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Introduction to
Epidemiology
and Population
Sciences
Prof Mieke Van Hemelrijck
Transforming cancer OUtcomes through
Research (TOUR)
Kings College London Overview TOUR team
Modules
Introduction to Epidemiology and
Population Sciences
Basic Vocabulary and Concepts
Details of the Modules Learning outcomes After this lecture you should be able to:
Define the term epidemiology and explain its relevance in the
context of population health.
Understand the scope of epidemiology, including key concepts
like exposure, outcome, and risk.
Differentiate between prevalence and incidence, and describe
how these measures are used in public health.
Describe the concept of risk and distinguish between relative
and absolute measures of effect.
Identify common sources of confounding and explain how
confounding can distort associations in epidemiological research.
Understand strategies to control for confounding at the design
and analysis stages of studies.
Define effect modification and distinguish it from confounding
using relevant examples.
Appreciate the historical context of epidemiology, including the
significance of Dr John Snows work in London.
Recognise the role of epidemiology and population sciences in
medical fields such as cancer research and healthcare outcomes. TOUR To use science to improve healthcare
outcomes by translating oncology
research into clinical practice.
A heterogeneous set of activities
with clinical cancer epidemiology at
the core.
Provide a methodology for
researching prevention, early
diagnosis and detection, treatment
outcomes, and living with and
beyond cancer.
Role of clinical epidemiology across
the entire cancer patient pathway. Modules 4BBY1002: Introduction to Clinical
Exercise Epidemiology
5MCS1000: Introduction to
Epidemiology & Population
Sciences 15 credits in Semester
B
6MCS1001: Advanced
Epidemiology & Population
Sciences 15 credits in Semester
B
6MCS1000: Cancer in Context:
Public Health & Clinical
Epidemiology 15 Credits in
Semester A Introduction
# to
# Epidemiolog
# yIt all started in London ... with a
## pump handle
> 7
Dr John Snow (1813-1858) The John Snow Pub
Broadwick Street, Soho What is epidemiology ?
According to the world health organization:
Epidemiology is the study of the distribution and
determinants of health-related states or events (including
disease), and the application of this study to the control of
diseases and other health problems
> 8
# What is epidemiology?
The study of the distribution and determinants of disease in occurrence in
human populations
Outcome of interest
Exposure of interest
Biostatistical methods
> 9
## What is epidemiology?
> 10
Ultimate aim: To prevent disease by
eliminating, reducing exposure to its
determinants
Method: Identification of disease determinants
Context: Medicine, public health The scope of
# epidemiology
> 11
Exposure
Risk factor
Cause
Outcome
Event
Effect The scope of
# epidemiology
> 12
Exposure
Risk factor
Cause (e)
Disease
Event
Effect (e)
Outcome
Death
Effect (p)
Intervention
as a consequence of event
Cause (p)
> Etiognosis (e) Diagnosis Prognosis (p)
## Vocabulary
> 13
Study
base Exposure Outcome Prevalenc
e
Incidence Risk Confound
er
Effect
Modifier Study
# base
> 14
Reference population
Source of the study population
Population giving rise to the cases
Defined before cases appear by a
geographical area or some other entity
like a cohort study Study base?
> 15
## Exposure
An exposure, risk factor, or other characteristic being observed or
measured that is hypothesized to influence an event or manifestation
> 16
## Exposure
## ?
> 17
## Outcome
> 18
Disease Disease
progression Death
Comorbidity Questionnaire
data
Biological
endpoints
expression
levels Outcome
## ?
> 19
# Prevalence
Proportion of a population found to have a condition at a specific
point in time
> 20
IARC, Globocan Incidence
> 21 IARC, Globocan
Proportion of a population found to have developed a
condition during a specific period of time. Risk
Probability of disease developing in an individual in a
specified time interval
> 22
## Risk?
> 23
## Measurements of effect
Relative: exposed versus unexposed
Absolute: i.e. incidence, prevalence Courtesy of Prof David Spiegelhalter
100 people eating a
bacon sandwich every
other day
## What does this
## mean? Courtesy of Prof David Spiegelhalter
100 people NOT eating a
bacon sandwich every
other day
## What does this
## mean? 25g processed meat a day associated with 19% increased risk of
getting bowel cancer
Such Relative risks are known to exaggerate apparent
effect
Need absolute risks
Around 6% of people will get bowel cancer anyway
So what is an 19% increase over 6%?
1.19 times 0.06 = 0.07
> Courtesy of Prof David Spiegelhalter
## Confounding
The apparent effect of the exposure of interest is distorted
because the effect of an extraneous factor (confounder) is
mistaken for or mixed with the actual exposure effect (which
may be null), leading to bias.
Confounding may be considered a confusion of effects Classic
## example of
## confoundin
## g
Increasing trend for prevalence of Down
syndrome with increasing birth order = effect
of birth order on the occurrence of Down
syndrome
Effect of birth order is blend of effect of birth
order itself and effect of other variable closely
correlated with birth order
Maternal age is much stronger associated with
Down syndrome
Mixing effects Another
## example
In men baldness is associated with the risk
of myocardial infarction
Age increases both the likelihood of
baldness and the risk of myocardial
infarction; thus age confounds the
association between baldness and
myocardial infarction Criteria
## for a
## confoundi
## ng factor
A confounding factor must be a risk
factor for the disease
A confounding factor must be
associated with the exposure under
study in the source population
A confounding factor must not be
affected by the exposure or the
disease. Cannot be an intermediate
factor. Do the
## criteria
## hold? causes causes
Sodium elevated blood heart disease
intake pressure
Is elevated blood pressure a confounder?
# Do the criteria hold? Control of
## confoundi
## ng
Randomisation
Restriction
Select subjects with similar values for
confounders, e.g., select only old, male
Matching
Match on confounding variable to force
comparison between cases and controls
Stratification
Modelling Review of confounding
1. Associated with the outcome of interest independent of its relation to
the exposure of interest
2. Associated with the exposure of interest in the study base that
produced the cases
3. Cannot be an intermediate variable on the causal chain leading from
the exposure of interest to the onset of disease
Confounding can be altered at the study design stage:
Matching
Restriction
Stratification
Randomization The strength of the association
between the exposure and the
outcome varies by levels of a
third variable
Effect modifier = Interaction
Term
> http://essedunet.nsd.uib.no/cms/topics/regression/7/2.html
# Effect
# Modification Effect
modificatio
n?
Refers to a situation in which two or more risk factors
modify one anothers effects on an outcome.
The effect of the physical activity categories sedentary or
active on the presence or absence of chronic heart disease
might differ depending on some third factor, such as sex;
physical activity might reduce the risk of disease among
men but not in women.
Sex would be the effect modifier. Example
## of effect
## modificati
## on
The effect of physical activity
assessed by questionnaire on the
risk for chronic heart disease (CHD)
may depend on BMI.
The risk of disease among the least-
active people might be greatest
among those having the highest
BMI.
If so, BMI would be considered an
effect modifier in the association
between activity and CHD. Effect
## modifier vs
## Confoundi
## ng factor Questions?
Prof Mieke Van Hemelrijck
[email protected]
www.kcl.ac.uk/tourteam Details of
# Modules on
# Epidemiolog
# y &
# Population
# Sciences
> 5MCS1000
> 6MCS1000
> 6MCS1001
## 5MCS1000
L1: Introduction and overview
L2: Study Design
L3: Bias and Confounding
L4: Causality and statistical interpretation
L5: Introduction to Randomised Controlled Trials
L6: Introduction to Behavioural Sciences
L7: Introduction to Implementation Sciences
L8: Introduction to Qualitative Research Methods
L9: Methods in global cancer: how to utilise
mixed methods for comparative systems?
L10: Ethics, data integrity, and final summary
T1-T6: Review of theory through application of
research papers
Introduction to Epidemiology &
Population Sciences 6MCS1001
L1: Introduction and overview
L2: Measurements of life style markers & their
correlates
L3: Introduction to systematic reviews and meta-
analysis
L4: Pharmaco-epidemiology
L5: Importance of behaviour in health outcomes
L6: Real World Evidence
L7: Introduction to screening
L8: Importance of patient reported outcomes
L9: Clinical epidemiology
L10: Health systems & services research (cancer)
T1-T8: Review of theory through application of
research papers
Advanced Epidemiology &
Population Sciences 6MCS1001
L1: Introduction to clinical cancer epidemiology
L2: Introduction to behavioural sciences for cancer
interventions
L3: Randomised controlled trials and/or/versus Real
World Evidence
L4: Introduction to mixed methods
L5: Quality of Life research for cancer patients
L6: The use of Core Outcome Sets in cancer research
L7: Linking epidemiology and shared treatment
decision-making in the cancer pathway
L8: The important of patient and public
involvement/engagement
L9: Introduction to implementation sciences
T1: Case study 1: Global Oncology Bridging
research and patient care
T2: Case study 2: Health inequalities - Cancer care in
the prison population
T3: Case study 3: Cancer and Exercise
Cancer in Context: Public
Health and Clinical
Epidemiology