George B. Ploubidis is Professor of Population Health and Statistics at University College London (UCL) and currently holds the posts of Director of Research and Chief Statistician at the UCL Centre for Longitudinal Studies. Prior to joining UCL he held posts at the London School of Hygiene and Tropical Medicine and the University of Cambridge. He is a multidisciplinary Quantitative Social Scientist with a primary interest in socio-economic and demographic determinants of population health and the mechanisms that link these over the life course.   Bianca DeStavola joined UCL GOS Institute of Child Health after 23 years at the London School of Hygiene and Tropical Medicine where she was Professor of Biostatistics in the Department of Medical Statistics and  co-Director of the Centre for Statistical Methodology. Bianca’s main research activities involve the understanding, development and implementation of statistical methods for long-term longitudinal studies, with specific applications to life-course epidemiology.  As these often involve causal enquiries, in particular related to understanding pathways towards disease development, mediation analysis is her main interest.    Emily Grundy is Professor of Population Science and Director of the Institute of Social and Economic Research (ISER) at the University of Essex. Previous appointments have been at the London School of Economics, University of Cambridge, London School of Hygiene & Tropical Medicine and King’s College, London. Emily is a demographer by training and most of her work has focussed on ageing. Her main research interests are families, households and kin and social networks in later life, especially in relationship to health, associations between family life courses and health and well-being at older ages, and trends and differentials in later life health, disability and mortality.   Rhian Daniel is a statistician with aparticular focus on methods for learning about cause-effect relationships from observational data. She is especially interested in situations, such as when attempting to learn about the joint effects of sequential exposures in the presence of time-dependent confounding, or when attempting to disentangle path-specific causal effects, where standard regression methods are known to be valid only under highly unrealistic assumptions, but where alternative, so-called "causal inference", methods rely on weaker assumptions and hence can deliver substantially more reliable inferences with respect to the question of scientific interest.   Sanna Read is an  Assistant Professorial Research Fellow at the Personal Social Services Research Unit, London School of Economics and Political Science. Her current research interests are long-term health effects of fertility history, social contacts and socioeconomic factors in middle and older age. She is also interested in social inequalities and school engagement, school burnout and mental health among young people.   Benedetta Pongiglione holds a PhD in Epidemiology and Population Health from the London School of Hygiene and Tropical Medicine, University of London. She previously obtained a degree in Economic and Social Science from Bocconi University and completed the European Doctoral School of Demography program.  She is currently involved on research on cost and outcome analysis of healthcare technologies and development of scientific models to investigate medical practice variations to foster the use of economic evaluation in policymaking. Benedetta’s research interests include socio-structural inequalities in health, and understanding their causes and consequences.  Lenka Benova is a quantitative population health scientist with training in management, economics, Middle East studies and demography.  From 2014 to 2018, she served as a co-investigator on the Maternal healthcare markets Evaluation Team (MET) at the London School of Hygiene & Tropical Medicine, where I led the SAGE (Secondary data Analysis for Generating new Evidence) team.  Lenka a keen interest in health-seeking behaviour, maternal health research, and evaluation in low- and middle-income countries. Within these areas, Lenka is interested in innovative methods to capture decisions and steps in health-seeking,  validity of self-reported health-seeking indicators, and coverage of care contact and content.