1: Debbie A. Lawlor & Gita D. Mishra: Why family matters - an introduction Section 1: What can family-based studies tell us about life course epidemiology? 2: Debbie A. Lawlor, Sam Leary & George Davey Smith: Theoretical underpinning for the use of intergenerational studies in life course epidemiology 3: Kate W. Strully & Gita D. Mishra: Theoretical underpinning for the use of sibling studies in life course epidemiology 4: Ruth J. F. Loos, Charlotte L. Ridgway & Ken K. Ong: Theoretical underpinning for the use of twin studies in life course epidemiology 5: Hazel M. Inskip: Discussant chapter: summary of the theoretical approaches to family-based studies in life course epidemiology Section 2: The practicalities of undertaking family-based studies 6: Anne-Marie Nybo Andersen, Mia Madsen & Debbie A. Lawlor: Theoretical underpinning for the use of intergenerational studies in life birth cohorts: a resource for life course studies 7: G. David Batty, Cesar G. Victora & Debbie A. Lawlor: Family-based life course studies in low- and middle-income countries 8: Susannah Tomkins: Using available family members as proxies to provide information on other family members who are difficult to reach 9: Rebecca Hardy & Diana Kuh: Discussant chapter: the practicalities of undertaking family-based studies Section 3: How to undertake statistical analyses of family-based studies 10: Dorothea Nitsch & Gita D. Mishra: Statistical considerations in intergenerational studies 11: Samuli Ripatti: Random effects models for sibling and twin-based studies in life course epidemiology 12: Amanda Sacker: Discussant chapter: statistical considerations in family-based life course studies Section 4: Use of family-based studies in life course epidemiology 13: Debbie A. Lawlor & David A. Leon: Family-based studies applied to the influence of early life factors on cardiovascular disease 14: Stephani L. Hatch & Gita D. Mishra: How family-based studies have added to the understanding of life course epidemiology of mental health 15: Susan M. B. Morton & Janet Rich Edwards: How family-based studies have added to understanding the life course epidemiology of reproductive health 16: John Lynch & Seungmi Yang: Discussant chapter: using family-based designs in life course epidemiology 17: Gita Mishra & Debbie Lawlor: The future of family-based studies in life course epidemiology: challenges and opportunities
Professor Deborah A. Lawlor completed medical training (University of Bristol) in 1986. She has an MPH (with distinction) from the University of Leeds, an MSc in Medical Statistics from the London School of Hygiene and Tropical Medicine and a PhD (MRC Training Fellowship, University of Bristol) in Epidemiology. She is the scientific director of the Avon Longitudinal Study of Parents and Children mother's study and a co-director of the British Women's Heart and Health Study. She has contributed to understanding the life course and genetic epidemiology of insulin resistance, diabetes, cardiovascular disease and women's reproductive health, and has developed methods for improving causal inference in observational epidemiology by using family-based studies and genetic variants as instrumental variables for making causal inferences about modifiable non-genetic risk factors. She is the Deputy Director of the MRC Centre for Causal Analyses in Translational Epidemiology. Dr Gita D. Mishra has an MSc and a PhD in Statistics from the University of Auckland, New Zealand and was awarded Chartered Statistician status by the Royal Statistical Society in 2004. She is a senior research scientist at MRC Unit for Lifelong Health and Ageing, University College London and an adjunct Associate Professor at the School of Population Health, University of Queensland, Australia. She has extensive research experience in the fields of statistical methodology for longitudinal studies, life course epidemiology, and women's health. Her work on intergenerational mobility has revealed some of the links between the timing of changes in social class and their effects on later dietary patterns and the way that such influences differ for men and women. Her research on missing data techniques has led to the development of a practical methodology for the selection of variables to be included in a multiple imputation model both in the context of cross-sectional and life course data.
"This book makes a valuable contribution to the field of life course epidemiology...it offers solid background and practical tools for researchers and should be included in life course epidemiology libraries."--Doody's