Summer School

Non-residential Summer School on the Social Determinants of Health

Monday 3rd - Friday 7th July 2017

To get on the school mailing list contact:

s.skinner@ucl.ac.uk

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Download the programme prospectus 

MSc Health Society Prospectus
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Course Content

Module descriptions can be found below:

Social Epidemiology: Dimensions of Inequality

Module Code EPIDGS46
Module Type Compulsory
Credits 15
Module Leader Dr Nicola Shelton

Aim

The aim of this module is to provide an introduction to social epidemiology, describe basic theories and concepts used in social epidemiology and studies of health and social inequalities, present current evidence of the influence of range of factors on health inequalities and encourage critical assessment of that evidence.

Learning outcomes

By the end of the module the student will be able to:

identify social determinants of morbidity and mortality and health behaviours, have an understanding of the relationship between socioeconomic status and a range of major risk factors for health; identify methods of measurement of major risk factors for health; identify policies developed to reduce health inequalities; debate the role of socio-economic inequalities in health

Content:

  • Historical (socio-economic status) SES inequalities
  • Socio-economic position and health
  • Gender, health and SES
  • Ethnicity, health and SES
  • Smoking, and SES
  • Alcohol consumption and SES
  • Physical Activity and SES
  • Place, health and SES
  • Social capital, social networks and health and SES
  • Transport and health and SES
  • Work and health and SES
  • Material, behavioural and psycho-social pathways

Teaching and Learning Methods

Sessions consist of a lecture and discussion or small group work. Materials will be posted on Moodle (www.ucl.ac.uk/moodle). Where reading materials are distributed in advance, students will be asked to read these prior to the session.

Constituency

This module is compulsory for all students in MSc/Diploma Health and Society: Social Epidemiology. The module may also be attended by other postgraduate students from the Faculty of Population Health and other faculties at UCL.

Assessment

  • Unseen exam (2 hours) 50%
  • Paired presentations (10 minutes) 50%

Epidemiology

Module Code EPIDGS31
Module Type Compulsory
Credits 15
Module Leader Prof Eric Brunner & Dr Anne Peasey

Aims and objectives

Their overall aim is to provide students with 

  • Basic knowledge of epidemiological concepts and methods principles of study design 
  • Appreciation of the errors that may arise in epidemiological studies 
  • Experience in interpreting and evaluating epidemiological data 
  • Examples of the contribution of epidemiology to knowledge of the main determinants of health and disease 
  • A foundation on which to build detailed knowledge appropriate to particular research interests

Description

Introductory course in epidemiology providing a grounding in key concepts, namely case definition, measures of effect, study design types (cross-sectional, longitudinal, case-control, ecological), bias and confounding, screening, health surveillance, genetic epidemiology. Contact hours are divided approximately equally between theory and practical sessions in order that students consolidate the concepts by applying them in a variety of contexts relevant to clinical and social epidemiology.

Teaching and Learning

Students attend two half-day sessions on Wednesdays and Thursdays every week in term 1. The majority of sessions will involve a lecture and a practical session. Teaching materials will be placed on Moodle, providing online access to lecture notes and practical assignments.

Assessment

Formative: written exercise during reading week

Summative: single best answer exam in November (50%) and short answer questions exam in December (50%)

Constituency

This module is compulsory for all students in MSc/Diploma Health and Society: Social Epidemiology and MSc/Diploma Dental Public Health. The module requires students to attend EPIDGS32 Basic Statistics for Medical Sciences or have attended a similar course.

Recommended Reading

Recommended textbook: M Porta. A dictionary of epidemiology, 5th edition, OUP 2008

Other texts:

  • K Rothman, Epidemiology: An Introduction, OUP 2002
  • R Bhopal, Concepts of epidemiology, OUP 2002
  • C Hennekens & J Buring, Epidemiology in Medicine, Little Brown 1987

You may want to browse the selection of epidemiology texts in a medical bookshop and choose one you like.

Basic Statistics

Module Code EPIDGS32
Module Type Compulsory
Credits 15
Module Leader Dr Hynek Pikhart

Aims

The main aim is to introduce the basic statistical methods used in epidemiological and public health research. Students will also learn to make practical use of the statistical computer package STATA.

Learning Outcomes

By the end of this Module students should be able to:

  • Describe the role of statistical methods in epidemiological and public health research;
  • Present results effectively by making appropriate displays, summaries, and tables of data;
  • Understand the problem of sampling variation, and the role of statistical methods in quantifying this;
  • Select an appropriate statistical method for the analysis of simple data sets;
  • Correctly interpret the results of statistical analyses reported in the health literature;
  • Perform simple statistical analyses using STATA, and
  • Interpret their findings from statistical analyses and present these findings in a clear, concise, and logical manner.

Description

This module will provide an introduction to some basic statistical methods commonly used in biomedical research for analysis of categorical and continuous outcomes, including calculation of risk ratio, odds ratio, chi square, t-test, ANOVA. Additionally, students will be introduced to sampling, sample size and power calculations and non-parametric testing as well as basics of survey design and survey analysis. Finally, students will learn standardisation methods as well as calculation of standardised means.

Constituency

This module is compulsory for all students in MSc/Diploma Health and Society: Social Epidemiology; MSc/Diploma Dental Public Health; MSc Genetics of Human Disease, MSc Pharmacogenetics and MSc in Cardiovascular Sciences. The module may also be attended by other postgraduate students from Division of Population Health, Faculty of Population Health and other faculties. The module does not assume any previous knowledge of statistics, although students who have some such knowledge will be aided by it. This module will be followed by modules Regression Modeling (MSc/Diploma Health and Society: Social Epidemiology; MSc/Diploma Dental Public Health), Advanced Statistics (MSc/Diploma Health and Society: Social Epidemiology), and Statistical Genetics (MSc Genetics of Human Disease and MSc Pharmacogenetics) in terms 2 and 3.

Recommended reading:

Kirkwood B & Sterne J. Essential Medical Statistics, Blackwell Science (UK), 2003. ISBN  0865428719

Advanced Reading (not necessary for the module)

Rothman K, Greenland S, Lash TL. Modern Epidemiology. Lippincott Williams & Wilkins, 2008 (3rd Edition).

Session structure

Most sessions consist of a 60 minute lecture and 90 minute computer-based practical session. The statistical package STATA will be used in computer practical sessions. There are several sessions with slightly different outlines, and these will be described at the beginning of the module.

Assessment

Data analysis exercise – task will be given to the students at the end of session 10. Students will be asked to analyse given dataset and write report (approximately 1500-2000 words) structured in the way described in the task. Students will be asked to submit the report on November 18th.

Exam – there will be 2 hours written exam.

Social Determinants of Global Health

Module Code EPIDGS41
Module Type Compulsory
Credits 15
Module Leader Dr Ruth Bell & Prof Sir Michael Marmot

Aim

The general aim of the module is to introduce the concepts and ideas underlying the social determinants of health in a global context.

Learning Outcomes

By the end of the course, the students should be able to:

  • Locate the discipline of social epidemiology within the broader context of public health and global health
  • Describe the social gradient in health in populations in high, middle and low income countries
  • Understand the relationships between gender, social inequalities and health inequalities
  • Understand the relationships between social inequalities,  health inequalities and human rights
  • Outline the reasons why inequalities in health exist in different countries
  • Conceptualise how social determinants affect individual health and the distribution of health
  • Analyse the policy implications of SDGH evidence 

Content

The following topics will be covered in teaching sessions:

  • Social determinants of health:  concepts and recent history
  • Measuring distribution of health and the social determinants of health
  • Philosophy and health inequalities: why we have to care
  • Early life, socioeconomic position and health
  • Employment/lack of employment and health inequalities
  • Welfare policies and health
  • Gender and health
  • Health in cities
  • Disability inequality and human rights
  • Sustainable development and health equity
  • Country case studies
  • Societal transformation and health in Central and eastern Europe
  • Teaching sessions will be followed by revision session putting all the topics into perspective.

Teaching and Learning Methods

Students will attend up to 6 half day sessions per week in first three weeks of term 2. These sessions will consist of short informal lectures and related practical exercises or discussions/debates. Moodle will be used to give students access to reading materials, lectures and other associated work.

Constituency

This module is compulsory for all students in MSc/Diploma Health and Society: Social Epidemiology. The module is made available to other students as optional module, and is usually attended by many students from MSc Global Health and development and few other students from different MSc courses.

Assessment

Small group presentation (10-15 minutes) 30%

Essay (2,500 words) chosen from two possible topics 70%

Regression Modelling

Module Code EPIDGS43
Module Type Compulsory
Credits 15
Module Leader Dr Paola Zaninotto 

Aim

To provide students with:

  • Basic knowledge of concepts and methods used in statistical modelling
  • Principles of data analysis
  • A foundation on which to build detailed knowledge appropriate to particular research interests
  • Appreciation of the errors that may arise in the analysis of data in biomedical studies
  • Experience of solving the problems

Learning Outcomes

Knowledge: selecting and using correct statistical regression methods for the analysis of simple datasets using different types of variables.

Skills: data handling and use of statistical software, using appropriate tests and methods, figures and summaries of the results, interpreting statistical results related to specified research questions, presenting the results in a clear way to non-statisticians.

Content

A course in biomedical statistics and statistical computing providing an advanced level of knowledge in key concepts (such as statistical methods for continuous and categorical variables), and introducing regression modelling (linear regression, logistic regression, multinomial regression, ordered polytomous regression, Poisson regression, Cox regression). Strategy of the analysis as one of the key bio statistical concepts is discussed in the final parts of the course. Statistical modelling is illustrated using Stata statistical software. Contact hours are divided between theory and computer practical sessions in order that students consolidate the concepts by applying them in a variety of contexts relevant to clinical and social epidemiology.

Teaching and Learning Methods

Students will attend 10 half-day sessions in term 2. The majority of sessions will consist of a lecture (90 minutes) and a related practical computer based exercise (90-120 minutes).

All the materials from the lectures will be available on the course Moodle page, datasets for the computer-based seminars, seminar tasks, model answers for the seminars and materials for self-learning will be also available on Moodle. FAQ section and on-line discussion will be maintained on Moodle.

Assessment

Data analysis exercise 50% (1500 words)

Unseen exam 50% (1 hour)

Constituency

This module is compulsory for students taking MSc/Diploma Health and Society: Social Epidemiology and MSc/Diploma in Dental Public Health. Subject to places being available, the module is also available for other postgraduate students from UCL such as students from MSc Global health and Development. 

Research Methods for Social Epidemiology

Module Code EPIDGS45
Module Type Compulsory
Credits 15
Module Leader Dr Anne Peasey

Aim

The main aim is to introduce and develop research skills used in epidemiological and public health research, in particular critical appraisal of evidence in quantitative research and successful grant proposal writing.  There is also an introduction to qualitative research methods.

Intended Learning Outcomes

By the end of the module, students should be able to:

• Compare and contrast qualitative & quantitative research methods in terms of theory, data collection and analysis

• Describe and understand strengths & limitations of epidemiological study designs

• Critique evidence surrounding a defined quantitative research topic

formulate a research question, objectives and hypotheses

• Define and justify a study design to address a particular research question

• Propose how to identify and take account of potential sources of bias

• State how issues of confounding and effect modification will be dealt with in their study

• Draw on the knowledge and skills described above to prepare a grant proposal on a standard proforma in response to a funding call

Teaching and Learning Methods

Sessions are varied, with most involving a discussion, practical session, small group work or a computer-based practical. Materials will be posted on Moodle (www.ucl.ac.uk/moodle). Some reading materials may be distributed in advance and students will be asked to read these prior to the session. Students need to log in to the system using their UCL username and password. All important announcements will be made in “News forum” on module pages.

Constituency

This module is compulsory for all students in MSc/Diploma Health and Society: Social Epidemiology. The Qualitative research sub-module will be jointly attended by students from MSc DPH. The module may also be attended by other postgraduate students from the Faculty of Population Health.

Assessment

Formative: students submit an outline of the grant proposal and receive written feedback to guide the development of their grant proposal.

Summative: students prepare a full grant application on a topic related to social epidemiology using a standard form similar to those currently used by leading research funding bodies (100% of mark for this module).

Health Inequalities over the Life Courses

Module Code EPIDGS42
Module Type Compulsory
Credits 15
Module Leader Dr Anne Peasey and Dr Elizabeth Webb

Aim

The aim of this module is to provide an overview of the fundamental theories and concepts used in life course epidemiology, present current evidence of the influence of factors over the life course on health inequalities and encourage critical assessment of that evidence.

Intended Learning Outcomes

By the end of the module, students should be able to:

  • Describe and distinguish between the different models and concepts used in life course epidemiology
  • Understand the main UK data sets that are available to life course researchers
  • Understand the advantages and disadvantages of a life course approach to health inequalities
  • Debate and critically assess the role of factors influencing health across the life course, and how health inequalities are affected

Content

Topics covered in the module include:

  • Life course epidemiology
  • Social-biological interface over the life course
  • Early child development and health inequalities
  • Adolescent health
  • Obesity
  • Gender divisions of labour, family & health
  • Cognitive ageing
  • Physical capability

Teaching and Learning Methods

Sessions consist of a lecture and discussion or small group work. Materials will be posted on Moodle (www.ucl.ac.uk/moodle). Where reading materials are distributed in advance, students will be asked to read these prior to the session. Students need to log in to the system using their UCL username and password. All important announcements will be made in “News forum” on module pages.

Constituency

This module is compulsory for all students in MSc/Diploma Health and Society: Social Epidemiology. The module may also be attended by other postgraduate students from the Faculty of Population Health and other faculties at UCL.

Assessment

Unseen short answer questions exam (1 hour) 50%

Essay chosen from two topics (2,000 words) 50%

Ethnicity, Migration and Health

Module Code EPIDGS21
Module Type Optional
Credits 15
Module Leader Dr Alice Forster

Aim and objectives

The course aims to theorise and understand ethnicity and race, describe issues related to research exploring ethnicity and health in the UK and elsewhere, describe patterns of ethnicity and health in the UK and explanations for ethnic differences in health, understand the impact of migration on health, understand the role of health behaviours in the development of ethnic differences in health and describe the impact of racism and poverty on health.

Learning Outcomes

By the end of this module, the student should be able to:

  • Identify different approaches to understanding/theorising ethnicity and race
  • Understand the social nature of ethnicity, its dynamic nature, and its location in (unequal) social relations
  • Summarise the evidence on ethnic inequalities in health around the world
  • Reflect on data limitations of much research on ethnicity and health
  • Theorise the main causal pathways that relate to ethnic inequalities in health and health services
  • Combine this understanding of causal pathways with the wider social inequalities faced by ethnic minority groups

Teaching and learning methods

Lectures, tutorials, seminar presentations and practical sessions. Moodle will be used as an information portal for participants and source for reading materials.

Assessment

Essay 50% (2500 words)

Oral Presentation 50% (10-15 minutes)

Bibliography

Nazroo J Y (1998) 'Genetic, cultural or socio-economic vulnerability? Explaining ethnic inequalities in health', Sociology of Health and Illness, vol. 20, no. 5, pp. 710-730

Nazroo J (ed.) (2006) Health and Social Research in Multiethnic Societies. London: Routledge.

Bhopal R (2007) Ethnicity, Race, and Health in Multicultural Societies: Foundations for better epidemiology, public health, and health care Oxford: Oxford University Press

Advanced Statistical Modelling

Module Code EPIDGS20
Module Type Optional
Credits 15
Module Leader Dr Owen Nicholas

Aims

The main aim is to introduce some advanced statistical methods commonly used in epidemiological and public health research.

Objectives

For each method covered in this Module, students should be able to:

  • Describe the statistical method and understand when it is appropriate to apply the method;
  • Understand how to interpret results from analyses using each method;
  • Describe methods to check main assumptions underlying the method;
  • Interpret the results of statistical analyses reported in the health literature;
  • Perform statistical analyses using STATA, and;
  • Interpret findings from statistical analyses, and present these findings in a clear, concise, and logical manner.

Description

This module will provide an introduction to some advanced statistical modelling methods commonly used in epidemiological research, including multilevel models (that allow the study of influences on health that operate at different levels, such as the study of associations between area characteristics and health of individuals), principal components models (used to form new variables which are linear composites of the original variables), factor analysis models (used to develop scales which measure latent or unobservable constructs), path models and an introduction to structural equation models (that allow the testing of complex models involving hypothesized pathways between risk factors and disease).

Each session consists of a 2 hours lecture and 2 hours computer-based practical session. The statistical package STATA will be used in computer practical sessions. There may be 2 or 3 additional non-practical sessions to review practical work. Teaching materials will be placed on Moodle, providing online access to lecture notes and practical assignments.

Assessment

A practical written assignment based on conducting analyses using STATA, understanding and interpreting data analysis. The assignment and data set will be given out towards the end of the module and is 100% of the mark for this module


Term 1

Compulsory Modules

  • Social Epidemiology: Dimensions of Inequality
  • Social Determinants of Global Health
  • Epidemiology
  • Basic Statistics 

Term 2

Compulsory Modules

  • Regression Modelling
  • Research Methods

Term 3

Compulsory Module

  • Health Inequalities over the Life Course

Term 2 or 3

Optional Module

The MSc runs two optional modules in term 3

  • Ethnicity, Migration and Health
  • Advanced Statistical Modelling

You can alternatively choose any module in any discipline within UCL either in term 2 or 3.  

The MSc degree (180 credits) is calculated is as follows:
120 Credits:
Course work assessment including multiple-choice questions and open questions tests, essays, presentations, data analysis exercise, and grant proposal exercise.
60 Credits: Dissertation

The Diploma assessment is calculated as follows:
120 Credits: Course work assessment including multiple-choice questions and open questions tests, essays, presentations, data analysis exercise, and grant proposal exercise.

Teaching assessment
Formal appraisal of teaching quality is carried out by colleagues, external assessors and anonymous student evaluation.

Page last modified on 03 mar 16 10:14