Introduction to Epidemiology and Population Sciences

Lecture by Prof Mieke Van Hemelrijck

• Part of Transforming Cancer Outcomes through Research (TOUR) at Kings College London

Key Objectives

• Define and explain the relevance of epidemiology in population health.
• Understand key concepts such as exposure, outcome, and risk.
• Differentiate between prevalence and incidence in public health.
• Describe and distinguish relative and absolute measures of effect.
• Identify confounding sources and strategies to control confounding.
• Define effect modification and distinguish it from confounding.
• Appreciate historical context and significance of epidemiological work.

TOUR Overview

• Aim: Improve healthcare outcomes by translating oncology research into clinical practice.
• Focus on clinical cancer epidemiology.
• Methodology for prevention, diagnosis, treatment outcomes, and cancer survivorship.

Modules Offered

1. 4BBY1002: Introduction to Clinical Exercise Epidemiology
2. 5MCS1000: Introduction to Epidemiology & Population Sciences (15 credits, Semester B)
3. 6MCS1001: Advanced Epidemiology & Population Sciences (15 credits, Semester B)
4. 6MCS1000: Cancer in Context: Public Health & Clinical Epidemiology (15 Credits, Semester A)

Historical Context: Dr John Snow

• Widely regarded for his work in London with a famous case involving a pump handle, leading to advancements in public health.

What is Epidemiology?

• Study of disease distribution and determinants in human populations.
• Aims to prevent disease by identifying and eliminating determinants.
• Involves biostatistical methods.

Key Concepts in Epidemiology

• Exposure: Risk factor or characteristic influencing an event.
• Outcome: Disease, progression, death, comorbidity.
• Prevalence: Proportion of a population with a condition at a specific time.
• Incidence: Proportion developing a condition over a period.
• Risk: Probability of disease occurrence in a time interval.
• Relative and Absolute Effects: Comparisons of exposed vs unexposed.

Confounding

• Distortion of the effect of exposure due to extraneous factors.
• Classic examples: Birth order and maternal age on Down syndrome.
• Control methods: Randomisation, Restriction, Matching, Stratification.

Effect Modification

• Interaction between risk factors modifying outcomes.
• Example: Physical activity’s effect on heart disease risk depending on BMI.

Course Content Highlights

• 5MCS1000: Includes study design, bias, confounding, causality, RCTs, behavioural and implementation sciences.
• 6MCS1001: Covers lifestyle markers, systematic reviews, pharmaco-epidemiology, behaviour, real-world evidence.
• 6MCS1001: Focuses on cancer epidemiology, behavioural sciences, RCTs vs real-world evidence, quality of life.
• 6MCS1000: Public health and clinical epidemiology related to cancer.

Contact

• Prof Mieke Van Hemelrijck, email
• TOUR Team Website