COMPASS seminars 2014

Social network analysis and public health: Unravelling selection, influence and environment in adolescent substance use networks.

James Greenwell, PhD candidate (Population Health)
27 November 2014

The aim of this research was to gain insights into adolescent tobacco and alcohol use through social network models. Preliminary network analysis for adolescent smoking indicates that social selection processes play a stronger role than influence processes corrected for one another as well as environmental factors. The opposite was found to be the case for adolescent drinking. A contagion model also suggests that network actors were susceptible to the contagion (having a negative perception of substance use) based on exposure, gender and popularity attributes.

Identifying causal pathways in longitudinal analysis using structural equation modelling

Professor Marjo-Riitta Jarvelin, Chair in Lifecourse Epidemiology, Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London.
3 March 2014

Over the last few years there has been increasing interest in conceptualizing disease aetiology within a life-course framework. Within epidemiology this reflects the challenging theoretical framework. We can defined a life course approach to chronic disease epidemiology as the study of long-term effects on chronic disease risk of physical and social exposures during gestation, childhood, adolescence, young adulthood and later adult life. It includes studies of the biological, behavioural and psychosocial pathways that operate across an individual's life course, as well as across generations, to influence the development of chronic diseases.

Conventionally, chronic disease cohort studies recruit subjects in mid-life and follow them up for future disease end-points. The risk of developing disease is then related to baseline exposures or changes in exposure measures ascertained at further follow-ups. Even when baseline measures include early life exposures, such as birthweight and childhood socioeconomic position, these would usually be entered into a multivariable model without much attention to the temporal relationship between variables. The collection of exposure data across the life course is not synonymous with a life course model of disease causation.

Professor Marjo-Riitta Jarvelin

The presentation will summarise the following issues:

  • Principles and importance of lifecourse epidemiology
  • Conceptual models in lifecourse epidemiology, introduction into model building with reference to “conventional” multivariate model building
  • Analytical strategy, modelling and interpretation of life-course data using structural equation modelling  (SEM)

Professor Jarvelin is Chair in Public Health and Lifecourse Epidemiology at Imperial College London with additional part-time professorships at the National Institute of Health and Welfare and at the University of Oulu, in Finland.  Professor Jarvelin has been running large-scale population based studies for over 25 years, investigating the genetic and early life environmental origins of multi-factorial diseases/disorders in close collaboration with many internationally well-known institutions, groups and networks. She is a director of the widely acknowledged Northern Finland Birth Cohort (NFBC) Research Program, which includes around 20,000 subjects, born in 1966 and 1986.  In 2006 she received an award of excellence in genetic epidemiology at Imperial College London and in 2012 she was honoured in Finland with the title Epidemiologist of the Year.