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This chapter outlines the concepts of life course epidemiology as applied to coronary heart disease (CHD), discusses evidence with regard to early life factors and CHD, and considers the recently debated issue as to whether there is any need to continue searching for additional CHD risk factors above the well-established adulthood factors. It examines how well CHD trends fit with life course approaches and concludes by reviewing some of the remaining important issues in CHD epidemiology from a life course perspective.

Reproductive health covers a broad category of health and disease conditions, according to the Cairo Statement. This chapter focuses on subfecundity fertility, fetal death, malformations, pregnancy complications, sexual health, and diseases that may have their origin in fetal life, but which will not surface to clinical detection before decades of birth.

Family characteristics and interactions can directly affect one's health and wellbeing across the life course. In addition to the importance of recruiting and collecting data on family members, including parents, grand-parents, and siblings, for understanding fully the determinants of health and well-being across the life course, family studies (for example, intergenerational, sibling, twin) can help assess causality and underlying mechanisms in life course epidemiology. In this introductory chapter a brief background to the importance of family based studies to life course epidemiology is provided, followed-by a summary of the structure of the book and its overall aims.

This introductory chapter provides an overview of adult risk factors and why interest in the early life origins for adult chronic disease emerged. It then discusses the growth of life course epidemiology, different conceptual models, and methodological challenges encountered in life course epidemiology.

This chapter begins with an overview of the central themes of this book. It then introduces life course epidemiology, which is the study of the contribution of biological and social factors acting independently, interactively, and cumulatively during gestation, childhood, adolescence, and adult life on health outcomes in later life. The chapter concludes with a discussion of challenges and opportunities in the study of women's health.

Family-based studies can provide a more comprehensive view of life course epidemiology than studies that do not engage with family effects. They can establish intergenerational associations, help to understand the influence that one family member can have on the health and wellbeing of another family member and they can help to unravel the mechanisms behind the relationships of genetic, social, and environmental factors that impact on health at different life stages. This chapter summarizes the common threads across the previous chapters and highlights the key methodological challenges and opportunities of using family study designs in life course epidemiology. It discusses a number of points, including some that receive less attention in the preceding chapters, that are felt to be important for the future direction of research using family-based studies in life course epidemiology.

In life course epidemiology studies, the use of proxy (secondary) respondents may be an integral part of the study design or a consequence of not being able to reach or obtain information from the index subject. Based on the available evidence, the main factors that increase validity and reliability of proxy responses are broad categorization of, and focus on, directly observable characteristics and behaviours; questions requiring a binary response; recent characteristics and behaviours; face to face interviews; spouse/partner selected as proxy. Certain issues remain unaddressed by the available literature, including subject areas such as diet, the choice of proxy beyond spouse/partner, validation of responses when the index is unavailable and the effect of index characteristics on proxy responses. Finally, practical tips are presented in this chapter from a case study that successfully employed proxy respondents.

Society views population ageing as a challenge at best, and as a social problem at worst, despite increased life expectancy being a notable human achievement. Population health trends show an inconsistent picture with wide variation between and within countries; thus research evidence that clarifies the state of knowledge and guides interventions to improve healthy ageing is of growing importance. This chapter reviews how healthy ageing is conceptualized, defined, and measured, making the case for a focus on optimizing physical and cognitive capability and wellbeing at the individual level, and the functioning of body systems, organs, and cells. It argues that social and biological factors across life affect the chance of healthy ageing, presenting an integrated life course model of ageing that highlights the importance of physiological compensation and social and behavioural adaptation. Being able to detect early markers of change offers opportunities for timely interventions to optimize function and wellbeing.

Siblings can have a great deal in common (e.g., parents, genes, early life home env1ironments, etc.), but they are also distinct individuals with unique personalities and physical traits. This chapter discusses how researchers can use similarities and differences across siblings to investigate questions of life course epidemiology. First, it discusses how sibling fixed effects models may help deal with residual confounding from unobserved family-level factors. Second, it discusses how behavioural genetics approaches can help unravel genetic heritability from environmental determinants of health. Finally, it explains genetic linkage studies in which researchers use siblings' DNA information to learn more about the effects of chromosomal regions and genes. When considering each of these strategies, the chapter reviews the relevant literature and discusses the strengths and weaknesses of the particular methods.

Reproductive events throughout a woman's life course tend to be both a product of the cumulative exposures a woman has been subject to before that event, as well as a marker for her likely future health. While genetic contributions influence the fertility, development, growth, and reproduction of the next generation, all of these critical events in life are subject to external, environmental influences. This is true for individual women and within families of individuals. Perhaps given the shared genes and environments within and across generations in a family it is therefore not surprising that family studies consistently demonstrate a higher degree of consistency in reproductive outcomes at all points in the life course for those who share a family connection, than for individuals who do not, and that the closer that connection (e.g., monozygotic twins) in general the greater the similarities.

Chapters 2 to 4 describe three specific approaches to family studies, namely, intergenerational, sibling, and twin studies. All can be used to assist in distinguishing between genetic and environmental influences mainly within the classical nature-nurture paradigm. This chapter summarizes the three approaches, describes links across the methods, and draws on other examples to highlight some of the areas discussed and to explore other issues, such as birth order effects. All three chapters use the example of influences on birth weight to exemplify the use of their specific study types, intergenerational, sibling or twin, but they also consider outcomes occurring later in the life course. As in all branches of epidemiology a variety of methods in different contexts is required for us to see consistent patterns emerge. Conflicting evidence points to our lack of understanding and for alternative hypotheses to be explored.

This chapter discusses issues concerned with the design and practicalities of setting up birth cohorts for life course epidemiology. The demand for a blueprint of the ideal birth cohort study is perhaps intuitive, but the chapter questions the extent to which standardization of data collection and study protocols across contemporary and planned birth cohorts is desirable or feasible. The chapter discusses different approaches, difficulties and strengths of these different approaches, the determination of scientific priorities, definition of the birth cohort (including which family members are key participants), data collection and samples size, as well as the ethical considerations specific to the establishment of a birth cohort. The advantages of a scientific focus on specific exposures in each birth cohort study, of documentation of birth cohort data, and of collaborative studies using data from several birth cohorts are emphasized.

This chapter summarizes the origins of some of the existing life course studies and the current potential for using these studies to address family-based life course questions. It also highlights important methodological and practical issues for the future conduct of such studies. It has to be considered carefully whether it is worth collecting more prior generation and/or offspring generation data in these established cohorts given the practical difficulties and costs associated with such an undertaking as detailed Chapters 6, 7, and 8. The chapter concludes that there is a growing need to build infrastructure across cohort studies to encourage and support collaborative research. It is also clear that there is a great need to value and support the lifelong volunteers and the researchers who initiate and run longitudinal studies in order to realise the full scientific potential of life course research.

This chapter briefly describes the growing impact of non-communicable disease in low- and middle-income countries (LMIC) which, together with existing infectious illnesses and a rising incidence of violence, represents a triple health burden. Birth cohort studies, and in particular those with family-based elements, clearly have a role in identifying risk factors for chronic disease. Existing studies from LMIC are described. The chapter advances a number of reasons for adding to the very sparse research base outside of industrialized nations, and attempts to provide solutions for some of the methodological complications that might accompany such endeavours.

This chapter reviews some of the key family-based studies that have identified links between various illnesses and behaviours in parents and siblings with psychiatric disorders in study members. It also describes how sibling and twin studies are beginning to produce results that quantify the relative contribution of genetic and environmental effects. The chapter concludes with recommendations from the perspective of life course epidemiology to move beyond the established associations and to increase our understanding of the underlying mechanisms involved in psychiatric disorders. Specifically, it describes the range of characteristics in terms of study design, and type and scope of data that should be incorporated in future large population based studies.

The three chapters in this section offer different but complementary conceptualizations of ‘family’. Morton and Rich Edwards used ‘family’ to document inter-generational concordance of reproductive outcomes, Hatch and Mishra documented how ‘family’ could be characterized as a risk exposure for later poor mental health, and Lawlor and Leon used ‘family’ as a means to control for unmeasured confounding by family characteristics to better understand causal mechanisms relating fetal growth to later disease. Lawlor and Leon's approach is similar to that used in studies examining the possible intrauterine origins of birth weight and cognitive ability and this chapter briefly explores that literature. Families surely matter for better understanding individual and population patterns of ill-health.

The classical twin design is used in genetic epidemiology to estimate the heritability of a trait or disease. Despite potential biases for certain traits at specific stages during the life course, the classical twin method remains a robust and useful tool in human genetics when interpreted with care. Twins have also been applied to study the fetal origins of adult disease hypothesis. Twins have unique genetic and prenatal characteristics, which can be modelled to disentangle the complex mechanisms that underlie the ‘fetal origins’ of later disease risks. However, these models have important caveats. This chapter explores how twin-specific characteristics allow a unique insight into the balance of genetic and environmental influences that underlie early-life associations with later disease risks. It also describes how the unique determinants of birth weight in twins necessitate caveats in the interpretation of twin studies in life course epidemiology.

There is good evidence that associations exist between fetal and other early life factors and subsequent risk of cardiovascular disease (CVD) that can be replicated in a range of settings. These associations provide the evidential basis for the developmental origin of CVD in humans, which posits that susceptibility to CVD in later life is importantly influenced by the nature of the in utero, infant, and childhood environment. However, much of this evidence is from cohort studies of unrelated individuals, and it has been argued that these associations may be explained by confounding by genetic variation or uncontrolled aspects of the environment. This chapter describes how family-based studies, including twin, sibling, and intergenerational studies demonstrate the potential of family-based studies in throwing light on the developmental origins of CVD.

Intergenerational data necessarily reflect the time and place that the different generations of participants were living in. This chapter aims first to introduce simple concepts to provide an understanding of the founding assumptions and principles, before moving on to more complex analytic methods. As the objectives of analyses may vary substantially across intergenerational studies, there is no easy guideline for analyses, except perhaps that some a priori clarity on the main associations of interest is crucial. Since parents and their offspring are genetically related, intergenerational studies are to some extent genetically informative even if no genotyping was performed. Much of the analyses are concerned with identifying or unravelling the relationship between outcomes and genetic and environmental factors. Ways of handling missing data as well as approaches to deal with non-paternity are also discussed. Illustrative examples are drawn from the two cohort studies.