys for the
determination of levels of reproductive health including
HIVIAIDS (Federal Ministry of Health, 2005), the Evaluation of
Prevention of Mother to Child Transmission of HIV/AIDS in
Nigeria (FMOH, 2005) and Sentinel Survey for the Estimation
of the Prevalence of HIV in Nigeria (FMOH, 2006). The later
report has informed the present scaling up of the programme and
refinements in the logistics. A national behavioral surveillance
survey of high risk groups of HIV/AIDs in Nigeria has just been
concluded and the report is yet to be published. The information
from the various surveys benefiting from the science of Medical
Statistics has been useful to policy makers in determining the
current health and disease status of Nigerians for effective health
service planning and development of strategies to aid the
campaign against HIV/AIDS.
Let me also add that I have collaborated with colleagues in
the Department of Obstetrics and Gyneacology to contribute
intellectually to reproductive health research. The objectives of
our Lord as contained in Genesis 1 verse 28 which says: "Be
fruitful and multiply and replenish the earth ... " can be realized
with good healthy reproductive practices. Studies on the growth
patterns of the fetus at different gestational ages in a normal
obstetrics population have produced appropriate techniques for
measurements of fetal growth and standards for evaluation
(Osinusi and Bamgboye, 1987; Marinho and Bamgboye, 1987).
The studies on the evaluation of ante-natal services in Saudi
Arabia have helped to develop a sound policy on the number of
antenatal visits and the provision of maternity services in
general (aI-Nasser et aI., 1991, 1992 and. 1994). Other
contributions were in the area of the determinants of abortion
and reproductive potentials following abortions as well as
ectopic pregnancies. The information has been a useful guide for
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health education and obstetric practices (al-Nuaim et al., 1995;
Adelusi et al., 1998).
My Contributions to the Science of Medical Statistics
My Ph.D thesis on the Methodology of Indirect Techniques is
one of my major contributions to Medical Statistics. The
outcome of this Ph.D degree work is now a central item in the
United Nations Manual X for Indirect Demographic Methods
(U.N. Manual X, Chapter IV, 1983). The methodology
developed under the supervision of Professor Brass, the father of
Medical Demography is one of the great topics in courses on
Indirect Techniques today. It is known as the Brass-Bamgboye
technique for locating time points for adult mortality estimation
from retrospective survivorship data ( Brass and Bamgboye,
1981; Bamgboye 1983). It was a great delight when Professor
Ken Hill, the greatest living icon in Indirect Demographic
Techniques at the John Hopkins University in April this year
introduced the topic in a lecture on Indirect Methods and
declared it as one of the greatest contributions to indirect
methods for mortality estimation. He further challenged me to
have a closer look at the methodology for possible refinements
(if necessary) in the light of new available data. Fortunately, we
now have a programme for a Ph.D in Medical Demography in
my department and one of our promising, young and talented
lecturers in Medical Statistics; Odunayo Akinyemi, has turned
his microscope in this area to search for more truth in pursuit of
his Ph.D.
The Indirect Method of Estimating Mortality (Medical
Demography) .
For the benefit of the audience, let me talk briefly on Indirect
Demographic Techniques. The numerator for mortality indices
can be obtained directly from records of deaths collected
routinely through the vital registration system and its
denominator from census figures (Bamgboye, 1983). It suffices
to mention the lack of traditional demographic data in
developing nations where the organization of national census or
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the establishment of vital registration systems continues to be a
problem (Ayeni, 1971). The childhood survivorship data
obtained from simple questions for mothers on total children
ever born and numbers surviving are known to provide good
estimates of infant and childhood mortality (Brass and Hill
1973). So also, reports on orphanhood and the ever-widowed
have provided acceptable adult-mortality levels (Hill 1977).
These estimates are obtained from simple questions such as 'Is
your father alive?, Is your mother alive? Is your spouse alive?
and so on requiring a Yes or No answer and included in single
round demographic surveys. The underlying assumption of the
methodology has been that mortality changes in the past can be
ignored or that mortality remains constant. My novel
contribution to this issue is the examination of this assumption
and development of a mathematical model that locates the time
in the past to which the estimates of mortality levels from these
retrospective survivorship reports refer (Brass and Bamgboye
1981; Bamgboye 1983). My contention is that mortality in
developing countries cannot and is not constant but changes. In
the light of many economic development and social strategies it
should be declining. However, this decline is assumed to be on
the logit scale.
These methods have been developed using sound
mathematical theories such as the Taylor's series theory used to
link cohort life tables with period life tables. The development
of the model was based on several assumptions of fertility and
mortality regularities and population models utilizing theories of
integral calculus , power series, and the logit models. The
evaluation has resulted in the equation for the time location (T)
in the past given as:
T/ = Ix I a xWa (f((a+x)T)/t(a, T)CxLa-x t(a,T) dadx
I,I a xWa (f((a+x)T)It(a, T) -f((a + T), T» dadx
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where
xWa = proportion of the group in the age group (a, a + x)
Ix J a .Integral signs at which persons enter the system (a) and
appropriate lengths of exposure respectively (The system may
be marriage or orphanhood)
f«a+x), T) = Life table survivorship to a + x at time period T.
This model, developed for estimating time location of estimates
obtained from retrospective survivorship reports may look
complex. And this underscores researchers' view that while a
physician is said to make an analysis of a complex illness, a
statistician makes one ill with complex analysis and this may
explain why a physician is held in higher esteem than the
medical statistician. But the interest in the medical field is more
of the application and results rather than the complex
methodology. .
My interest in the development of mathematical models had
encouraged me to estimate indicators for health and diseases for
countries with poor and deficient data. The work has facilitated
my estimating fertility and infant mortality levels for Saudi
Arabia and South West Nigeria (Bamgboye 1989, 1990, 1993;
AI-Nasser and Bamgboye 1992).
A disease surveillance and notification system for
monitoring the expanded programme on immunization was also
developed in the 1980s while I was working as consultant to the
UNICEF office in Nigeria, through the establishment of sentinel
sites (Bamgboye, 1988) .
.Development of Medical Statistics Education
The science of Medical Statistics was at its infancy when I
joined the then Department of Preventive and Social Medicine
as there was only one person in the unit. This was the first
Professor of Medical Statistics in Africa and one of the 3
pioneers of the programme of Medical Statistics at the
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University of London, School of Hygiene and Tropical
Medicine-the renowned Professor Olusola Ayeni. A
statistically significant information is the fact that I was in the
7th set of students that drank from the fountain of Medical
Statistics at the London School of Hygiene and Tropical
Medicine. Suffice to say that the growth of Medical Statistics in
Ibadan today was master-minded by the doyen of Public Health
worldwide - our own Professor Adetokunbo Lucas whose
dynamism and brilliance has led to what we witness today. My
experience has shown that Medical Statistics is not an attractive
subject to the medical student. Perhaps they do not understand
the doctrine it is preaching at the time it is introduced to them.
Therefore, my knowledge of the psychology of students to
mathematics, and particularly of medical students and others in
the allied health professions who had thought the only
microscope they need is to read slides on patients from the
pathology and hematology laboratories diagnoses has led me to
find simple innovative ways to teach the Medical Statistics
course. A simple textbook was produced based on the earlier
approach by Professor Lucas (Bamgboye 2004). The approach
has popularized the Medical Statistics course and this has
increased the interest of students and staff in a subject hitherto
regarded as relatively difficult.
Design of Medical Experiments
Another area of my contribution is in the design and analysis of
various medical experiments. It is important to note that
properly designed and well analysed clinical trials have resulted
in bringing to light appropriate prophylactic and therapeutic
treatments of major diseases. Many treatments or procedures
today have emerged through experiments aptly designed using
the mathematical approach. To come to this stage has not been
a smooth journey as the statistician suggests elements of
randomization to avoid bias and at times recommends blindness
as a measure to avoid both subject and assessment bias. The
physician holds a contrary view that he has to know and be in.
control of the drugs or treatments given to his patients, and does
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not subscribe to chance in determining the dosages or
treatments.
The picture today is that no treatment or drug can be
introduced into the market without undergoing clinical trials
heavily policed by medical statisticians. In fact, for drugs
developed in other countries and which have undergone clinical
trials in those countries, the regulation body in Nigeria,
NAFDAC requires a repeat of such clinical trials using Nigerian
subjects. To this end, our drug companies are often testing new
drugs for the treatment of urological problems, chronic diseases
such as hypertension, and diabetes. My major contribution in
this regard has been either in the design or statistical analysis of
data collected during these drug trials. For example, one major
contribution was in the study design and statistical analysis of
the multi-centre drug trial of Niprisan, a drug for the control of
sickle-cell disease (SCD) in Nigeria. This drug was recently
launched in Abuja with the trade name Nacosan (Wambebe et
al., 2001; Bamgboye 2006).
Other clinical trials I have participated in include-just to
mention a few:
(1) Anastrazole trial in the treatment of Breast Cancer;
(Bamgboye, 2006).
(2) Open label, flexible dose escalation study to assess the
efficacy and safety of Doxazosin(Cardura) in patients
with benign prostatic hyperplasia; (Bamgboye, 1999).
(3) The effectiveness and safety of an individualized
Symbicort Turbuhaler maintenance dosing regimen
(Symbicort Asthma Control Plan) versus Symbicort
Turbuhaler given as standard regular twice daily
therapy-The Symbicort Adjustable Maintenance
Study (SAM), (Bamgboye, 2001).
(4) A multi-center open label assessment of the efficacy
and safety of Atorvastatin(Lipitor) in the treatment of
Types IIA & lIB Hyperlipoproteinemia (Bamgboye,
2003); and
(5) Viagra for erectile dysfunction.
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This microscope is not only towards health and disease but
also to allied areas where the truth is needed. Such is the
performance of students in the universities and their admission
criteria. My work in this area has been in examining the
University of Ibadan as a case study. This effort resulted in the
present admission guideline for Post-UME screening referred to
as the Ibadan Model. (Bamgboye, 1981; Bamgboye et al., 2001;
Kale and Barngboye, 1984; and Ibadan Post-UME Screening
Committee. 2(05).
The Growth of Medical Statistics in the College of Medicine
Mr. Vice-chanceHor sir. this inaugural lecture would not be
complete if I fail to speak on the growth of Medical Statistics in
the College of Medicine. The story would have been "sweeter in
the mouth" of Professor Ayeni, who created the path for me to
follow but he did not have the benefit of an inaugural lecture
before he retired: from this University in 1985. A look at the
records of inaugural lectures in the University revealed a
deficient data system as. we can only estimate that only 200
professors have given s.ince 1949. The lecture that I am giving
today is the 35th of all inaugural lectures from the
Faculty/College of Medicine which has produced 17% of all
inaugural lectures ever-given in the university. As at today, there
are 57 professors. in the College of Medicine.
Medical Statistics in the training of Undergraduate Medical
Students
As earlier mentioned, Professor Adetokunbo Lucas, the doyen
of public health introduced medical statistics into the medical
curriculum of the University of Ibadan and taught the course
himself until 1969. Because of his understanding of the multi-
disciplinary nature of public health, he recruited, the first
professional medical statistician, Professor Olusola Ayeni in
1968. Thereafter, Professor Lucas established a special unit of
medical statistics and realizing its uniqueness to medical
research and practice, located the unit in the first floor of the
new clinical science building housing the other players of the"
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medical profession (Surgery, Medicine, Pediatrics and
Obstetrics and Gyneacology). The experiences as told by the
'Mungo Park' of medical statistics in Africa was that of
ignorance of this new discipline that found its root in medicine
and medical research. The Medical Statistics course was taught
to medical students for only 8 hours as part of a course in the
pre-clinical years but was initially never examined. When the
senate finally approved that the course be examined under
Biochemistry, Professor Ayeni told me of a story of the Head of
Biochemistry setting questions on Biostatistics, a course he
taught as a medical statistician. And unfortunately, the question
was like a sentence with neither a verb nor a predicate. It took
the poorest student to point out this mistake. It came to the open
and the senate queried the professor of Biochemistry who
replied that the senate when approving the inclusion of
Biostatistics as an examinable course in the medical curriculum
did not specify who should set the questions. There are no two
'Lucases' when we talk of public health in University of Ibadan.
However, all researchers in medicine at that time benefited from
the only medical statistician, and such was the impact of the
professional medical statistician in the first 5years that they
clamoured for another one. Topics and terms like Chi-Square
(X2), Regression, Correlation, P-value, Random Sample, t-test,
ANOVA, have developed deep roots in medicine as they form a
compulsory part of the undergraduate medical curriculum. But
my experience has shown that medical statistics is not an
attractive subject to any medical or para-medical student. There
was in fact a dialogue with some medical students who wanted
to know from the Professor of Medical Statistics why they need
to study medical statistics at all. The professor answered;
"because statistics save life." And the students asked, "how?"
The professor answered, "statistics keep all the idiots out of the
medical or nursing profession."
Postgraduate Training in Medical Statistics
One major contribution to knowledge as a Professor of Medical
Statistics is the development of the science of medical statistics.
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Mr. Vice-chancellor sir, I am happy to announce that there has
been a dramatic progress in this area since 1996/1997 academic
session when a sub-department of Epidemiology, Medical
Statistics and Environmental Health (EMSEH) was carved out
of the Department of Preventive and Social Medicine for
administrative convenience. Perhaps it may be illuminating to
give some background information on how we came about a
sub-department.
Birth of EMSEH
It all started when I was appointed as the convener of the 4-man
committeeset up by the then Provost - Professor B. Osotimehin
who recommended that PSM should divide into 6 departments
for the academic growth of Public Health. It was not an easy
task but we managed to get 3 sub-departments of which
Epidemiology, Medical Statistics and Environmental Health
(EMSEH) was one. Unfortunately, I was away in Saudi Arabia
when the sub-departments were created.
When I finally returned to Nigeria in 1996, to assume co-
ordination of the sub-department of EMSEH, the situation was
like a Yoruba saying which means that "who comes last meets
the watery part of the soup". A sub-department, scattered, with
not enough office space, poor complement of non-teaching staff,
two typists, no secretary, no office for the HOD, and above all,
no specific academic programme except the MBBS held on to
by all members of the College, the only MPH in Environmental
Health programme still being contested, and so on, was all that
was inherited. It is to the Glory of God that today, we are not a
sub-department but a full department in the Faculty of Public
Health with well-defined academic programmes.
Postgraduate Education
The first step was to initiate the development of postgraduate
programmes and because of the staff strength and mix then-
four epidemiologists, two medical statisticians and one
environmental health specialist, we decided to start with a
Master's degree programme in Epidemiology and Medical
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Statistics and we relied largely on part-time lecturers.
Incidentally, before my final return to the Department in 1996,
Professor Ayeni and I, had discussed the possibility of a
Master's Programme in Biostatistics and he assured me of the
support of WHO through its special programme on Human
Reproductive Health Research and Development in which he
was the Chief Medical Statistician, and with his technical
support and that of Professor Oluwole Akande, who was Project
Manager of HRP in the WHO at that time, the proposal for an
M.Sc degree in Biostatistics was approved in principle.
The WHO support for this course which includes
scholarships for some students, building capacity to strengthen
the academic staff and enhance computer facilities, library and
communication equipment, was implemented in the 1998/1999
academic session. Since its inception, the programme has
trained 103 professional biostatisticians and epidemiologists,
both male and female, at the Master's degree level (see Table 2).
Of these, eleven were foreign students from other African
countries such as Ghana. Kenya, and Cameroon. Four others
have already completed their Ph.D. degrees, three in
Epidemiology and one in Medical Statistics, two of whom were
supervised by me.
Table 2: Distribution of Student Enrolment for
M.Sc Biostatistics Programme since inception
Session Male Female Total
1998/99 1 4 5
1999/00 6 2 8
2000/01 8 5 13
2001102 13 4 l7
2002/03 11 1 12
2003/04· 16 1 17
2004/05 10 1 11
2005/06 14 6 20
Total 79 24 103
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WHO Evaluation ofM.Sc Biostatistcs Course
The course was evaluated in July 2006 by a team of experts
from the World Health Organization and wondered how the thin
staff on ground could do such a wonderful job. They
interviewed some of the students and read a few of their
projects. They concluded that the quality and scope of the
Master's programme is comparable to any such programme in
the world. The evaluation team recommended continued
financial WHO support for the course for at least a further 2-3
years based on the high level of performance.
Other Master's Programmes
At the instance of the request of the WHO through the Federal
Ministry of Health, another Master's degree programme in Field
Epidemiology was developed and approved in the 2002/03
academic session in the Department. And in the 2003/4
academic session, yet another Master's Course Program, the
MPH in Medical Demography, the First of its kind in any
African University was developed and approved for the
Department-This-Course however also received some technical
support from the Mellinda 1mO-6atc1S Irrstinrre 'for Reproductive
Health based at the Johns Hopkins University, USA. Thus today
to the Glory of God, we have 6 Master's degree programmes in
the Department.
Mr Vice Chancellor Sir, we need more staff to cope with the
heavy academic postgraduate programmes run by our
Department. The impact of which has helped research output in
the College of Medicine, Federal Ministry of Health and other
medical and health agencies in Nigeria.
Conclusion
This lecture has revealed the science of medical statistics as the
microscope to understand health and disease. The diagnostic
criteria for numerous diseases have been developed using sound
statistical theories with the dominant contribution of probability
and multivariate analytic technique such as discriminant
analysis.
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Any medical statistician often gets worked up about other
peoples' activities so that he can make (a number of times) some
of them his own and assume full responsibility. One particular
attribute of a medical statistician is his being at home with
mathematics, having the ability to read the more mathematical
literature, to follow mathematical argument and use
mathematical. tools with some confidence. Every mathematical
topic should be of potential interest to a medical statistician but
what he needs is the relatively elementary bit. However, the
methodologically-oriented statistician is able to make the fullest
use of his non-medical basic training and by the generality of his
approach, may be successful in developing new and modified
techniques that may be of value far outside the immediate
context that prompted the works. He should however not leave
the task of extracting information from real data to the
epidemiologist. Both Medical Statisticians and Epidemiologists
should foster a symbiotic relationship to be more productive.
This is the basis of the tremendous strength of the Department of
Epidemiology and Medical Statistics emerging from our current
Department of EMSEH.
Sadly enough, the practice gaining unprecedented ground in
collaborative research between our medical researchers and
colleagues in foreign countries is that Nigeria is being turned to
a mere collecting site, whereby, the blood specimens as well as
data collected in some major studies (particularly on
HIV/AIDS), are sent directly to the foreign partners overseas. In
most cases the researcher in Nigeria cannot even access the data
after it has. been entered into the computer. I make bold to say
that this is not a collaborative research!
In any collaborative research, every professional is an equal
member of the research team, and so the best time to involve
every member, particularly the medical statistician is at the
planning stage. This is so that he can contribute technological
suggestions about the conduct of the research which may greatly
increase its impact or reduce its cost; and he/she can contribute a
good deal more than this if he/she has an adequate and broad
knowledge of the subject matter, which is often recommended.
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There is no amount of statistical massage that can bring the
truth out of a badly planned study. But a study developed
according to statistical science can be corrected for
appropriateness of statistical methods of analysis of data if
discovered later. From my experience, Medicine contains its
full quota of dominant personalities and if one of these can
persuade a medical statistician to be processing his data and be
providing him with the answers he expects, he will certainly turn
the statistician into his technician.
This inaugural lecture has shown beyond reasonable doubt
that a medical statistician as a professional understands the real
needs of his clients or employer, often very much better than the
client himself, and has the ability and status to persuade the
client to recognize his own interests and to abandon his less
useful flights of fancy. He has a professional skill to
recommend from a range of known and trusted techniques, those
research methods that in the given circumstance will achieve the
required effect at minimum cost and inconvenience to the client,
and finally, he has the professional integrity to resign his post or
commission if his recommendations are not accepted. This is the
true collaboration which I have found myself demonstrating as a
medical statistician in the medical milieu.
Thus, if the chief medical director of any hospital or the
director of a medical research group needs someone to do
routine data analysis, they can hire a well trained statistician or
buy a computer; just like what Paul told the Corinthians in his
first letter in Chapter 7 verse eight that "they do well". But if
they want a real medical statistician, they need to pitch their
expectations at a realistic level. In this regard, the medical
statistician on their staff can regard him/herself as a member of a
group of professionals which cuts across narrow specialties of
medicine, that he can give seminars, organize workshops and
take part in discussions at which his special problem can be seen
in their wide statistical context. As one of my professors at the
LSH and TM said, "the medical statistician is thus a generalist
whose special gift is precisely her lack of specialization. This is
the level of collaboration that has a promise. Because in this
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regard, the medical statistician is to be welcomed in the health
or medical domain as an equal colleague with the right of entry,
not a cap-in-hand visitor.
The bulk of our health problems in this country can benefit
more from a population based approach in which the members
of the 'club' of Public Health are well endowed with the
necessary expertise. The Faculty of Public Health in the College
of Medicine, University of Ibadan can change the poor health
situation in Nigeria if all members of the team come together
and throwaway what I label professional intolerance. The
physician in the group should not arrogate the administrative
,leadership role exclusively to himself and see others as support
staff. The Faculty of Public Health should live to the
expectations of the founding fathers and develop to a School of
Public Health.
The Federal Ministry of Health should set aside 3% of all
allocations to medical statistics. This will help to explain and to
assess how the remaining 97% is disbursed and spent.
Today's inaugural lecture calls for celebration as PSM has
developed to a Faculty of Public Health and my Department of
EMSEH for which I am head is almost becoming as large as the
old PSM. The Department of EMSEH has been a melting pot for
professional medical statisticians, epidemiologists and
environmental health specialists. Our products are now found in
Ghana, Cameroon, Kenya and in virtually all medical research
institutions and agencies in Nigeria.
ACKNOWLEDGEMENTS
I wish to thank the Almighty God who has made it possible for
me to be what I am, especially to stand before you today to give
an inaugural lecture, which I had thought has eluded me, as
those who became Professors 10 years after me have since given
their.
I will like to thank my parents, Elder & Mrs. Jacob Dada
Bamgboye of Blessed Memory who thought it fit to send me to
school despite the fact that they had no formal education. I also
thank my Uncle, Mr. Emmanuel Ayorinde Bamgboye who
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exposed me to the University of Ibadan since 1958 when I lived
with him to complete my primary school at the Abadina School.
I appreciate my late maternal uncle, Chief Ayo Omidiji whom I
followed to Ibadan in 1958 and who bought me my first suit in
1966 when I left secondary school and late Chief Titus Oke who
coached me at home for the A-levels in Pure and Applied
Mathematics in 1967, working sometimes late in the night in
spite of his busy schedules.
I am most grateful to Professors M.I Iro and Opeyemi ala
who first introduced Medical Demography to me as a Subset of
Medical Statistics in 1973. I thank the University of Ibadan for
employing and allowing me to travel overseas when it mattered,
to have Master's and Doctorate degrees. In this respect, I want
to thank Professor E.O Akande specially, who as Dean of the
Faculty of Medicine in 1978, recommended the approval of a
leave of absence with pay for me and the second day approved
the recommendation as Acting Vice-Chancellor. I appreciate my
supervisor and mentor, the' late Professor William Brass and the
contributions of Professors Rasia Zaba, John Blacker, John
Simon, and MJ.R Healy and the entire faculty members in the
London School of Hygiene and Tropical Medicine between
1976 and 1983.
I thank Professor Olusola Ayeni immensely, for bringing
happiness to the Department when it mattered, by developing a
Master's programme in Biostatistics and for facilitating the
financial support for the programme and I also appreciate his
intellectual review of the manuscript of today's inaugural
lecture. I appreciate highly, late Professor Benjamin Osuntokun
for his mentoring, Professor M.T Shokunbi for making good his
promise in facilitating the creation of the Faculty of Public
Health and the support of Professor I. F. Adewole, former
Provost of the College of Medicine for the growth of EMSEH.
I thank Professor Adefunke Oyemade who encouraged me
to travel to Saudi Arabia, Professor Olu Longe, who submitted
my CV to the Department of Family and Community Medicine,
King Saud University and the then Head of Department there,
Prof Shabrawy Alii, one of the leading Public Health Physicians
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in the World(Africa) who recommended instant appointment for
me on seeing my CV.
I thank my Dean, Professor Akinyele who gave me the
opportunity of an inaugural lecture and read through the
manuscript for constructive contributions, and I thank all the
members of staff of my Department. Permit me to mention
Professor J.D Adeniyi, a gentle and honest man to the core, and
Professor A.B.O.O Oyediran, the man I always admire, who has
inspired me on many occasions in my academic pursuit.
I thank my sister, Mrs. Florence Ogundare Awayino for her
kindness to me at all times. I also appreciate Mr. Thompson
Akinwunmi for accommodating me in his lOB, Repton Court in
Hommerton area during my very first visit to London in 1976.
My uncle, Mr. Joseph Omidiji, is also appreciated. He has
always stayed with me in times of need.
You will agree that you need to be spiritually healthy
according to WHO to be healthy and so I have a full
complement of members of my church from C.A.C., Oke-
Agbara, Prophet M. O. Olowere and his wife, our District
Supretendent, Pastor Adams and the District Evangelist Pastor
Farayola and a host of other pastors including Pastors Gbuyiro,
Omidiji, Oluwasanmi and Faturoti, as well as elders and
Deaconesses. I thank them all. I also thank the President of CAC
worldwide, Pastor (Dr) E.H.L.Oluseye and members of the
governing council of Joseph Ayo Babalola University (JABU)
headed by the Chairman, Professor A.M. Imevbore and other
members of staff.
My appreciation goes to the Alaaye of Efon-Alaaye Oba Dr.
E.A. Aladejare who is visiting this hall for the 2nd time in a
month , his Olori and other sons and daughters of Efon Alaaye
present. I appreciate and thank my friend of 43years 10 months
and 2 days for his care and encouragement in turbulent and
difficult times in my life. He is on a special assignment in Benue
State but had to be here today for this special occasion. I am
talking of no less a person than Professor James Oladipo
Kolawole, a professor of Political Science and current Deputy
Vice-Chancellor University of Ado Ekiti. I am grateful to our
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senior brother Mr. Rufus Kolawole for the 201 pounds he gave
me in 1981 when University of London demanded some money
I did not have before they could allow me to defend my Ph.D.
thesis. I appreciate my two siblings, Mr. Ezekiel Adebayo
Bamgboye and Dr. Isaac Adeleke Bamgboye.
Finally, I will like to thank my better half, Mrs. Ebun Ayodele
Bamgboye who has just completed her Ph.D in Virology and
currently Chief Technologist, IMRAT, College of Medicine, for
her ability to cope with the family situation when I am away on
several occasions or come home late from the office.
Lastly and not the least, I will like to pay tribute to my
children, Miss, Eunice Adeola Bamgboye, the career lady and
understanding daughter, my ever smiling son, Ebenezeer
Adebola Bamgboye and the baby of the family, Dr Eniola
Adetola Bamgboye, who typed a significant proportion of the
manuscript for this inaugural lecture.
Thank you and God Bless You All.
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