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Title Methods for Life Course Epidemiology
Course number 2968
Programme Epidemiologi
Language English
Credits 1.5
Date 2020-12-07 -- 2020-12-11
Responsible KI department Institutet för miljömedicin
Specific entry requirements Knowledge equivalent to "Epidemiology I: Introduction to epidemiology", "Biostatistics I: Introduction for epidemiologists", "Epidemiology II: Design of epidemiological studies", "Biostatistics II: Logistic regression for epidemiologists" and "Biostatistics III: survival analysis for epidemiologists" or corresponding courses.
Purpose of the course The course critically reviews life course theory and methods for analysis of longitudinal data with applications to life course epidemiology. A special focus is put on discussing and applying methods for mediation analysis.
Intended learning outcomes After successfully completing this course, the student is expected to be able to:
- Discuss the most common life course models and their implications for health policy
- Evaluate strengths and limitations in using register data for research in life course epidemiology
- Explain the applicability of visualization techniques for research in life course epidemiology
- Identify and apply appropriate methods for mediation analysis
- Perform mediation analysis, and interpret and communicate the derived results
- Critically appraise evidence from life course epidemiological studies.
Contents of the course This course focuses on an overview and critical discussion of life course theory and methods for analysis of longitudinal data with applications to life course epidemiology. We shall review, discuss and apply different approaches to addressing common challenges in register-based, life course and intergenerational research through both methodological innovations and adaptation of existing statistical methods. Examples of techniques to be discussed and applied include methods for visualizing and modeling changes in categorical variables, modeling the effects of binary exposure variables over the life course, and techniques for mediation analyses. We shall also discuss and apply concepts and methods from the field of causal inference to life course studies. The statistical software used in the lectures and computer labs is Stata.
Teaching and learning activities Lectures, computer labs and individual and group work involving analysis of real-life research problems using longitudinal data and a statistical software (Stata).
Compulsory elements Individual written examination (summative assessment).
Examination To pass the course, the student has to show that the intended learning outcomes have been achieved. The assessment methods used in this course are individual and group assignments (formative assessment) and an individual take-home examination (summative assessment). The focus will be on application of methods to research problems and interpretation of results, rather than mathematical detail. The examination is viewed as contributing to the development of knowledge, rather than a test of that knowledge. Students who do not obtain a passing grade in the first examination will be offered a second examination within two months of the final day of the course.
Literature and other teaching material Suggested reading:

Ben Shlomo Y, Mishra G and Kuh D. Life course epidemiology. Pp. 1521-1549. In: W. Ahrens, I. Pigeot (eds.) Handbook of Epidemiology, 2nd edition, DOI 10.1007/978-0-387-09834-0 56, © Springer Science+Business Media New York 2014. http://link.springer.com/referenceworkentry/10.1007%2F978-0-387-09834-0_56

De Stavola BL, Daniel RM. Incorporating concepts and methods from causal inference into life course epidemiology (Commentary). Int J Epidemiol. 2016;45:1006-1010. doi: 10.1093/ije/dyw103

Miguel A. Hernán, John Hsu & Brian Healy (2019) A Second Chance to Get Causal Inference Right: A Classification of Data Science Tasks, CHANCE, 32:1, 42-49, DOI:10.1080/09332480.2019.1579578.

Howe LD, Smith AD, Macdonald-Wallis C, Anderson EL, Galobardes B, Lawlor DA, Ben-Shlomo Y, Hardy R, Cooper R, Tilling K, Fraser A. Relationship between mediation analysis and the structured life course approach. Int J Epidemiol. 2016 Aug;45(4):1280-1294. DOI: 10.1093/ije/dyw254

Mishra GD, Chiesa F, Goodman A, De Stavola B, Koupil I. Socio-economic position over the life course and all-cause, and circulatory diseases mortality at age 50-87 years: results from a Swedish birth cohort. Eur J Epidemiol 2013;28(2),139-47.
Number of students 8 - 25
Selection of students Eligible doctoral students will be prioritized according to 1) the relevance of the course syllabus for the applicant’s doctoral project (according to written information), 2) date for registration as a doctoral student (priority given to earlier registration date). To be considered, submit a completed application form. Give all information requested, including a short description of current research training and motivation for attending, as well as an account of previous courses taken.
More information
Additional course leader Course leader is Ilona Koupil, Professor of Health Equity Studies/Public Health Medicine, CHESS, Stockholm University/Karolinska Institutet. Participating teachers will be Bianca De Stavola, Professor of Medical Statistics, University College London, UK and Gita Mishra, Professor of Life Course Epidemiology, University of Queensland, Australia.
Latest course evaluation Course evaluation report
Course responsible Anita Berglund
Institutet för miljömedicin

Anita.Berglund@ki.se
Contact person Johanna Bergman
Institutet för miljömedicin

johanna.bergman@ki.se

Nobels väg 13

17177
Stockholm