Skip to main content Accessibility help
×
Hostname: page-component-586b7cd67f-tf8b9 Total loading time: 0 Render date: 2024-11-22T08:12:35.014Z Has data issue: false hasContentIssue false

Section 3 - Key Concepts for Biosocial Research

Published online by Cambridge University Press:  20 June 2024

Michelle Pentecost
Affiliation:
King's College London
Jaya Keaney
Affiliation:
University of Melbourne
Tessa Moll
Affiliation:
University of the Witwatersrand
Michael Penkler
Affiliation:
University of Applied Sciences, Wiener Neustadt

Summary

Type
Chapter
Information
The Handbook of DOHaD and Society
Past, Present, and Future Directions of Biosocial Collaboration
, pp. 131 - 184
Publisher: Cambridge University Press
Print publication year: 2024
Creative Commons
Creative Common License - CCCreative Common License - BY
This content is Open Access and distributed under the terms of the Creative Commons Attribution licence CC-BY 4.0 https://creativecommons.org/cclicenses/

Chapter 10 Lifecourse

Mark Tomlinson , Amelia van der Merwe , Marguerite Marlow , and Sarah Skeen
10.1 Introduction

Lifecourse theory was developed in the last 50 years, combining neurobiology, child psychology, developmental psychopathology, sociology, population sciences, and increasingly genetics [Reference Banati, Verma and Petersen1]. Up to the latter part of the twentieth century, the focus was largely on the treatment of infectious diseases, acute illness, and injury within single-cause, simple biomedical models [Reference Halfon, Larson, Lu, Tullis and Russ2]. This was followed by a growing awareness of the roles of social and behavioural influences on illness, and revised bio-psychosocial models were developed that focused on managing chronic diseases over time and shifting unhealthy lifestyle choices [Reference Halfon, Larson, Lu, Tullis and Russ2]. However, health and social services continued to largely function separately, and the integration of physical and psychological health programmes was limited [Reference Halfon, Larson, Lu, Tullis and Russ2].

Lifecourse models take into account the influences of multiple risk and protective factors, operating across health trajectories or pathways throughout the lifespan and across generations [Reference Halfon, Larson, Lu, Tullis and Russ2]. The principles of lifecourse theory include: human agency in the construction of lives, timing (the developmental consequences of life transitions or events, which depend on when they take place in an individual’s life), linked or interdependent lives (social and historical impacts are expressed through shared relationships), and human lives in historical time and place [Reference Elder3]. Developmental psychology contributed to the concepts of life stages and turning points, while sociology added the contributions of history, social conditions, and adaptation [Reference Banati, Verma and Petersen1]. Genetics has contributed numerous concepts such as differential susceptibility [Reference Morgan, Kumsta, Fearon, Moser, Skeen and Cooper4]. A proliferation of research conducted during the early twenty-first century, including a large number of longitudinal studies that monitored continuity and change across the lifecourse, has prompted new ways of thinking about developmental trajectories and entrenched the lifecourse perspective in developmental research [Reference Banati, Verma and Petersen1].

The lifecourse perspective overlaps with a number of theoretical traditions, including sociocultural perspectives that emphasise the social meaning of age and developmental stages, such as the socially defined, age-graded meanings associated with the biological facts of birth, puberty, or death, for example [Reference Elder, Shanahan and Lerner5]. The concept of the lifecourse can also be historically linked to particular social transitions and to the meanings associated with a specific cohort [Reference Elder, Shanahan and Lerner5]. Lifecourse theory incorporates some of the principles of interactionist thinking, particularly its emphasis on the interactions between the person and context, and the organisation and shifts in the organisation of social structures and pathways through the lifecourse [Reference Elder, Shanahan and Lerner5]. Lifecourse theory is also based on Bronfenbrenner’s concepts of the ecology of human development, including multi-level influences from the environment, extending from micro- to macro-level influences. The individual lifecourse furthermore shares conceptual premises with developmental science with its focus on developmental trajectories and the dynamic interactions between events and processes that occur across time frames in multiple contexts [Reference Elder, Shanahan and Lerner5].

Previously, studies focusing on continuity and change from childhood and adulthood tended to include only correlational and regression analyses of patterns between measures of outcomes at two time points, typically childhood and adulthood [Reference Elder, Shanahan and Lerner5]. There was very little exploration of what happened in between and what the mechanisms of change and continuity were. Furthermore, there was limited awareness of individuals as agents of change in their lives [Reference Elder, Shanahan and Lerner5]. The lifecourse focus brought this into sharp relief and replaced child-based, growth-oriented (ontogenic) explanations of development with theories that account for development and ageing over the lifecourse. This focus emphasised how human lives are organised over time, including patterns of continuity and change, which focus on the developmental effects of social change and transitions [Reference Elder, Shanahan and Lerner5]. In this chapter, we explore the issues of continuity and change across the lifecourse, developmental trajectories, and a lifecourse theory to investigate how exposures and experiences influence different individuals in different ways, with some more vulnerable or susceptible to risk than others, resulting in significant variability in developmental outcomes.

10.2 Lifecourse Approach to Health

Modern healthcare systems need to synthesise prevention, treatment, and health promotion and set in motion more integrated and networked strategies for designing and implementing multi-level interventions that move beyond the individual to include populations [Reference Halfon, Larson, Lu, Tullis and Russ2]. The lifecourse development perspective shifts our understanding from simple, linear, mechanistic, and reductionist models to models that acknowledge that the development of health is complex, interactive, holistic, and adaptive [Reference Halfon, Larson, Lu, Tullis and Russ2]. It also shifts our focus to inclusive explanations about the developmental origins of health, how stress influences current and future health, and the outcomes associated with dynamic interactions between individuals and their multiple environments across time [Reference Halfon, Forrest, Lerner, Faustman, Tullis, Son, Forrest, Halfon and Lerner6]. Lifecourse perspectives provide a conceptual bridge between constructs that have until recently been assumed to be opposites, such as nature and nurture, mind and body, individual and population, and short-term and long-term change [Reference Halfon, Larson, Lu, Tullis and Russ2].

The lifecourse perspective incorporates pathways, which are constructed by the choices and actions that form individual lifecourses, and their developmental implications and consequences, including potential resources and constraints [Reference Elder, Shanahan and Lerner5]. Rutter and colleagues argue that pathways involve dependent sequences, to include an exposure/experience at one point in the lifecourse, how it affects the likelihood of others occurring later in the lifecourse, and how this in turn influences health and developmental outcomes, including chains of risk [Reference Hertzman and Boyce7]. A number of concepts are relevant to pathways, such as latency, which refers to the association between an exposure or experience at one point in the lifecourse and the related developmental outcome years or decades later, despite the presence of intervening exposure or experience [Reference Hertzman and Boyce7]. Cumulative risk is another relevant concept that describes multiple exposures, either to a recurrent single factor or sequential exposures to different factors over the lifecourse, which combine to influence development [Reference Hertzman and Boyce7]. These factors relate reciprocally, so that children with multiple exposures (to, for example, low socio-economic status [SES], poor parenting style, and residential instability) are likely to have more difficult trajectories than those exposed to single-risk factors [Reference Hertzman and Boyce7]. These constructs tend to coexist in the real world. In fact, research conducted by Hertzman and colleagues in 2001 has demonstrated a strong relationship between latency, pathways, and cumulative factors in childhood and self-rated health at age 33 [Reference Hertzman and Boyce7]. The current extensive focus on adverse child experiences (ACEs, see also chapter Kenny and Müller) [Reference Hughes, Bellis, Hardcastle, Sethi, Butchart and Mikton8] is the next logical step building on the work of Sameroff [Reference Sameroff9] and Hertzman [Reference Hertzman and Boyce7].

Social interactions that are sustained by their consequences (cumulative) and behavioural styles that tend to evoke maintaining reactions from the environment (reciprocal) lead to behavioural continuities across the lifecourse [Reference Elder, Shanahan and Lerner5]. Thus, both cumulative continuity and reciprocal continuity result in the cumulation of experiences that maintain and further the same behavioural outcome [Reference Elder, Shanahan and Lerner5]. Conversely, transitional experiences disrupt continuity through individual agency, dispositions, situational constraints and opportunities, and previous experiences that accompany individuals to new situations [Reference Elder, Shanahan and Lerner5]. This can bring about a significant change in behavioural trajectories and constitute a turning point [Reference Elder, Shanahan and Lerner5].

10.3 Developmental Origins of Health and Disease (DOHaD)

Research focusing on the Developmental Origins of Health and Disease (DOHaD) began to emerge in the 1970s [Reference Barker10]. Subsequently, researchers began to integrate the new ‘fetal origins’, and later DOHaD, research outcomes, with results from lifecourse sociology and psychology to create newer lifecourse models of health and disease [Reference Halfon, Larson, Lu, Tullis and Russ2]. The theories on which these models draw, such as evolutionary life-history theory, propose that development during fetal life is designed to prepare the infant for a particular external environment, and so, when conditions in utero match the conditions in infancy, development occurs along pathways originating in utero [Reference Salsberry, Tanda, Anderson, Kamboj, Forrest, Halfon and Lerner11]. However, when a mismatch occurs between the intrauterine and postnatal environments, certain dimensions of development may be compromised, or disadvantaged; for example, when intrauterine undernutrition is followed by an oversupply of nutrients postnatally, it poses risks for metabolic health [Reference Salsberry, Tanda, Anderson, Kamboj, Forrest, Halfon and Lerner11].

The centrality of maternal and child healthcare in DOHaD focuses research and intervention on health trajectories that can improve child health outcomes, as well as health development across the lifespan, and possibly even into subsequent generations [Reference Halfon, Larson, Lu, Tullis and Russ2]. There is substantial research evidence for the notion that maternal physiology, body composition, diet, and lifestyle during pregnancy significantly influence the health of the infant throughout their life, including the presence of cardiovascular and metabolic illnesses (such as hypertension, obesity, and type 2 diabetes), atopic conditions, cancer, and neurological impairment [Reference Fleming, Watkins, Velazquez, Mathers, Prentice and Stephenson12].

10.3.1 Biological Embedding and Differential Susceptibility

DOHaD research, framed by a lifecourse perspective, can account for how both ordinary and extraordinary experiences may ‘get under the skin’ by altering biological functions during developmental windows of opportunity, which can ultimately shift lifecourse trajectories and influence intergenerational health patterns [Reference Hertzman and Boyce7]. There are four systems that have the features of biological embedding: the HPA axis and the associated secretion of cortisol; the autonomic nervous system and its relation to epinephrine and norepinephrine; the development of the prefrontal cortex (including memory, attention, etc.); the primitive amygdala and locus coeruleus, and associated higher order cerebral connections, mediated by serotonin and other important hormones that are involved in systems of social affiliation [Reference Hertzman and Boyce7]. For example, poor nurturance, through the mediation of gene expression, may lead to a disturbed HPA axis, impaired capacity for complex learning, and high age-related declines in learning and memory capacity [Reference Hertzman and Boyce7].

Chronic stresses cause wear and tear on the HPA axis, which leads to dysregulation. This, in turn, may result in either hypo- or hypersecretion of cortisol with lifelong implications for health [Reference McEwen13, Reference McEwen14]. It is also clear that it isn’t either genes or the environment, or even genes and the environment, but gene-by-environment interactions that affect developmental trajectories [Reference Hertzman and Boyce7]. Epigenetic processes – for example, DNA methylation – have been identified as important processes through which early environmental signals are altered into conditionally adaptive shifts in key functions in metabolic, endocrine, and neuroregulatory pathways [Reference Hertzman and Boyce7, Reference de Kloet, Fitzsimons, Datson, Meijer and Vreugdenhil15]. These changes produce systematic developmental biases towards more adaptive functioning in terms of growth, metabolism, immune responsivity, developmental pace, and behaviour, although changes are not uniformly protective [Reference Hertzman and Boyce7]. Epigenetic changes, which occur in response to environmental cues, also play a role in the development of psychopathology and chronic medical conditions [Reference Hertzman and Boyce7].

Exposures and experiences affect individuals differently, and there is significant variability in developmental outcomes. Approximately 15 per cent of children may be more biologically reactive to their immediate social environment than other children [Reference Hertzman and Boyce7]. The effect of this on pathological outcomes is bivalent, as it can be protective or risk-enhancing depending on context [Reference Hertzman and Boyce7]. This has been described as differential susceptibility, which refers to the risk-enhancing or risk-abating character of the social contexts children inhabit [Reference Ellis, Boyce, Belsky, Bakermans-Kranenburg and van Ijzendoorn16]. Experimental studies have shown that the majority of children with low autonomic reactivity have only slightly more symptoms in families with high family conflict, while the high-reactivity children display a combination of significantly more symptoms in high-conflict families but markedly fewer symptoms than peers in families with low levels of conflict [Reference Ellis, Boyce, Belsky, Bakermans-Kranenburg and van Ijzendoorn16]. As a result the 15–20 per cent of study children with the highest levels of reactivity either demonstrated the worst outcomes or the best outcomes, as a function of the level of conflict in their families [Reference Boyce17]. It has been argued that more reactive children were more sensitive to both positive and negative social influences, while children who were low in reactivity were able to function adequately in a variety of contexts [Reference Boyce and Ellis18, Reference Boyce19]. Boyce and Ellis (2005) outline the following principles:

  1. A. Exposure to high-stress childhood environments enhances biological sensitivity to context and increases the child’s capacity to identify and respond to environmental threats;

  2. B. Exposure to particularly supportive childhood environments also enhances biological sensitivity to context and increases receptiveness to social supports and resources; and

  3. C. The majority of children are not exposed to environments that are either very stressful or very supportive, which reduces biological sensitivity to context and protects them against stressors [Reference Boyce and Ellis20].

Differential susceptibility is a useful concept to bear in mind when attempting to account for why environmental and intervention effects have been shown to be both variable and typically modest in published studies [Reference Ellis, Boyce, Belsky, Bakermans-Kranenburg and Van IJzendoorn21]. This is possibly a function of samples including both more and less susceptible individuals, which renders the average effect across all participants an invalid index of intervention effectiveness [Reference Ellis, Boyce, Belsky, Bakermans-Kranenburg and van Ijzendoorn16]. For example, distinguishing between short-allele and long-allele carriers was significant in determining the effectiveness of a maternal–infant attachment intervention. Specifically, for infants with one or two copies of the short allele of 5HTTLPR, the intervention improved attachment quality dramatically and significantly, while for those with only the long allele, the intervention produced no significant changes [Reference Morgan, Kumsta, Fearon, Moser, Skeen and Cooper4]. Differential susceptibility demonstrates in this way that averaging across all participants does not produce meaningful results [Reference Morgan, Kumsta, Fearon, Moser, Skeen and Cooper4]. Adverse social conditions such as socio-economic disadvantage increase the risk for various and multiple types of pathology by producing a generalised susceptibility [Reference Hertzman and Boyce7]. Typically, social adversities include feedback loops that result in one stressful or traumatic event following another, resulting in extremely negative social contexts [Reference Masten and Cicchetti22].

Although preconception and intrauterine experience have demonstrated marked effects on later health outcomes, there is a huge body of research that shows that childhood is a critical period for preventive and intervention efforts [Reference Ellis, Boyce, Belsky, Bakermans-Kranenburg and van Ijzendoorn16, Reference Patton, Olsson, Skirbekk, Saffery, Wlodek and Azzopardi23]. Neurobiological susceptibility is not categorical and should be viewed as occurring on a continuum [Reference Ellis, Boyce, Belsky, Bakermans-Kranenburg and van Ijzendoorn16]. It is also important to bear in mind that less susceptible individuals may benefit from more intense intervention efforts to obtain results similar to those who are more susceptible [Reference Ellis, Boyce, Belsky, Bakermans-Kranenburg and van Ijzendoorn16]. Furthermore, less susceptible individuals may not always stay that way, and individuals may be more or less susceptible in different stages across the lifespan [Reference Ellis, Boyce, Belsky, Bakermans-Kranenburg and van Ijzendoorn16]. For this reason, and because equity matters as much as intervention efficacy, certain groups should not be excluded from supportive services [Reference Ellis, Boyce, Belsky, Bakermans-Kranenburg and van Ijzendoorn16]. This is in addition to population-level interventions advocated by the lifecourse health perspective to prevent poor developmental outcomes, such as folic acid supplementation during pregnancy. One cross-cutting risk factor that results in a generalised susceptibility or vulnerability to risk which is broadly pathogenic and presents a host of challenges occurring at multiple ecological levels, is socio-economic disadvantage (SED).

10.3.2 A Cross-Cutting Theme: Socio-economic Disadvantage and Exposure to Adverse Childhood Events

Socio-economic disadvantage early in life has repeatedly and robustly been shown to influence health outcomes across the lifespan, even when considering later SES. Socio-economic disadvantage in infancy is associated with higher infant mortality and adverse birth outcomes [Reference Kim, Evans, Chen, Miller, Seeman, Halfon, Forrest, Lerner and Faustman24]. In both childhood and adolescence, SED has been linked to an increased risk for asthma, dental problems, and physical inactivity [Reference Kim, Evans, Chen, Miller, Seeman, Halfon, Forrest, Lerner and Faustman24]. In terms of psychological health outcomes, a range of researchers have shown that SED is linked to poor language, cognitive deficits, and behavioural difficulties during childhood and higher rates of substance abuse, disruptive behaviours, and depression in adolescents [Reference Kim, Evans, Chen, Miller, Seeman, Halfon, Forrest, Lerner and Faustman24].

Heightened stress levels appear to be the most important mediating mechanism underlying the influence of socio-economic disadvantage on health development [Reference Kim, Evans, Chen, Miller, Seeman, Halfon, Forrest, Lerner and Faustman24]. Childhood socio-economic disadvantage is linked to greater exposure to stressors, including harsh parenting, exposure to violence, separation from parents, lower school quality, negative peer relations, substandard housing, pollutants, noise, and crowding [Reference Kim, Evans, Chen, Miller, Seeman, Halfon, Forrest, Lerner and Faustman24]. Meijer and colleagues have also demonstrated that neighbourhood deprivation poses risks, including a lack of access to physical and cultural resources such as fresh fruits and vegetables, open space and other recreational amenities, libraries, and transportation, in addition to higher levels of exposure to violence and crime [Reference Meijer, Röhl, Bloomfield and Grittner25]. Those who have been exposed to SED are significantly more likely to encounter multiple, chronic, and severe stressors, which over time disables individuals’ capacity to cope [Reference Kim, Evans, Chen, Miller, Seeman, Halfon, Forrest, Lerner and Faustman24].

Exposure to ACEs such as those associated with socio-economic disadvantage is robustly associated with a range of childhood outcomes, including impaired physical growth and cognitive development, higher risks for childhood obesity, asthma, infections, non-febrile illnesses, disordered sleep, delayed menarche, and non-specific somatic complaints [Reference Lopez, Ruiz, Rovnaghi, Tam, Hiscox and Gotlib26]. Although these health conditions vary according to ACE characteristics, age of occurrence, and specific types of exposures, it is clear that the more ACEs the child is exposed to, the more likely she or he will have complex health problems, with multiple needs across developmental, physical, and mental health domains [Reference Lopez, Ruiz, Rovnaghi, Tam, Hiscox and Gotlib26]. Among ACEs, caregiver mental health is particularly important in terms of child health outcomes and is especially important for children aged under 5 years [Reference Lopez, Ruiz, Rovnaghi, Tam, Hiscox and Gotlib26]. Retrospective studies have shown that ACEs also increase the risk of chronic non-communicable diseases, substance abuse, sexual risk-taking behaviours, suicide, domestic violence, and impaired physical and mental health, which may lead to the transfer of ACEs to the next generation [Reference Lopez, Ruiz, Rovnaghi, Tam, Hiscox and Gotlib26].

Chronic exposure to cumulative risk factors linked to socio-economic disadvantage ‘gets under the skin’, by leading to dysfunction in the brain and associated physiological systems, and these dysfunctions impact the likelihood of physical and psychological illnesses [Reference Kim, Evans, Chen, Miller, Seeman, Halfon, Forrest, Lerner and Faustman24]. Neurobiological mechanisms of stress emphasise three areas of the brain that are involved in stress perception, appraisal, and regulation, namely, the amygdala, hippocampus, and medial prefrontal cortex [Reference Ulrich-Lai and Herman27]. Ulrich-Lai and Herman argue that the purpose of these areas of the brain is to regulate the physiological stress systems, especially the hypothalamus-pituitary-adrenal axis and autonomic nervous system [Reference Ulrich-Lai and Herman27]. Chronic exposure to adversity exceeds the neuroendocrine system’s ability to maintain homeostasis and, particularly during life stages associated with greater neuroplasticity (from pregnancy to early childhood), influences important components of brain development involved in cognition, self-regulation, and physical and mental health [Reference Lopez, Ruiz, Rovnaghi, Tam, Hiscox and Gotlib26]. As we have noted, chronic exposure to stressors can result in hyper- or hypo-responsivity of the HPA axis, which represents impaired adaptation and results in a higher likelihood of eventual exhaustion. Lopez and colleagues cite a multitude of studies that show that HPA-axis dysregulation has far-reaching effects on young children and may manifest as both internalising and externalising behaviours [Reference Lopez, Ruiz, Rovnaghi, Tam, Hiscox and Gotlib26].

The allostatic load model is important in this regard, as it suggests that exposure to chronic stress may result in wear and tear in primary stress regulatory systems (the hypothalamus-pituitary-adrenal axis and autonomic nervous system) and, consequently, in secondary physiological stress systems (metabolic processes, inflammatory and immune responses, and cardiovascular responses), which may lead to long-term damage and impairment [Reference Kim, Evans, Chen, Miller, Seeman, Halfon, Forrest, Lerner and Faustman24]. Dysregulation of these physiological systems, which is understood in terms of allostatic load, is a strong indicator of health development outcomes in adulthood, including cardiovascular disease, diabetes, as well as cognitive impairment and premature mortality [Reference Kim, Evans, Chen, Miller, Seeman, Halfon, Forrest, Lerner and Faustman24].

10.4 Limitations and Future Directions

Although there have been major strides in lifecourse health research, there continue to be significant gaps and limitations in the available research, particularly in terms of translation to policy and practice [Reference Halfon, Forrest, Lerner, Faustman, Tullis, Son, Forrest, Halfon and Lerner6, Reference Halfon, Forrest, Lerner, Halfon, Lerner and Faustman28]. Much of the research on the early biological origins of later health outcomes is based on animal studies, there are few longitudinal studies on preconception and pregnancy, and three-generational data are limited [Reference Halfon, Forrest, Lerner, Faustman, Tullis, Son, Forrest, Halfon and Lerner6]. In addition, most lifecourse and developmental research is based on studies that have not been designed for this specific purpose [Reference Halfon, Forrest, Lerner, Faustman, Tullis, Son, Forrest, Halfon and Lerner6, Reference Halfon, Forrest, Lerner, Halfon, Lerner and Faustman28]. Banati (2018) argues, in reference to the cross-sectional measurement of the Sustainable Development Goals, that longitudinal data add depth and complexity in understanding the lifecourse and provide answers to ‘why’, which is crucial to the nature and timing of interventions [Reference Banati, Verma and Petersen1]. A number of important lifecourse constructs – such as stress, weathering, and allostatic load – are not consistently defined or measured, and we lack knowledge of how these constructs could be best operationalised across different life stages, such as childhood and adolescence [Reference Halfon, Forrest, Halfon, Forrest, Lerner and Faustman29].

In spite of progress, much of the available research still uses reductionist statistical approaches that focus on isolating causal variables [Reference Halfon, Forrest, Lerner, Faustman, Tullis, Son, Forrest, Halfon and Lerner6, Reference Halfon, Forrest, Lerner, Halfon, Lerner and Faustman28]. More sophisticated statistical methods, such as longitudinal growth models to explore health trajectories, and multi-level modelling to better understand contextual contributors to health status, as well as decomposition methods to determine the influence of multiple risk and protective factors at different life stages on future health outcomes are necessary [Reference Halfon, Forrest, Lerner, Faustman, Tullis, Son, Forrest, Halfon and Lerner6, Reference Halfon, Forrest, Lerner, Halfon, Lerner and Faustman28]. New methods of analysis based on dynamic systems approaches are more suited to the complexity of the lifecourse health framework, but these have been limited in their application to understanding the roots of health disparities [Reference Halfon, Forrest, Lerner, Faustman, Tullis, Son, Forrest, Halfon and Lerner6, Reference Halfon, Forrest, Lerner, Halfon, Lerner and Faustman28]. Dynamic systems methods differ from correlational and regression approaches and include a number of computational approaches that can be applied to model dynamic and shifting interactions between individuals and their multiple environments, as well as complex processes such as feedback loops and non-linear relations [Reference Halfon, Forrest, Lerner, Faustman, Tullis, Son, Forrest, Halfon and Lerner6, Reference Halfon, Forrest, Lerner, Halfon, Lerner and Faustman28].

Despite the focus of lifecourse health research on structural and upstream policy and community-level factors influencing health status disparities, most research continues to examine downstream determinants, for example, health behaviours and healthcare [Reference Halfon, Forrest, Lerner, Faustman, Tullis, Son, Forrest, Halfon and Lerner6, Reference Halfon, Forrest, Lerner, Halfon, Lerner and Faustman28]. There is still limited knowledge of how complex processes resulting from dynamic interactions between biological, environmental, social, and behavioural factors over time produce disparities in population health [Reference Halfon, Forrest, Lerner, Faustman, Tullis, Son, Forrest, Halfon and Lerner6]. Many debates are unresolved, such as the relative importance of early vs. later exposures and the timing and plasticity of sensitive periods in development [Reference Halfon, Forrest, Lerner, Faustman, Tullis, Son, Forrest, Halfon and Lerner6, Reference Halfon, Forrest, Lerner, Halfon, Lerner and Faustman28].

The lifecourse health framework offers a foundation for more integrated, preventative, and developmentally prepared health systems that are developed around the central notion of advancing health and health-promoting environments across the lifespan and across generations [Reference Halfon, Forrest, Lerner, Faustman, Tullis, Son, Forrest, Halfon and Lerner6, Reference Halfon, Forrest, Lerner, Halfon, Lerner and Faustman28]. Cross-disciplinary knowledge can only be generated when there is an integration of lifecourse research, greater cooperation, and more collaboration and synthesis of disciplines [Reference Halfon, Forrest, Lerner, Faustman, Tullis, Son, Forrest, Halfon and Lerner6, Reference Halfon, Forrest, Lerner, Halfon, Lerner and Faustman28] to allow the development of a common set of principles that promote resilience under stress [Reference Ungar30]. This requires integrated, transdisciplinary funding opportunities and research agendas [Reference Suleiman and Dahl31].

A lifecourse perspective is relevant to all dimensions of health but is most relevant to health equity [Reference Braveman32]. A lifecourse perspective allows us to examine and understand how health disparities develop, are amplified or mitigated, as well as reproduced across generations, which may allow us to intervene more effectively [Reference Braveman32]. Specifically, this perspective helps us understand how social risks and opportunities create vulnerability or resilience at each life stage, and how they accumulate, or are reduced across lives and generations [Reference Braveman32]. The lifecourse perspective highlights stark disparities – children from relatively more wealthy contexts have benefitted the most, while there has been a limited impact on the poorest, who continue to need more resources and safety nets to mitigate the effects of the multiple vulnerabilities they face [Reference Banati, Verma and Petersen1].

In this chapter, we have drawn attention to how socio-economic disadvantage contributes to pathology across the lifecourse and beyond. The findings have far-reaching implications for policymakers and interventionists. In the spirit of equity, the lifecourse perspective and DOHaD theory suggest that early, population-level intervention (at critical or sensitive periods) may prevent the consequences of exposure to socio-economic disadvantage and all its associated risks. In addition, and perhaps in combination with population-level interventions, the concept of differential susceptibility suggests the importance of identifying risk indicators that render some more vulnerable than others and the urgency of conducting more research on the factors that influence responsivity to interventions. Identifying indicators that point to both additional risk or vulnerability and heightened responsivity to intervention will allow for the more efficient implementation of targeted services. This approach may be our best chance at addressing the probability of socio-economically linked disease outcomes and its repercussions, which are likely to be felt across multiple lifetimes.

Chapter 11 Syndemics

Edna N. Bosire , Michelle Pentecost , and Emily Mendenhall
11.1 Introduction

Recognising how early experiences frame and impact later health is a central focus of DOHaD. However, rarely in DOHaD studies are the synergistic characteristics of diseases throughout the lifecourse a central focus. Syndemic theory can enhance our understanding of health over the lifecourse by integrating a more synergistic understanding of early stressors and long-term adverse health, often caused by the interactions of health and social conditions. Syndemic theory posits that disease concentrations (where diseases cluster together) and disease interactions (what adverse effects result from the clustering) cause more health adversity due to their synergistic dynamics. Moreover, because the clusters and interactions of health conditions share upstream drivers, designing interventions to mitigate one condition may have larger-scale impacts on health and well-being. In this way, syndemic theory can contribute meaningfully to DOHaD studies because it considers how and why diseases occur, cluster, and interact across the lifecourse. Further, DOHaD thinking is inherent to syndemic theory, which recognises how chronic stress and inflammation over the lifecourse can play central roles in the interaction and exacerbation of certain infectious and/or non-infectious health conditions. Recognising how and why health conditions cluster together, and what factors from early life through adolescence may have a major impact on adult multi-morbidities, can advance both DOHaD and syndemic thinking.

In this chapter, we consider how syndemic thinking can advance DOHaD scholarship by critically engaging with the synergistic underlying conditions of early life that profoundly affect health and disease in later life. In what follows, we describe the history of the syndemics framework and provide a few examples of how the framework has been used in other studies. We discuss the synergies of syndemic and DOHaD theory. We draw on our work with the ‘Birth to Thirty’ birth cohort based at the Developmental Pathways for Health Research Unit (DPHRU) at the University of the Witwatersrand to provide some examples of how social, psychological, and biological factors cluster and drive health and disease over a lifetime, and demonstrate how the syndemic framework may benefit DOHaD research.

11.2 History of Syndemic Theory

The term syndemics was first proposed by Merrill Singer [Reference Singer1] to demonstrate how socio-economic, political, or environmental factors influenced the frequently co-occurring problems of substance abuse, violence, and HIV. Singer and Clair [Reference Singer and Clair2] defined syndemics as a set of intertwined and mutually enhancing epidemics involving disease interactions at the biological level that develop and are sustained in a community/population because of harmful social conditions and injurious social connections. Singer argued that the synergies of epidemics are crucial for understanding what diseases emerge, where, and why. Specifically, syndemics theory focuses on disease concentration (the where) and disease interactions (the how) and provides a framework for understanding what drives disease clusters and for designing interventions that might mitigate these effects. Others have described syndemics by thinking about interactions of ‘people, place, and time’ and as a ‘constellation of affliction’ [Reference Milstein3]. In many ways, the syndemics framework provides a clear way of thinking about disease: rarely does an individual or population experience a disease in isolation from other conditions – such as social, political, or historical contexts where people live.

Singer first proposed the SAVA Syndemic, showing how substance abuse, violence, and AIDS cannot be understood in isolation among inner-city residents of Hartford, Connecticut. Singer argued that the local HIV epidemic could not be dissociated from the local epidemic of substance abuse and that the pathways of transmission were inextricably linked and deepened by structural violence [Reference Singer1]. In this way, Singer emphasised that understanding local history and social context was fundamental for understanding the social life of an infectious disease. The SAVA syndemic framework is now widely used to develop interventions in the field of HIV/AIDS, while recognising that the interactions between and concentration of diseases have a history and may share an origin. This framing provides clear pathways for intervention, such as through integrating mental health and substance use interventions for the prevention of and living with HIV.

Three rules frame syndemic thinking [Reference Singer1, Reference Singer and Clair2], and these rules are crucial for defining what comprises a syndemic and what does not [Reference Tsai4]. First, two or more diseases concentrate within a population. In many cases, this relationship is well documented in the epidemiological literature, often cited as a comorbid or multi-morbid relationship. Second, disease interactions are measurable through bio-bio, bio-social, or bio-psychological pathways, which may include anything from well-documented interactions in biology (such as inflammation) to cultural dynamics (like stigma). Third, macro-scale forces precipitate disease clustering, framed by factors at the macro-level (such as structural violence) to meso-level (such as immigration or gender-based policy) and micro-level (such as interpersonal violence or chronic food insecurity). DOHaD takes a similarly integrative approach, recognising how early exposures to adversity and chronic stress, particularly in relation to nutrition, can profoundly shape disease risk later in life. It is this adversity and the diseases that emerge that often become syndemic; chronic stress and inflammation are closely linked to non-communicable diseases, and these conditions increase the risk for or compromise health when one confronts infections like HIV. It is these underlying conditions, and the weakening of immune function, that compromise one’s ability to fight off or live well when multiple serious conditions concentrate together within individuals and communities. The elevated risk of morbidity and mortality among people with such conditions, who are socially and economically marginalised, was exemplified by the recent COVID-19 crisis.

Another example is the syndemic of violence, racist immigration policy, diabetes, depression, and abuse (verbal, emotional, physical, or sexual) among Mexican immigrant women living in the Chicago metropolitan area, as described by Emily Mendenhall [Reference Mendenhall5]. In a mixed-methods study consisting of data collected through life history narrative interviews, biological specimens, and validated psychiatric instruments, Mendenhall describes how interpersonal violence and fear (bound to immigration policy) drove distress. These experiences linked stress and trauma from undocumented migration and navigating a racist immigration system to the deleterious effects of living with chronic illness (type 2 diabetes) amidst financial uncertainty. In this case, the adverse health effects of these larger forces, often obscured, could be observed in the epidemiological data demonstrating the close biological and psychological links between depression and type 2 diabetes [Reference Mendenhall5, Reference Lynch, Fernandez, Lighthouse, Mendenhall and Jacobs6]. A central focus of this work was to describe how study participants, despite seeking care for diabetes or being identified by the state as having diabetes (e.g. via Medicaid), could not become well without psychological healing and overcoming structural barriers like a lack of safety and food [Reference Mendenhall, Seligman, Fernandez and Jacobs7]. In this way, their diabetes was entangled in a feedback loop with traumatic memories, family stress, chronic financial uncertainty, and untreated depression that required nuanced care and support from the clinic, their community, and their families [Reference Mendenhall5].

These examples illustrate how syndemic co-factors build throughout a lifetime. DOHaD studies can emphasise at what time and in what ways interventions for one aspect of a syndemic may elevate overall health and well-being by lessening the interactions within and among syndemic problems [Reference Soepnel, McKinley and Klingberg8] – in this way, syndemic and DOHaD theories are complementary and synergistic.

11.3 How Syndemics Thinking and DOHaD Studies Are Inherently Synergistic

Understanding the social and biological histories of people is as fundamental to the syndemic framework as it is for DOHaD studies. Histories of disease have long engaged with a ‘disease biography’ approach – where diseases are viewed as biological entities, overlooking how diseases become interconnected and co-occur through social and political processes [Reference Proctor9, Reference Newfield10]. Thinking about the rise and decline of syndemics across time, as well as intergenerationally, provides an opportunity to recognise the fundamental role of contexts and driving forces that underlie how and why diseases interact within bodies and populations in a certain time and place. Studies central to driving DOHaD scholarship, such as of the 1944 Dutch Hunger Winter famines [Reference Roseboom, de Rooij and Painter11] and other famines such as in China and Nigeria [Reference Heijmans, Tobi and Stein12, Reference Song, Wang and Hu13], can provide situational evidence for why and how socio-political contexts may have affected biological risk for disease later in life or across generations. DOHaD studies emphasise how experiences of deprivation can provoke multiple and overlapping chronic conditions later in life, but rarely do they emphasise how these synergistic interactions occur and why. In many ways, DOHaD studies are already thinking syndemically, but making these links clearer, with a focus on interactions that perpetuate disease experiences, can provide clearer modes for intervention [Reference El Hajj, Schneider, Lehnen and Haaf14]. Using syndemic theory in DOHaD research could push forward an understanding of the connectedness of synergistic conditions through time and across space. This allows for syndemics to be studied historically and may allow researchers to fundamentally understand current syndemics and anticipate future ones.

Another attractive aspect of syndemics framework is its broad applicability to conditions or diseases that commonly cluster together such as malnutrition, obesity, and diabetes; HIV and TB; and HIV and non-communicable diseases such as diabetes and mental health [Reference Mendenhall15]. This provides a chance to develop interventions that respond to these diseases concurrently and in an integrative manner as opposed to dealing with individual diseases. Further, preventing syndemics requires not only prevention or control of each disease, respectively, but also understanding and controlling the forces that tie the diseases together. Insights gained from understanding syndemics (e.g. HIV syndemics research) can then be transferred and applied to other syndemics.

Syndemics often emphasise how deleterious social and political conditions such as poverty, food insecurity, inequalities, or political instabilities expose populations to disease clustering and interactions across the lifecourse [Reference Manderson and Ross16]. These factors further shape disease burden, from immune responses to healthcare access. The reverse is also true; disease burden and limited access to healthcare may influence social and economic conditions or processes [Reference Douglas-Vail17]. For DOHaD research, the syndemic framework may allow researchers to understand diseases holistically by examining how biological synergisms cluster and are worsened by social and structural forces. In other words, the syndemics framework may shed some light on inequalities in diseases and health and why some people suffer more than others within or outside the same geographical locations. For instance, although conditions like type 2 diabetes have been associated with old age [Reference Kalyani, Golden and Cefalu18], we know that insulin resistance can emerge and afflict younger people in part because economic pressures and intensified economic inequalities cause increasing stress, and viral and metabolic conditions are increasingly linked [Reference Mendenhall, Richter, Stein and Norris19Reference Yates-Doerr22]. This may best be exemplified in countries such as South Africa that have experienced extraordinary social and political changes [Reference Moodley, Christofides, Norris, Achia and Hofman23]. Metabolic disease appears to emerge at earlier ages in South Africa and makes people sicker faster compared to other developed countries [Reference Barnett, Mercer, Norbury, Watt, Wyke and Guthrie24, Reference Gluckman, Hanson and Mitchell25].

While DOHaD interventions often focus on child, maternal, and preconception health as influential for health across the lifecourse, a syndemic lens is useful to foreground the social or environmental challenges that interact in the early life period to influence well-being. For example, part of our collaborative work in South Africa under the Healthy Life Trajectory Initiative (HeLTI) has suggested that women suffer considerably because of long-term exposure to hardships, poverty, and intergenerational conflicts at home [Reference Cohen, Ware, Prioreschi, Draper and Bosire26]. Women may also frequently parent alone, in part due to parental separations and the early departure of the father in the context of women giving birth before marriage [Reference Cohen, Ware, Prioreschi, Draper and Bosire26]. Women with girl children, fearing for their daughters’ futures, sometimes exert undue pressure on their children to achieve educational goals and find secure employment before marriage or childrearing, but this can lead to significant intergenerational tensions. Daughters express stress, anger, anxiety, depression, and suicidal ideations [Reference Cohen, Ware, Prioreschi, Draper and Bosire26], which may affect the risk of early pregnancy [Reference Bouvette-Turcot, Unternaehrer and Gaudreau27]. Patriarchal culture plays a crucial role in girls’ experiences, where a hierarchy of power and privilege that typically favours men over women, and boys over girls, affects access to food, school, jobs, emotional support, and other crucial aspects of well-being. This then reinforces a systemic inequality that undermines the rights of women and girls and restricts the opportunity for women, men, and gender minorities to express their authentic selves.

This example illustrates the complex social dynamics that affect young people’s health, from ways of thinking about sexuality and power to financial security, emotional support, and conceptualisations of a healthy life and well-being. Social, psychological, and biological conditions emerge and interact in different ways throughout the lifecourse. By disentangling how conditions interact and perpetuate one other, clinical programmes can integrate mental and physical healthcare, and policymakers can also prioritise community-based interventions, given that, as we have found in Soweto, people engage in health-seeking far beyond the clinic and can improve their overall health and well-being by engaging in activities that may be religious or relational [Reference Bosire, Cele, Potelwa, Cho and Mendenhall28].

Moreover, syndemic theory can advance DOHaD studies as it highlights where, when, and how disease concentration or interaction is likely to occur across the lifecourse. For example, households that are exposed to violence (e.g. gender-based violence including intimate partner violence, child maltreatment, or early marriages) may have consequential impacts in later life. Studies have shown that children born in households that experience violence may have developmental delays first seen in infancy; anxiety and mood disorder symptoms and poor peer relationships first seen in childhood; substance use, abuse, or addiction or a diagnosis of substance use disorder often first seen in adolescence; and increased risk for personality and other psychiatric disorders and relationship problems during adulthood [Reference Norman, Byambaa, De, Butchart, Scott and Vos29]. Other research shows that among people exposed to major psychological stressors in childhood, there are elevated rates of morbidity and mortality from chronic diseases of ageing [Reference Miller, Chen and Parker30]. Understanding such factors can enable the development of timely interventions to ensure that disease clustering does not happen.

In sum, syndemic thinking in DOHaD studies can illuminate how macro-scale factors such as structural violence, meso-level factors such as health policies, and micro-level factors such as intimate partner violence influence disease clustering and interactions and produce poor health outcomes.

11.4 Conclusion

Syndemic theory facilitates an understanding of the cumulative effects of social and environmental influences, and how these interact with other variables such as demographic, biological, genetic, and epigenetic factors across the lifecourse. The syndemic framework underscores a need to focus on social inequality as a root cause of syndemic clustering and interactions and demonstrates that population-level disease prevention can only occur by addressing the large-scale social and structural forces that shape both individual and population health. In addition, addressing harmful or injurious forces at family, community, and population levels can help reduce disease clustering or interactions now and later in life. In this sense, the syndemic framework can highlight ‘hotspots’ where there is a high likelihood of disease clustering now or in the future and provide an opportunity to intervene before the clustering and interaction take place. Finally, the syndemic framework provides an avenue for interdisciplinary research – as it focuses on multi-layered factors that shape disease distribution at the population level. Thus, integrating syndemics in DOHaD studies may enhance cross-disciplinary research. The framework also enables researchers to address one of the greatest barriers to health improvements: the failure to examine linked phenomena. Syndemic theory allows researchers to move beyond understanding the proximate causes of diseases and draws attention to the processes that create clusters of disease and noxious living conditions for particular populations, affected by a particular condition. It is therefore imperative for DOHaD to think syndemically to understand disease patterns across different time periods.

Chapter 12 Embodiment

Ziyanda Majombozi and Mutsawashe Mutendi
12.1 Introduction

Embodiment is an established concept within the fields of medical anthropology and other social sciences. It has been used as a way of thinking and writing about the body and bodily experiences that challenge dualistic assumptions about the mind and the body. This chapter explores the various ways in which the concept of embodiment has been used in the social sciences and health sciences research with a particular focus on the ‘first 1000 days’ and the Developmental Origins of Health and Disease (DOHaD). By drawing on case studies and ethnographic data, this chapter illustrates how the concept of embodiment can be used as a heuristic or analytical tool to challenge the way we understand the body – particularly the ailing body, the sick body, and the birthing body. We draw on examples that illustrate how the concept of embodiment has the potential to contribute to DOHaD research. Using the concept of embodiment as a tool within DOHaD research allows us to show the ways in which challenging social environments and stressors have long-term effects on health and biology [Reference Clarkin1].

12.2 What Is Embodiment?

According to Musolino et al. [Reference Musolino, Warin and Gilchrist2], the conceptual framing of embodiment came into social science writing as a critique of the highly contested theory of Cartesian dualism, which continues to be the dominant approach to understanding and treating the body in other disciplines. René Descartes’s theory of dualism asserts that the mind and the body are separate entities that exist independently of one another and that could not exist in unity. Descartes believed that ‘…Mind was unextended, an immaterial but thinking substance and body was an extended, material but unthinking substance’ [Reference Mehta3]. This theory had implications for science and, of interest to this paper, the practice of medicine. In medicine, the body is often portrayed as a biological fact, an object, a collection of cells and tissue, a ‘… machine, void of mind or soul’ [Reference Goldberg4]. This can mean that the mind and its significance in one’s experiences of health and illness are not accounted for. However, since the 1970s, anthropologists and other social scientists have challenged Cartesian dualism and have suggested different ways to think about the body, one of which is the concept of embodiment.

While the concept of embodiment has been used differently within various disciplines, we will draw on three notions of embodiment that are of particular relevance to DOHaD: first, the political economy approach within critical medical anthropology [Reference Scheper‐Hughes and Lock5]; second, the phenomenological approach conceptualised by Csordas [Reference Csordas and Harwood6]; and finally, the biosocial approach, drawing on Nancy Krieger’s work [Reference Krieger7]. Thus, the first part of the chapter is a survey of how embodiment has been theorised and used within the social sciences. In the second half of the chapter, we argue that DOHaD should embrace social science concepts as biosocial collaboration compels cross-disciplinary legibility and a shared vocabulary. We provide a discussion of why embodiment (conceptualised in the three ways we present) is a useful theoretical tool for DOHaD science. In doing so, we illustrate why it is important to integrate concepts/tools from social sciences, in this case embodiment, to deepen our awareness and understanding of the kind of influence environmental experiences can have on the development of health and disease over the lifecourse. We suggest that employing the embodiment concept can make DOHaD research and interventions more socially just and socially sensitive.

12.3 Approaches to Embodiment

The political economy approach to embodiment is best described by Nancy Scheper-Hughes and Margaret Lock. In their seminal essay, The mindful body: A prolegomenon to future work in medical anthropology, Nancy Scheper-Hughes and Margaret Lock [Reference Scheper‐Hughes and Lock5] conceptualise the body as something that is ‘simultaneously a physical and symbolic artifact, as both natural and culturally produced, and as securely anchored in a particular historical moment’ [Reference Scheper‐Hughes and Lock5]. They propose the idea of three bodies. Firstly, the ‘individual body’ represents one’s personal experiences, perception, and consciousness of their body. Secondly, the ‘social body’ focuses on the messages that the body sends and how the body is perceived and analysed by others. Thirdly, the ‘political body’ focuses on the regulation, control, and surveillance of bodies. This way of thinking about the body challenges the view that the body is simply a biological fact. The idea of the three bodies not only challenges mind–body dualism but also opens up a new lens of analysis in which illness is not experienced solely in the mind or the body but is crucially shaped by social and political structures. This is best illustrated by their concluding words:

What we have tried to show in these pages is the interaction among the mind/body and the individual, social and body politic in the production and expression of health and illness. Sickness is not just an isolated event, nor an unfortunate brush with nature. It is a form of communication – the language of organs – through which nature, society and culture speak simultaneously. The individual body should be seen as the most immediate, proximate terrain where social truths and contradictions are played out, as well as a locus of personal and social resistance, creativity, and struggle [Reference Scheper‐Hughes and Lock5]

The phenomenological approach to embodiment conceptualised by Thomas Csordas has also been widely influential within anthropology and social sciences discourses. Csordas [Reference Csordas and Harwood6] proposed the idea of phenomenological embodiment to move away from discourses that frame the body as a passive subject. Instead, he advocates for a conceptual framework that captures human existence as relational, temporal, embodied, and situated [Reference Zigon and Throop8]. Csordas [Reference Csordas and Harwood6] sees the body as ‘a biological raw material’ that ‘inherits its culturality through the process of embodiment’. This approach has allowed scholars to illuminate how culture and history shape bodily experiences. Used in this way, the concept of embodiment provides us with useful tools for thinking about everyday taken-for-granted bodily practices, about how bodily knowledge is acquired, and about how, in turn, this acquisition accounts for the differences in how people hold and use their bodies (gestures or accents) [Reference Musolino, Warin and Gilchrist2, Reference Bourdieu and Nice9].

The biosocial approach to embodiment goes beyond ‘considering’ how culture and politics influence health and illness experiences to show the detrimental implications of not considering embodiment. A failure to consider embodiment can lead to deeply unjust experiences of health and illness as the social becomes biological. Scholars such as Nancy Krieger have described embodiment as ‘a concept referring to how we literally incorporate, biologically, the material and social world in which we live, from conception to death; a corollary is that no aspect of our biology can be understood absent knowledge of history and individual and societal ways of living’ [Reference Krieger7]. Embodiment for epidemiology grapples with the implications of how global and local social, political, and economic structures shape people’s lives and become embodied in individual sickness and suffering [Reference Gravlee10].

We now move onto three case studies that illustrate the usefulness of the above approaches to embodiment. It is important to note that we do not advocate for any one approach to embodiment; we see all the approaches we have surveyed here are equally useful. The case studies below show us an alternative to the DOHaD tendency to individualisation and blame that is often directed towards women for negative outcomes with regard to reproduction. For example, Manderson and Ross [Reference Manderson and Ross11] suggest that DOHaD research and the interventions born from it tend to over-emphasise the maternal role in keeping the fetus safe and healthy. As a result, there is a tendency to focus interventions on women with the assumption that a woman’s body is ‘an incubator of population health, both in the immediate present and, according to current understandings of epigenetics, for two generations (at least) into the future’ [Reference Manderson and Ross11]. This has the unintended consequence of leaving other bodies such as those of men underexamined and puts the responsibility of the health and well-being of future generations solely on women, leading to the surveillance of particular bodies in order to control population health [Reference Manderson and Ross11]. The following case studies provide insight into how the experience of pregnancy cannot be adequately grasped by focusing on the individual mother. Instead, they illustrate how an embodiment approach can better illuminate the environmental and structural conditions surrounding pregnancy.

12.4 Case Studies

Anthropologist Emily Yates-Doerr’s [Reference Yates-Doerr12] work in Guatemala effectively illustrates how health and illness are shaped by social and political structures. Yates-Doerr [Reference Yates-Doerr12] provides an insightful multi-layered analysis using embodiment to trace the relations and material conditions that shape the worlds of mothers and their infants. In 2006, the Central American Free Trade Agreement came into effect. This resulted in Guatemalan markets importing an influx of US market foods, which included unhealthy and highly processed foods that were not a staple commodity prior to the implementation of the international trade agreement. Furthermore, the liberalisation of the Guatemalan food economy meant it became more expensive for the country to locally produce staple commodities, thus resulting in the proliferation of supermarkets that could mass import food into the country. Yates-Doerr [Reference Yates-Doerr12] notes that the rising rates of diabetes, heart disease, hypertension, and other illnesses associated with dietary practice within the country are in part due to the transformation of the region’s food economy brought about by the international trade agreements [Reference Yates-Doerr12, Reference Groeneveld, Solomons and Doak13]. Like Yates-Doerr, many other scholars have noted that the introduction of the Western diet, especially the emergence of highly processed foods in particular countries, corresponds to the rising rates of cardiovascular diseases and hypertension [Reference Hall14]. Thus, in the case of Guatemalan women, the high rates of obesity and diabetes in infants cannot be solely blamed on a mother’s individual lifestyle choices. The political economy of Guatemala is embodied in the lives and bodies of women and their infants; in Rubin and Hines’ words [Reference Rubin and Hines15], political economy ‘enters the body’, transforming the bodies of women and their infants, and affects their health outcomes.

The second example we draw on is from Mutsawashe Mutendi’s [Reference Mutendi16] work on maternal health among South African platinum mineworkers. Mutendi [Reference Mutendi16] shows how platinum mining makes mineworkers vulnerable to various occupational health-related problems, particularly reproductive health-related problems. The exposure to toxic chemicals while mining underground can potentially be harmful to the health of pregnant women and the health of the fetus. Her work shows how women opt to evade mining policies that stipulate that when a female mineworker discovers that she is pregnant, she should report her pregnancy to human resources so that an alternative and safer job can be found for her. Under such policies, if the number of pregnant women exceeds the number of available alternative jobs on the surface, the remaining pregnant mineworkers are sent home by the mining company until they give birth. In such cases, women will only be compensated for four months of maternity leave, as stipulated by the Basic Conditions of Employment Act (BCEA) of 1997, Section 25 [17]. Hence, pregnant mineworkers in this context opt to conceal their pregnancies and continue working underground despite the reproductive dangers that this potentially poses to the mineworkers, their fetuses, and subsequent generations. Mutendi highlights the complex political and economic realities and multiple forms of vulnerability faced by female mineworkers during pregnancy. These include how pregnancy, mining policies, the fear of being economically redundant, motherhood, exposure to toxins, and the in utero experience shape one another.

Some of the groundbreaking research conducted on the biosocial approach builds on Krieger’s work on embodiment, to show how racial inequality can result in poor health outcomes for particular groups of people (see Meloni et al. in this volume). For instance, the work of neonatologists David and Collins [Reference David and Collins J18] illustrates how racial oppression can be embodied and influence the health outcomes of infants. In Disparities in infant mortality: what’s genetics got to do with it?, David and Collins explore the differences between infants of African American women and white women in the United States, with a particular focus on the disparities in low birth weight between the two racial groups. Their research shows that low birth weights of infants were not a result of genetic predisposition but rather the socio-economic and environmental influences that African-born women were exposed to, which changed their biology, putting them at a higher risk of birthing infants with low birth weight. Their research speaks to the ways in which structural racism is embodied: it enters the bodies of women of colour, and the stressors associated with racism lead to women having unfavourable maternal health outcomes and their infants also having bad outcomes such as low birth weight and premature birth. Thus, the social issue of racism manifests itself in biological ways. Although research that is framed within the biosocial approach of embodiment is largely Euro-American as is shown in the example above, there have been some recent strides in this topic within South Africa. Kim et al. [Reference Kim, Mohamed, Norris, Richter and Kuzawa19] look at the intergenerational mental health impacts of prenatal stress in South Africa, focusing on a longitudinal birth cohort in South Africa called Birth to Twenty Plus (Bt20++). Their research illustrates how the trauma caused by apartheid conditions, coupled with other societal ills such as poverty and inequality, can be inherited and embodied by children in utero and affect their mental health in the future. Kim et al.’s key findings are that trauma and stressors caused by apartheid conditions have had enduring biological effects that continue to influence socio-emotional behaviour and mental health across the lifecourse [Reference Kim, Mohamed, Norris, Richter and Kuzawa19].

12.5 Discussion

As the definitions and case studies that we have used in this chapter make clear, the conceptual framework of embodiment allows us to connect the subjective experiences of the body to broader social contexts and also shows us how the body is inscribed with history, politics, and culture. That is, individual bodily experiences are shaped by social, political, historical, and cultural forces [Reference Scheper‐Hughes and Lock5, Reference Foucault20]. Furthermore, the concept of embodiment has allowed social scientists and health scientists to incorporate more nuanced approaches to quantify stress or other social, cultural, and material circumstances that could influence one’s illness or sickness [Reference Kuzawa and Sweet21]. As Buklijas et al. mention in this volume, DOHaD research is based on the premise that conditions experienced in the womb, infancy, and childhood could potentially predict adult biological and health outcomes [Reference Kuzawa and Sweet21]. In the same vein, Krieger [Reference Krieger7] argues that the clues to the current changing health population patterns can be found in the dynamic social, material, and ecological contexts in which people are born into, develop, and interact within.

While the focus is on interventions that aim to modify the behaviour and lifestyle of pregnant women might be useful, there are much larger structural forces at work beyond the control of the mother. The case studies we have presented demonstrate that we cannot divorce the body from politics and cultural context. Thus, to understand health and disease, DOHaD research needs to go beyond looking at what is present in the body, or the personal decisions made by an individual. Considering these case studies, we would want to look beyond the pregnant women who choose to work underground or pregnant women who eat processed food. Instead we want to consider the amalgamation of socio-economic-political factors that influence the decision-making of pregnant women and, ultimately, their health and that of their unborn babies. Such a deepened awareness can bring about more socially aware representations of women in DOHaD research and more socially just DOHaD interventions. In the Kim et al. case, for example, the health outcomes of pregnant women and future generations must be understood in the context of the racial inequality and injustice that occurred during apartheid South Africa; these have biological implications for Black maternal bodies. This awareness of how racial inequality and injustice can be embodied demands DOHaD research and interventions that take seriously the health impacts of racial inequality. In bringing attention to broader contexts, an embodiment approach would also encourage DOHaD interventions to focus on other reproductive actors and caregivers beyond pregnant women, including men and adolescents, as well as attending to broader contexts.

Adopting an embodiment approach in DOHaD research is challenging but vital. Such an approach widens the scope and focus of intervention, takes racial discrimination, political issues, and structural violence into consideration, and investigates how those socio-economic-political issues may enter the body and cause disease. An embodiment approach to DOHaD research navigates questions such as: how do bodies experience pregnancy and childbirth? How do certain contexts produce particular kinds of experiences of pregnancy? How do the circumstances under which women are pregnant enter their bodies and cause disease or ill health? Under what circumstances are bodies learning how to be pregnant and how to then feed an infant? How do others relate to certain pregnant bodies? What kind of power relations play out in the pregnant body, and how does this affect the health outcomes of the mother and child? Our hope is that using embodiment as a tool will help DOHaD researchers heed Krieger’s call in her latest work, to use what we know about how injustice and inequalities shape people’s health to guide our actions and direct resources into ‘prevention, redress, accountability and change’ [Reference Krieger22].

12.6 Conclusion

This chapter has defined and illustrated embodiment as a crucial concept for theorising the body and illness in social and health sciences. These perspectives highlight that the body is relational, temporal, embodied, and situated. Using embodiment as a conceptual tool allows us to go beyond highlighting how structural inequality can literally be embodied and trigger sickness and move towards emphasising the transgenerational implications of health as a result of the previous generation/s embodying social ills. DOHaD science provides the scientific backing for the embodiment concept as it clearly shows that environmental factors impact health. This chapter calls for DOHaD research and interventions that not only acknowledge the environmental impact on health but also consider and include that wider environment and wider social structures in the interventions proposed. Embodiment is an insightful analytical tool that allows for conducting DOHaD research that can attend to social, political, cultural, and material processes and ultimately produce socially aware and socially just research and interventions. Embracing social science concepts such as embodiment also allows for shared vocabulary between DOHaD scientists and social scientists, which is vital for biosocial collaboration.

Chapter 13 Causal Crypticity

Sarah S. Richardson

Causal crypticity is an epistemic norm in the field of maternal–fetal effects science. That is, fetal origins researchers assert causal hypotheses about links between small permutations in the gestational environment and later life outcomes. The causes and effects of these permutations are typically not directly observed but are inferred from variations in developmental outcomes or health risks that occur later in life, often along a decades-long chain of other exposures and experiences. To advance these hypotheses requires field-wide epistemic norms that accept, in most cases, an ineliminable crypticity – meaning both subtlety and elusiveness – in the causes and effects under study.

This feature of Developmental Origins of Health and Disease (DOHaD) science is not the perception of hard-nosed sceptics. Many DOHaD researchers are frank about its causal dilemmas [Reference Heijmans and Mill1Reference Richmond, Relton and Davey Smith3]. DOHaD scientists have faced fierce criticisms of their theories and findings by scientists who doubt the plausibility of their causal claims [Reference Paneth and Susser4Reference Wilcox7], and scientists in the varied research streams that comprise fetal origins/maternal effects science have been openly debating the question of causality for decades. The search for causal mechanisms propelled the entry of epigenetic methodologies into the field and contributed to the pioneering of new inference causal testing models such as Mendelian randomisation to attempt to examine the plausibility and strength of hypothesised causal relations [Reference Birney, Smith and Greally8Reference Richmond, Timpson, Felix, Palmer, Gaillard and McMahon12].

The crypticity of causality in DOHaD is no standard-issue causality conundrum. As I argued in The Maternal Imprint: The Contested Science of Maternal-Foetal Effects (2021), from the field’s inception, causal crypticity has been deeply carved into the historical development of the field and will likely continue to be a persistent feature of any research in maternal–fetal effects science, regardless of the amount of data acquired or the sophistication of computational methods employed [Reference Richardson13]. Nods to the context-specificity and complexity of causal attributions in DOHaD science do not sufficiently acknowledge the persistent, intransigent crypticity of causality in maternal–fetal effects science, nor do they capture the social dimension of its function as an epistemic style in DOHaD discourse.

High tolerance for causal crypticity can be defined as a field-defining epistemic norm that accepts a persistent state of indeterminacy about the empirical reality, strength, and magnitude of hypothesised causal phenomena that are the object of study. Causal crypticity distinguishes approaches to causal reasoning within DOHaD from certain ideals of scientific inference prising replicable experiments, intervenability demonstrating causal invariability across conditions, and identification of a physiological mechanism [Reference Woodward14]. But this does not imply that causal crypticity is particularly epistemically suspect compared to other causality-seeking knowledge projects. Causal crypticity is not a term intended to pinion the scientific merit or rigour of DOHaD science but to characterise its epistemic norms to better understand the field’s theories, its evidential base, and the judgements that undergird its inferences. My claim is descriptive, not evaluative: causal crypticity operates as an epistemic norm in DOHaD science.

In this chapter, I explicate and develop the concept of causal crypticity, first introduced in Richardson (2021). Causal crypticity can be understood in three ways: as an epistemic norm; as a boundary-delimiting signature of field culture or epistemic style; and as a promissory mode. Contending with causal crypticity as a norm-shaping feature of the knowledge landscape of maternal–fetal effects science, I conclude, demands reflection on strategies for ethical and accountable practices of claimsmaking in DOHaD science, in a world where its findings are received as carrying social implications in arenas ranging from reproductive autonomy to efforts to redress the health implications of racism and intergenerational trauma.

13.1 Crypticity

The term ‘cryptic’ has multiple connotations, which I embrace. Something that is cryptic may be real but difficult to decode or retrieve. Equally, something that is cryptic can be unclear, and whether it is real or not can be impossible to discern. Phenomena that are cryptic are elusive, shape-shifting, and impermanent in form. DOHaD science connects cryptic effects with cryptic causes. Cryptic effects are findings of health outcomes in exposed compared to unexposed populations that are small in effect size and that present inconsistently across different study cohorts; moreover, such crypticity in reported outcomes is persistent and unresolved despite expanding volumes of data. Cryptic effects are typified by DOHaD studies reporting small absolute changes in risk factors for common diseases among populations of healthy, average births exposed to a hypothesised intrauterine variable.

The field’s tolerance for causal crypticity is in clear evidence, for instance, in the Dutch famine studies, a touchstone in DOHaD research. The Dutch famine studies are often presented as definitively demonstrating a causal link between nutrition in the womb and obesity and related metabolic conditions, including high blood pressure, diabetes and insulin resistance, and cardiovascular disease. These metabolic outcomes are based on measures taken from a small sample of 422 survivors, in their fifties, who were gestationally exposed to the famine (and matched siblings) during the four months of the acute famine of 1944–1945 in the Netherlands [Reference Lumey, Stein, Kahn, van der Pal-de Bruin, Blauw and Zybert15]. As researchers will readily agree when queried, the findings from these studies are much less generalisable, and much more contingent and uncertain, than portrayed in the standard textbook narrative. Famine survivors have been found to have, on average, modestly elevated blood pressure compared to non-survivors [Reference Stein, Zybert, van der Pal-de and Lumey16]. Women gestated during the Dutch famine have, on average, an extra few centimetres around the waist, at age 59, than their non-exposed sisters [Reference Rundle, Stein, Kahn, van der Pal–de Bruin, Zybert and Lumey17]. However, the effect sizes in such findings are small. They are also unstable, appearing and disappearing across different age cohorts and genders/sexes within the study populations. Critical reviews demonstrate that the Dutch famine studies have shown a few, if any, stable metabolic outcomes of significant effect size specifically correlated with in utero exposure to famine [Reference Lumey, Stein and Susser18].

Other statements frequently reiterated in the literature, such as that early exposure to famine doubles the risk of obesity, are, upon examination, not supported by current evidence but are statistical relics of dated metrics of what constitutes abnormally overweight body composition from the 1970s [Reference Ravelli, Stein and Susser19]. Furthermore, researchers have struggled to identify biological mechanisms that could account for the purported specific causal effects of famine exposure during gestation. A much-celebrated early finding of epigenetic changes in the insulin-like growth factor 2 (IGF2) gene among famine survivors has never been replicated [Reference Heijmans, Tobi, Stein, Putter, Blauw and Susser20, Reference Tobi, Slieker, Luijk, Dekkers, Stein and Xu21]. Subsequent studies attempting to find epigenetic mediators of triglyceride levels among survivors have not withstood causality inference testing [Reference Richmond, Relton and Davey Smith3]. Yet even as effects are causally cryptic – effect sizes remain small, findings are contested and conflicting, and mechanisms are elusive – the Dutch famine studies are presented in the literature as a foundation and model for future work [Reference Roseboom22], and scientific publications, textbooks, and popular media frequently feature studies of health outcomes among ageing members of the cohort of infants gestated during the Dutch famine as a gold-standard example of the promise of developmental origins science [Reference Zimmer23].

Causal crypticity characterises the explanations for cryptic effects because such cryptic effects are unstable and variable, such that they make non-ideal observations for substantiating a link to a specific cause. In the case of maternal intrauterine effects, in which the direct effects of perturbations during gestation are already challenging to observe, measure, or quantify, causal crypticity is particularly amplified. This is because, due to the many environmental and genetic confounders of early human development, in nearly every case the cryptic maternal effect is an endpoint of complex, multiply confounded causal chains, frequently occurring at a significant temporal distance from the hypothesised initial exposure, which itself is sometimes a confounded, variably defined, difficult-to-measure ‘cryptic cause’ such as ‘stress’ or ‘metabolic dysregulation’.

Such crypticity is apparent even within maternal–fetal programming science that is often presented as most foundational, most settled, and as presenting the most extreme exposures, the largest effects, and the most incontrovertible findings, as in the Dutch Hunger Winter studies. The field’s high tolerance for causally cryptic findings as constituting knowledge helps us understand how such findings, which at best offer support for what may be model-theoretically plausible or physiologically possible, become concretised as a textbook, settled science, and as known or proven facts within the field of DOHaD.

13.2 Causal Crypticity as an Epistemic Style and Promissory Mode

Tolerance for causal crypticity, as a feature of the DOHaD field’s culture, norms, standards, or epistemic style, is apparent in the forms of evidence accepted within the DOHaD field as contributions to scientific knowledge and reflected in its shared assumptions about the questions and objects of interest. For example, the quality of crypticity is arguably constitutive of what makes something a developmental or maternal effect rather than, for instance, a birth defect or anomaly. Causal crypticity is, furthermore, integral to the central questions and problems that the DOHaD field addresses and to how it goes about addressing them. As Gemma Sharp, Debbie Lawler, and I have argued, the question of whether maternal–fetal programming effects are real is in many senses not a question for researchers in the DOHaD field. For DOHaD researchers, it is indisputable that programmable maternal–fetal effects are real [Reference Sharp, Lawlor and Richardson24]; the question is only whether we can see and prove them, given that the biology involved must be very complex and that the pragmatics of studying maternal–fetal effects in human populations is challenging.

Scientific fields are social formations. Sociologists and historians of science posit that scientific fields function most efficiently to advance empirical understanding of phenomena when there is a shared culture of sorts and when the field agrees on its core questions. As a part of this boundary-defining work, fields typically close down or defer certain questions as well as certain epistemological considerations [Reference Bourdieu25Reference Knorr-Cetina28]. Causal crypticity can be tolerated, one might hypothesise, when it serves other important functions for the field as a social formation. Following scholars of scientific hype [Reference Fortun29, Reference Caulfield30], one speculation is that causal crypticity may function to keep fetal origins science at the centre of controversy, with findings persistently described as emergent, yet to be validated, still being tested, and even essentially contested. In part because of this, causal crypticity could work cathectically to draw intrigue and to construct a continually self-replicating arc of future speculation and possibility. In this way, causal crypticity may function as an electric current that both makes the field of maternal–fetal effects a flashpoint and draws curious researchers to it.

In this sense, causal crypticity can be understood as a promissory discourse that conveys causal-ish claims that generate excitement and interest [Reference Fortun29]. Thus, although the field is now more than three decades old, its claims are frequently presented as offering a new, emergent, and provocative resource for science. It is commonplace to read in publications, to hear at an academic conference on DOHaD, or to find in a media presentation of DOHaD research a statement such as: ‘In recent years, research from the field of the Developmental Origins of Health and Disease (DOHaD) has suggested that events before birth can have life-long consequences’ [Reference Jacob and Hanson31]. Such broad statements suggesting a powerful causal relation between intrauterine environment and later life health are, technically speaking, perfectly consistent with a collection of unreplicated findings that intrauterine exposure X is associated with small effects on offspring outcome Y in study population Z, yet it also implies stronger and more widely validated causal effects actionable for public health and in the clinic than present evidence can support.

Specifically, causal crypticity may function socially and discursively to generate excitement and interest in the scientific field by pointing towards a future in which knowledge of such cryptic patterns could be harnessed to optimise health outcomes [Reference Heeney32]. Notably, cryptic patterns of perturbations linked to outcomes do not promise control or prediction for any particular individual, but at best speak to patterns and trends and to risk categories and potential problems at the level of population groups [Reference Penkler33]. These patterns and risk categories generate uncertainty and require concern and ongoing monitoring.

In a world rife with crises, risk, and uncertainty, the potential for cryptic sources of fetal developmental perturbation requiring ongoing tracking is everywhere. We thus see speculation about the relevance of developmental origins theories to nearly every area of social anxiety and uncertainty, including natural disasters and political or economic crises, from the 9/11 attacks [Reference Berkowitz, Wolff, Janevic, Holzman, Yehuda and Landrigan34Reference Ohlsson and Shah36] to climate change [Reference Wesselink and Wellenius37Reference Derfel39], to most recently, the COVID-19 pandemic [Reference Forestieri, Pintus, Marcialis, Pintus and Fanos40Reference Schoenmakers, Verweij, Beijers, Bijma, Been and Steegers-Theunissen42]. Writing in 2021, Tessa Roseboom and colleagues warned in the Journal of the Developmental Origins of Health and Disease that ‘the legacy of this pandemic looms large for unborn babies … These individuals, being unseen and unheard, are likely to go unprotected’. The implications of experiencing the pandemic while in the womb, these authors assert, will affect an entire generation and ‘all of our future societies’: ‘Today’s (unborn) children will drive growth and development in our future societies. […] We must now act to prevent further scarring of the life chances of a generation’ [Reference Roseboom, Ozanne, Godfrey, Isasi, Itoh and Simmons41]. The potential for harm to the ‘unborn’ is pervasive, as in Figure 13.1, which conceptualises the mother’s work, daily hassle, and even the condition of pregnancy itself, as health-imperilling stressors transmuted to the fetus through the mother [Reference Schoenmakers, Verweij, Beijers, Bijma, Been and Steegers-Theunissen42].

Figure 13.1 ‘Overview of potential maternal prenatal stressors during the current COVID-19 pandemic as part of the early life course medicine’.

DOHaD science on maternal–fetal effects promises to inform public policy to improve future outcomes, but causal crypticity entails that DOHaD research is not, by and large, likely to produce interventions driven by the reversal of biochemical mechanisms at the moment or site of programming [Reference Penkler33]. In a field of inquiry characterised by the epistemic style and promissory mode of causal crypticity, interventions, while hoped-for, are ultimately less the order of the day than demonstrating the possibility or plausibility of harm. In the case of DOHaD, this harm is conceptualised as a limitation on future potential. That is, DOHaD findings of cryptic effects deliver evidence of limitations or lesions in the potential for life flourishing, from early mortality to educational achievement. Powerful ableist, Western norms and pressures to optimise birth outcomes, complemented by globalist, development economics frameworks for measuring human capital in the metrics of health and at the level of the body, help sustain this promissory mode in maternal–fetal effects science [Reference Valdez43Reference Reiches46]. The range of possible future adverse outcomes is so wide that the full implications of the developmental harm can never be fully grasped, only proxied by limited quantitative physiological measures such as adiposity or blood pressure. Moreover, it is argued that these harms are set so early in development that compensating for or redressing the harms will be challenging. DOHaD researchers frequently suggest that early developmental harms might only be redressed in future generations by removing or waiting out the scourge of trauma, poverty, or metabolic deprivation.

13.3 Causal Crypticity in the Context of Big Data and Postgenomic Science

While DOHaD science has long operated with a high tolerance for causal crypticity, the epistemic norm of causal crypticity, as I have characterised it here, increasingly might be said to characterise the knowledge claims and knowledge practices endemic to data-rich, twenty-first-century postgenomic biomedical life sciences, particularly those endeavours operating in complex biosocial causal spaces. Indeed, as commentators have pointed out [Reference Richardson and Stevens47], in many areas of postgenomic biomedicine, causal claims are not expected to result from investigations. It is expected that the strength of findings will vary depending on contextual factors and that findings will not replicate across all datasets. Even as researchers strive to validate causal connections, a tolerance for a certain permissiveness with implying the likely causality of observed correlations is increasingly integrated into the norms and culture of postgenomic biomedicine.

There is a broader social context for these shifts in knowledge paradigms in the postgenomic life sciences. The epistemic style of causal crypticity is primed to flourish in a knowledge culture defined by massive information. The epistemology of massive information is defined by constructs such as ‘search’, trending ideas, chatter, pattern recognition, the notion of ‘data mining’, network, and systems-like ideas about the connectivity of all things, total information, emergence, and surveillance [Reference Stevens, Richardson and Stevens48]. This epistemology contrasts sharply with ‘magic bullet’ or ‘master molecule’ approaches to knowledge that are oriented towards control, intervention, and cure [Reference Keller49]. In a knowledge culture embracing causal crypticity, grievance or evidence of harm is not expected to surface as a gaping wound – acute, localisable, and repairable – but as a population-level signal – subtle, elusive, and with harms and benefits of uncertain interpretation.

Similarly in postgenomic science, signals are not expected to be single-gene lesions [Reference Boyle, Li and Pritchard50], but polygenic scores or risk calculi that must be carefully contextualised against a backdrop of population genetic structure, developmental context, and social conditions. These sciences, underpinned by genome-wide association studies, multidimensional forms of social data, and AI-informed analytics, are made up of statistically sophisticated evidence of correlations between biological and social outcomes. While these correlations themselves do not support causal inference, causal crypticity enables a presumption of the likelihood of causality. Findings are narrated within a larger frame that implies a strong assumption that such correlations, summed in their entirety, are evidence supporting an intuition of causality. This shift in epistemic norms is collapsing the twentieth-century oppositional distinction between the complexity-affirming ‘dissident’ anti-genetic determinist sciences and the reductionist and determinist gene-centric biological sciences [Reference Richardson, Richardson and Stevens51].

In sum, causal crypticity is an epistemic norm that aligns with the speculative and promissory mode of today’s transnational, big data-crunching science, which proposes to mine previously undetected patterns across populations, unlocking a key to who we are and where we are going in our uncertain era of demographic transformation in lifespans and family size, technological change, and environmental crisis. Like these fields, DOHaD pleads for a deferral of judgement and for more space for free investigation, by implicitly suggesting that cryptic patterns long postulated or hypothesised, and for which current evidence is trace-like at best, will soon be detectable as meaningful sources of human variation in health – once we have the data and the proper data mining tools to retrieve those patterns. In this way, within the postgenomic life sciences, DOHaD science offers an index case of the leading edge of a broadening trend of embracing the bold pursuit of cryptic causes.

13.4 Ethical and Accountable Claimsmaking in DOHaD Science under Conditions of Causal Crypticity

In The Maternal Imprint, I traced the history of attempts to empirically confirm speculations about the long-term or permanent effects of experiences or exposures in the womb [Reference Richardson13]. The book followed three intertwining threads within this history: First, discourses about maternal agency and responsibility for reproductive outcomes. Second, progressive, anti-genetic determinist constructs of the biosocial body position the maternal–fetal relation as a particularly heightened space for the inscription of social and environmental context on the body. Third persistent and unresolved questions about the limits of empirical science in confirming the causal effects of intrauterine perturbations on disease distribution in human populations.

This third, seemingly epistemic dimension, I argued, cannot be fully pulled apart from the other two. This is because bold causal claims in the absence of consistent and convincing evidence of predictive, intervenable effects can only persist if there is a powerful social and scientific imaginary carrying them forward. The churning, resilient, charged space of maternal responsibility for optimising reproductive outcomes and the subversive, hopeful, riveting, intuitive, and narratively compelling picture of bodies embedded in environments and social systems are two such imaginaries.

The subtle effect sizes and complex confounding typical of causal claims in DOHaD science are not simply an everyday causal challenge but rather function as both a defining epistemic norm of the field and a future-oriented social discourse. The concept of ‘causal crypticity’ directs attention to the links between causal crypticity as an epistemic norm, the production of risk categories, and the promissory hype cycle of science.

Fields such as DOHaD are defining the epistemic terrain of postgenomic inquiry, particularly at the interface of the genetic and social sciences [Reference Richardson, Richardson and Stevens51]. For some DOHaD scientists, the concept of causal crypticity as I have motivated it here may at first provoke defensiveness. Most scientists understand themselves instead to be seeking – even if not always finding – causal relations grounded only on rigorous empirical inference. However, embracing this feature of DOHaD research could make DOHaD a laboratory for grappling with causal crypticity in a reflective and forthcoming manner. This surely includes strengthening frameworks for making causal inferences in the face of causal crypticity, as some already are [Reference Lawlor, Relton, Sattar and Nelson2, Reference Gage, Munafo and Davey52]. But it also includes practices such as rigorously placing risk claims emerging from such sciences in context, in particular through collaboration with social scientists exploring the socio-structural dimensions of health and lifecourse development [Reference Müller, Hanson, Hanson, Penkler, Samaras and Chiapperino53], accurately characterising the degree of uncertainty in scientific findings in this area [Reference Richardson, Daniels, Gillman, Golden, Kukla and Kuzawa54], and educating the consumers of such science in the features of reasoning in a field defined by causal crypticity.

Chapter 14 Intergenerational Trauma

Jaya Keaney , Henrietta Byrne , Megan Warin , and Emma Kowal
14.1 Introduction

The term intergenerational trauma describes how trauma experienced in one generation can lead to trauma in the lives of descendants. For scholars and practitioners of Developmental Origins of Health and Disease (DOHaD), intergenerational trauma is an important aspect of human experience that can shape physiological development and influence individual, family, and community health across generations. In a DOHaD model, parental and community experiences of trauma can be transmitted in utero and in early life, having a cumulative physiological effect such that historical experiences are embodied in the present. In this chapter, we provide a conceptual overview of ‘intergenerational trauma’ in the interdisciplinary field of DOHaD research. The concept has been variously defined in relation to other disciplines and implicitly or explicitly drawn on other concepts such as historical trauma, transgenerational trauma, and post-traumatic stress disorder (PTSD). Intergenerational trauma is of interest to many disciplines and frameworks in part because it lends itself to ‘biosocial’ understandings of violence and discriminatory social contexts as physiologically embodied. Yet, intergenerational trauma also presents challenges for scientific study due to the difficulties inherent in stabilising it as a scientific object. As a group of social theorists working across anthropology, gender studies, and science and technology studies (STS), we attend in this chapter to both the operationalisation of intergenerational trauma in DOHaD research (including the increasing importance of epigenetic mechanisms) and the particularities of how intergenerational trauma is enacted as a supposedly stable entity in science. Given the growing public interest in intergenerational trauma, and its increasing clinical uptake for the care of marginalised communities, this chapter also considers a range of important questions related to policy translation, biopolitics, and social justice.

14.2 What Is Intergenerational Trauma?

Broadly speaking, intergenerational trauma can be understood as ‘emotional and psychological wounding that is transmitted across generations’ [Reference Cerdeña, Rivera and Spak1]. It is entangled with the allied concepts of historical trauma and transgenerational trauma. While often used synonymously with intergenerational trauma, we distinguish historical trauma here through its connection to large-scale historical violence ‘such as enslavement, colonization, and genocide’ [Reference Cerdeña, Rivera and Spak1, Reference Bombay, Matheson and Anisman2]. While this understanding of historical trauma falls within the remit of intergenerational trauma, the latter can also encompass traumatising experiences that do not register in large-scale histories of global violence but occur on more personal and micro-scales, such as interpersonal violence. ‘Transgenerational trauma’ is another term that is often used synonymously with intergenerational trauma (e.g. [Reference Cerdeña, Rivera and Spak1, Reference Atkinson3]); however, in the DOHaD field, the term ‘transgenerational’ has a specific meaning that pertains to epigenetic mechanisms of transmission to two or more subsequent generations (as discussed in more detail later in this chapter). As we define it here, intergenerational trauma does not imply a particular kind of violence or a particular biological mechanism of transmission.

A capacious concept, intergenerational trauma has captured the attention of theorists, clinicians, and writers across innumerable fields. These range from Indigenous studies [Reference Bombay, Matheson and Anisman2, Reference Redvers, Yellow Bird, Quinn, Yunkaporta and Arabena4], psychology and psychiatry [Reference Scorza, Duarte, Hipwell, Posner, Ortin, Canino and Monk5Reference Van Der Kolk7], social work [Reference Atkinson3], and public health, to literature [Reference Caruth8], queer studies [Reference Cvetkovich9], and memory studies [Reference Hirsch10]. Scholars across these fields differently approach intergenerational trauma as a useful concept for thinking through human relatedness, collective identity formation, and the channels through which histories and legacies are embodied, suturing us across time and space. Theories of how intergenerational trauma is inherited vary widely across these different approaches – from attention to narratives and material culture shared in families [Reference Atkinson3], to artistic texts and collective remembrance practices through which new generations are enculturated [Reference Hirsch10], to somatic mechanisms of implicit or bodily memory held by individuals [Reference Atkinson3, Reference Van Der Kolk7].

While social environments were key to early formulations of DOHaD [Reference Warin, Moore, Zivkovic and Davies11], the increasing molecularisation of the environment has narrowed the focus to biological mechanisms of transmission. This includes two important junctures. The first is the transmission to a fetus of a pregnant person’s real-time experience of a traumatic event/environment or its after-effects. Developmental programming in utero and in early life in response to trauma can foster a greater propensity for stress and mental health challenges [Reference Yehuda and Lehrner12] and can contribute to low birth weight, preterm birth, chronic disease, and immune and metabolic dysfunction later in life [Reference Singh, Morrison and Hoy13Reference Lewis, Austin and Galbally15]. The second juncture is the effects of patterns of parental care behaviours, including breastfeeding, nutrition, and emotional responsiveness [Reference Conching and Thayer16]. Here, the destructive effects of trauma in caregivers’ own lives, often compounded by material disadvantage and ongoing discrimination, can lead to the re-creation of traumatising contexts for children. Manifesting as developmental challenges, sustained distress, and detachment from caregivers, communities, and culture, this is often referred to as the ‘cycle of trauma’. Here, trauma is both cause and effect. Past traumas suffered by parents, communities, or ancestors may be an origin of an individual’s present-day health challenges and may also manifest as personal experiences or psychological symptoms of trauma.

The scholarly genealogy of intergenerational trauma and its potential mechanisms is often traced to empirical studies of the effects of the Holocaust on children of survivors [Reference Conching and Thayer16, Reference Kellerman17]. These studies found that the children of Holocaust survivors experienced mental health challenges characteristic of those who experienced trauma directly [Reference Cerdeña, Rivera and Spak1, p. 2]. The application of the concept has since broadened considerably, including to explore the impacts of colonisation on First Nations communities [Reference Bombay, Matheson and Anisman2, Reference Redvers, Yellow Bird, Quinn, Yunkaporta and Arabena4]; the effects of forced displacement and armed conflict on survivors and refugee populations [Reference Clarkin18Reference Perroud, Rutembesa and Paoloni-Giacobino20]; intergenerational harms among African American communities wrought by trans-Atlantic slavery and enduring racism [Reference Kuzawa and Sweet21, Reference Grossi22]; and the embodied legacies of systemic gender-based violence [Reference Uwizeye, Thayer, DeVon, McCreary, McDade, Mukamana, Park, Patil and Rutherford19, Reference Karpin23].

While ‘trauma’ is deployed as a stable biomedical entity in DOHaD-informed studies, defining and measuring trauma scientifically is a complex endeavour always entangled with social worlds. Far from a ‘timeless unity’ [Reference Leys24, p. 3], trauma is made measurable within diagnostic categories and measurement tools that stabilise it as a pathological disease entity. Chief among these are the diagnosis of PTSD, which was added to the Diagnostic and Statistical Manual (DSM) in the 1980s and has been critical to studies and therapeutic interventions for trauma; and measurement tools such as the Adverse Childhood Experiences scale [Reference Leitch25, Reference Müller and Kenney26], which aims to quantify experiences of trauma through scales tabulating challenging events and living conditions.

Such tools conceptualise and enact trauma differently from one-another and in context-dependent ways [Reference Dubois and Guaspare27]. For example, the association between context, symptom, and relationship is differently assembled in individual study designs. As Judy Atkinson and co-authors [Reference Atkinson, Nelson, Atkinson, Purdie, Dudgeon and Walker28, p. 289] have written, trauma is variously conceived as an ‘event, environment, or reaction’. Trauma is often implicitly conceptualised as an event itself, for example, a collective historical trauma or a set of adverse childhood experiences. Yet in other contexts, it is defined as the distress exhibited in response to an event or situation [Reference Cerdeña, Rivera and Spak1, p. 16]. These slippages have a significant impact on understanding what trauma is, who is affected, and the scales of intervention. Defining trauma with reference to a particular historical event such as colonisation, for example, risks homogenising members of a group by assuming they all experienced the event as similarly traumatising [Reference Gone and Kirmayer6]. As Andrew Kim [Reference Kim29] writes, studies of stress and trauma can also often result in researchers assessing whether a given event is traumatic according to their own worldview rather than through deep engagement with the worldview and reference points of the participants. Furthermore, studies that focus conceptualisations of trauma on an event can make it challenging to attend to heterogenous groups for whom traumas are compounding or not easily delineated as discrete events. As Cerdeña et al. [Reference Cerdeña, Rivera and Spak1, p. 2] note, one of the reasons that Latinx communities are underrepresented in the literature on intergenerational trauma may be due to their significant heterogeneity and the multiple overlapping sources of trauma, including diverse forms of colonisation, political oppression within Latin America, dangerous passages of international migration, and systemic racism.

14.2.1 DOHaD Research, Epigenetics, and Transgenerational Trauma

As discussed above, much of the early scholarly literature surrounding DOHaD has focused on historical cohorts that have experienced trauma from war and nutritional deprivation (particularly famine – for example, the Biafran (1967–70) or Chinese famine (1959–61)). The oft-cited Dutch Winter famine from the Second World War is perhaps the best known: a period of severe malnutrition forced on Dutch families by Nazi occupiers in the western part of the Netherlands in 1944–45. Pregnancy data, birth records (including placental weights and birth weights), and daily food ration cards were collected from women across differing trimesters in order to map any developmental ‘insults’ from ‘hostile environments’. The perinatal and gestational data collected (including data from fathers) have been tracked across the lifecourse of the children as they progressed into adult life. Thirty thousand people died as a result of malnutrition and extreme cold, and the children conceived and born during the famine were found to have disproportionally higher rates of adult disease risk, such as diabetes, coronary heart disease, and cancer (with different outcomes dependent on respective trimesters in utero during the famine) [Reference Painter, Osmond, Gluckman, Hanson, Phillips and Roseboom30, Reference Heijmans, Tobi, Stein, Putter, Blauw, Susser, Eline Slagboom and Lumey31]. Researchers claim the Dutch Winter famine cohort as an example of intergenerational transmission of adverse exposures that is linked to epigenetic changes.

In the DOHaD context, much attention has been given to epigenetics in relation to transgenerational trauma. Broadly defined, epigenetics is the study of how various external factors, including food, stress, and toxins, alter genetic expression. While interest in the ‘science’ of trauma was strongly rooted in neurology and neurobiology in the 1980s [Reference Leys24], epigenetics has recently emerged as a popular concept when it comes to attempts to codify trauma in a scientific or biological frame. Epigenetic studies look at how the epigenome is impacted by various factors that modify DNA and the proteins it binds to, therefore affecting how genes are expressed. The most widely studied mechanism through which this occurs is DNA methylation. DNA methylation is often described through the metaphor of a volume knob on a stereo, operating by ‘turning down (or even off) certain genes in some cases and turning up other genes in other cases’ [Reference Sullivan32, p. 200–1]. Epigenetics offers a biological pathway for the transmission of impacts of traumatic events from one generation to the next, and also potentially between more than two generations (known as ‘transgenerational transmission’). Transgenerational epigenetic transmission is established in some non-human models, such as the nematode C. Elegans [Reference Woodhouse and Ashe33, Reference Frolows and Ashe34], drosophila [Reference Xing, Shi, Le, Lee, Silver-Morse and Li35, Reference Ciabrelli36], honeybees [Reference Remnant, Ashe, Young, Buchmann, Beekman, Allsopp, Suter, Drewell and Oldroyd37], and rodents [Reference Horsthemke38Reference Gapp, Jawaid, Sarkies, Bohacek, Pelczar, Prados, Farinelli, Miska and Mansuy40]. Though well understood in animal models, transgenerational epigenetic transmission in humans is heavily debated. Despite this contestation though, the theory itself – that multiple generations of families and communities hold the epigenetic ‘marks’ of previous social environments and experiences – is widely discussed in relation to trauma both within and beyond the field of DOHaD.

14.3 Critiques of Trauma: Biopolitics and Pathologisation

Given the rising public and scholarly interest in epigenetic mechanisms of trauma transmission and intergenerational trauma more broadly, it is important to consider some questions related to policy translation, biopolitics, and social justice. While trauma-informed approaches have become increasingly important in DOHaD science and therapeutic interventions globally, researchers must also pay attention to cultural specificity and the limitations of cross-cultural translation. Trauma manifests in bodies in ways that are deeply localised, framed by situated histories, cultures, and modes of embodiment [Reference Kim29]. While instruments to measure stress and trauma are often adapted for local contexts, this is not always effective, with localised idioms of pain and distress rendered illegible [Reference Cerdeña, Rivera and Spak1, Reference Mendenhall and Kim41, p. 18]. Non-Western theories of intergenerational trauma and the holistic epistemologies of embodiment that they derive from, such as ‘blood memory’ among Native American communities [42] or ‘communal wounds’ [Reference Gilbert43] and ‘trauma trails’ [Reference Atkinson3] among Indigenous Australians, may likewise be rendered illegible by biomedical definitions and measures that place emphasis on the individualised scale of the patient. Differing cultural concepts of time, reproduction, and kinship that do not rely on colonial imperatives of linear temporalities also need to be considered. Compounding these challenges is the difficulty of measuring trauma when it is ongoing, without a clear beginning or end. For many communities that face intergenerational trauma, violent forces such as colonisation, racism, and socio-economic inequality are not only formations connected to historical events but are ongoing structures of devastation with deeply felt daily impacts.

One of the most pressing interrelated questions around invoking intergenerational trauma in DOHaD is how to effectively translate this into policy in such a way that avoids pathologising individuals and instead addresses ongoing structural inequalities. In the Australian context, with which the authors are most familiar and from where we write, there is considerable concern that ‘trauma’ and associated concepts such as intergenerational trauma and trauma-informed care are becoming ‘buzzwords’ that are used in policy discussions but do not lead to any concrete policy changes. Instead, invoking ‘trauma’ can obfuscate the need to direct attention to specific socio-environmental situations that need to be urgently addressed. The use of ‘intergenerational trauma’ in particular can lend to a sense that the marginalisation and discrimination that continue to impact the lives of many people are somehow inevitable and fixed [Reference Pentecost44].

For example, prominent Aboriginal scholar Chelsea Watego recently contended that the strikingly high rate of incarceration of Indigenous people in Australia, which is often described as an ‘intergenerational trauma issue’, is in fact an ‘institutional racism issue’ [Reference Watego45]. As seen in this example, there is a risk that trauma is being used as a vague umbrella term that does not name or make explicit the proximate sources of trauma. ‘Trauma’ can be a euphemism for the experience of forces like racism, poverty, and domestic violence, erasing the perpetrators (individual and/or state) and placing attention on the ‘recipient’ of the trauma and their capacity to ‘manage’, rather than on structural injustice and policy failures that need correcting. In the case of DOHaD, where the concept of intergenerational trauma is often invoked in relation to parenting, we are concerned that discourses of trauma can perpetuate increased surveillance of the ability of parents to cope with ‘their trauma’, rather than keeping the lens squarely focused on the structural conditions that lead to circumstances of difficulty in which families live.

Further, this focus on individual risk factors and parenting is often directed towards women and mothering. In their review of literature on intergenerational trauma in Latinx communities, Cerdeña et al. [Reference Cerdeña, Rivera and Spak1] found that, of the many mechanisms of intergenerational trauma transmission, the ‘vast majority center around disrupted maternal behaviour (e.g. maternal distress, maternal substance abuse, harsh parenting) and impaired attachment’. They describe this focus on maternal behaviour as a ‘weakness’ in DOHaD literature on intergenerational trauma as it fails to account for structural barriers [Reference Cerdeña, Rivera and Spak1, p. 17]. This slippage or trick is a common problem in studies of trauma, and in the DOHaD field more generally. Here, theories attuned to the biosocial are engaged to bring to light structural inequalities and marginalisation at socio-ecological levels (e.g. intergenerational trauma). Yet through the research process the undue focus on individual (and most often, maternal) behaviour as the scale of inquiry routinely propagates reductive frames of individual responsibility.

14.4 Conclusion

Intergenerational trauma is a powerful concept within the scientific fields that contribute to DOHaD research, and within a range of academic disciplines in the humanities and social sciences. The reach and utility of intergenerational trauma is a strength, allowing concepts from DOHaD research to travel far beyond the field and, in turn, to be influenced by many other disciplines concerned with biopolitics and social justice. However, with these strengths come inevitable weaknesses. Intergenerational trauma can be used to denote a cause, a mechanism, an effect, or all three at once. This capaciousness of the concept increases its usefulness to a range of scholars but decreases its precision. When there are attempts to operationalise intergenerational trauma through more precise definitions (e.g. PTSD diagnosis) and measurements (e.g. ACE scales), these can erase certain experiences of trauma, for example, those derived from a range of chronic experiences of racism and marginalisation rather than a discrete historical event. Further, focusing on the effects of intergenerational trauma on individuals often leads to a focus on interventions that seek to improve individual coping mechanisms rather than interventions that address the structural causes of trauma for marginalised groups. This can cause pathologising treatment of these groups as ‘inherently’ traumatised, paradoxically compounding the effects of intergenerational trauma. Similarly, a focus on pregnancy and maternal care as a mechanism of the transmission of intergenerational trauma can lead to the pathologisation of mothers as inherently risky to their children and as a site of surveillance and interventions.

For intergenerational trauma to be an empowering concept that leads to structural, collective change rather than punitive measures towards individuals, the tendency of DOHaD research and media reporting of this research to focus on mothers’ individual behaviours needs to be challenged (see [Reference Lappé46Reference Richardson, Daniels, Gillman, Golden, Kukla, Kuzawa and Rich-Edwards48]). Similarly, the keen interest in intergenerational trauma in DOHaD research should be balanced by stories of survivance and strength from communities that face intergenerational marginalisation. The growing interest in intergenerational trauma among a wide range of scholarly and clinical practitioners provides an opportunity for DOHaD researchers to exert a wide influence. The onus is on DOHaD researchers to ensure this influence leads to outcomes that promote social and reproductive justice.

Chapter 15 Bioethnography

Elizabeth F.S. Roberts , Jaclyn M. Goodrich , Erica C. Jansen , Belinda L. Needham , Brisa N. Sánchez , and Martha M. Téllez Rojo

Critical social scientists and scholars in medical anthropology, sociology, geography, science technology studies, and feminist theory had hoped that, by moving past genetic reductionism, DOHaD and allied postgenomic frameworks might become a bridge between life and social sciences [Reference Lock1Reference Jablonka and Lamb5]. DOHaD research, however, especially within biomedical paradigms, has often retained a reductive focus on the behaviour of individuals, especially mothers, instead of on the larger political-economic processes and environments that contribute to poor health and exacerbate inequality [Reference Lamoreaux6Reference Valdez10]. Additionally, DOHaD researchers, who tend to reside in high-resource environments, often universalise their own experience as they develop research questions and test hypotheses, rather than identifying the most relevant research questions for people living within circumstances quite different from their own.

DOHaD researchers can counteract this reductionism and universalism by incorporating more open-ended, iterative, observational methods into their investigations. Our multidisciplinary team engaged in an environmental health birth cohort study in Mexico City has been developing one such tool, ‘bioethnography’, which provides DOHaD with an even more powerful and sensitive framework for understanding the relationship of the environment to health outcomes and disease burdens. Our bioethnographic approach combines methods and data from both ethnography and the life sciences to arrive at a better understanding of the larger histories and life circumstances that shape health, disease, and inequality. Unlike most mixed or biocultural methods, where ethnographers are often asked to consult on data after its collection, bioethnography makes open-ended ethnography a first step, which provides the capacity to generate better hypotheses and better data about the developmental origins of disease.

Ethnographers usually reside long term with or near the people they are learning from, so that they can observe the dynamic environments that shape research participants’ lives. Additionally, ethnography tends to entail a wider aperture than focus groups or interviews, because the ethnographer does not predetermine a list of ‘standardised’ questions in advance. In its beginning stages, ethnography fosters what can seem like an excessive initial vagueness to scientists who are accustomed to deductively posing hypotheses in advance. By approaching a study population in a non-hypothesis-driven fashion, ethnography allows for deeper insights into how, where, when, and why people do what they do. Open-ended observations about a group can provide the basis for collecting more relevant and accurate environmental, quantitative, and biomarker data. While ethnographic findings are produced from a small sample size, they can guide the development of context-specific epidemiological hypotheses and appropriate data collection procedures to test them. In other words, ethnography can be used to generate empirically grounded theories and hypotheses about environmental causal mechanisms, which can then be tested in larger, population-representative samples [Reference Krieger and Davey11].

A short example of how we have used bioethnography to understand sleep illustrates the process. In 2016, birth cohort researchers began designing a new adolescent sleep survey that asked cohort participants, now teenagers, about length of sleep, perceived sleep quality, technology use before bedtime, and sleep difficulties, which would be combined with accelerometer data. At the initial survey design meetings, the ethnographer, who had lived near and worked with cohort families, noticed that the life science researchers assumed that participants had their own bedrooms, or at most shared them with one other person. Even though the ethnographer had never explicitly studied sleeping arrangements among project participants, she knew that in most participant homes, bedrooms accommodate up to eight people at once. This insight allowed the researchers to include survey questions about bedroom sharing. When the team analysed the data, they found that adolescents who shared a bedroom had lower levels of mental/emotional sleep disturbances than adolescents who did not share a bedroom, which complicates the assumptions embedded in research conducted among middle-class populations that bedroom sharing negatively impacts sleep quality [Reference Zamora, Arboleda-Merino, Tellez-Rojo, O’Brien, Torres-Olascoaga and Peterson12, Reference Chung, Wilson, Miller, Johnson, Lumeng and Chervin13]. This collaborative experience prompted the team to design a new bioethnographic sleep study that seeks to characterise the complex social, chemical, and economic ecology of sleep within households in Mexico City.

15.1 Bioethnography’s Background

Since 1994, researchers involved in the longitudinal birth cohort study, Early Life Exposures in Mexico to ENvironmental Toxicants (ELEMENT), have carried out chemical or molecular analysis of blood, urine, breast milk, hair, toenails, bone, and teeth, as well as administered questionnaires and psychometric testing on over 1,000 mother–child pairs, mostly living in working-class neighbourhoods in Mexico City [Reference Perng, Tamayo-Ortiz, Tang, Sánchez, Cantoral and Meeker14]. These women and children return for periodic follow-up visits. Initially, ELEMENT researchers focused on the effects of early-life lead exposure on neurological development in childhood (Tellez-Rojo et al., 2002). Over time, ELEMENT expanded to include additional metals, and other chemical exposures, that might affect conditions like diabetes, obesity, menopause, and sleep. Many ELEMENT researchers deploy a DOHaD framework, investigating whether chemical, dietary, or social ‘exposures’ during pregnancy, infancy, and puberty impact health outcomes [Reference Goodrich, Dolinoy, Sanhez, Zang, Mercado-Garcia and Solano-Gonzalez15]. In 2014, a medical anthropologist (Roberts, first author) began collaborating with ELEMENT to carry out long-term ethnographic observations with ELEMENT participants. Roberts aimed to combine her ethnographic findings about the lives of working-class participants with ELEMENT biomarker data. The goal of this ‘bioethnographic’ process was to ask questions more specific to the study population and to produce better knowledge about dynamic and situated bodily processes in a highly unequal world.

In 2014–2015, Roberts carried out long-term ethnographic work with a subset of six ELEMENT participant families, gathering extensive qualitative data on their everyday lives. This research involved living in participant neighbourhoods and spending three to six hours at a time with specific families, returning multiple days each week over the course of a year, and then follow-up visits ever since. During these visits, Roberts participated in and documented the families’ daily routines, including neighbourhood activities, such as festivals and political events, through field notes, photographs, and recordings, which were later thematically coded [Reference Roberts, Sanz and Meloni16]. After this initial intensive field work year, Roberts began working with ELEMENT researchers to combine ethnographic and biomarker data in projects focused on nutrition, sleep, and household water infrastructure in order to ask research questions that could not be answered through any one data source alone.

Bioethnography then is the combination of two different methodologies – ethnographic observation and biochemical sampling – in an analysis that understands environment–body interactions as always relational, contingent, and constructed phenomena. This combination of methods might sound like other mixed-methods approaches, but bioethnography is more open-ended than combining focus groups or interviews with quantitative data, where the focus and questions have been decided in advance. Additionally, bioethnography avoids designating biomarker data as ‘biological’ and ethnographic observations as ‘social’. Avoiding these domain designations makes it easier to grasp how phenomena like diabetes are produced together through class hierarchy, epigenetic processes, international trade agreements, household organisation, body mass index (BMI), and zoning laws, which are all parts of an ‘environment’.

The team’s experience with the iterative design and counter-intuitive results of the sleep study described above also demonstrated that bioethnography can reduce one of the biggest unseen challenges to DOHaD and health science investigations more generally. Euro-American researchers tend to be from middle-class backgrounds, which emphasise individual autonomy, while their study subjects tend to be from communities designated as, in some way, marginalised. Without knowing they are doing so, middle-class researchers tend to universalise their own experience and often do not know how to identify the important environmental drivers of the developmental origins of disease. Instead, many focus on what can be easily measured, like the characteristics of individuals (e.g. mother’s education or lack of it) or seemingly individual behaviours like sleep or eating, which, in practice, are deeply social.

Our bioethnographic collaborations have allowed us to develop three principles that guide our ongoing research projects: (1) individuals are not necessarily the most meaningful unit of analysis when, beyond households and neighbourhoods, nation-states and political and economic processes shape bodily conditions [Reference Diez-Roux17]; (2) biological conditions are as dynamic and historically shaped as any other process; and (3) an open-ended, ethnographically inductive stage before narrowing the aperture to a specific and testable hypothesis is a powerful means of generating robust research questions about the relationship of environment to disease. In the next section, we lay out how these principles can be applied to DOHaD-focused research by using examples from our bioethnographic work within ELEMENT, focused on eating and nutrition.

15.2 A Bioethnographic Approach to Eating and Nutrition

Throughout its first decades, ELEMENT researchers collected data about the diet and nutritional intake of ELEMENT mothers and children through standard methods, including semi-quantitative Food Frequency Questionnaires (FFQs). ELEMENT researchers published papers analysing prenatal and early childhood consumption patterns with health outcomes in adolescence, including body weight, metabolic markers, and timing of sexual maturation [Reference Cantoral, Téllez-Rojo, Ettinger, Hu, Hernández-Ávila and Peterson18Reference Mulcahy, Tellez-Rojo, Cantoral, Solano-González, Baylin and Bridges20]. In order to understand what biological mechanisms could explain how maternal nutrition during gestation influences children’s health, the ELEMENT team examined links between maternal diet and the epigenome (DNA methylation) of the children [Reference Wu, Sánchez, Goodrich, Dolinoy, Cantoral and Mercado-Garcia21]. In 2013, this research took on additional urgency when the WHO designated Mexico the world’s most obese industrial nation.

Soon after this designation, Roberts commenced ethnographic fieldwork in the households of ELEMENT participants and their neighbours. Much of her research focused on how ELEMENT families and their neighbours purchased, prepared, served, shared, and ate food. Roberts’ ethnographic findings affirmed what most ethnographies of food have long demonstrated about many non-elite communities: that eating is intrinsically collective [Reference Carsten22, Reference Weismantel23]. Few eat alone, and food is rarely measured, controlled, organised, or experienced as pertaining to individual health. Eating and sharing food reinforces collective survival, especially in economically precarious environments [Reference Carney24, Reference Fielding-Singh25]. In addition, girth and fat are often valued among groups who have experienced past deprivation, and sharing food is a common and potent way to care for others, especially children [Reference Kulick and Meneley26Reference Roberts28].

In light of the importance of shared eating, public messaging on billboards and public-service announcements decrying junk food, especially soda, as unhealthy seemed particularly tone-deaf to how participant households and their neighbours shared food and ate with others. The ubiquity of soda and the need to demonstrate love outweighed health education messages about the harms of soda. By ethnographically following study participants from their households and neighbourhoods to ELEMENT study visits, it was clear that ELEMENT study participants likely underreported consumption of FFQs, especially soda, because participants knew that soda was considered unhealthy by those administering the survey. Likewise, when sugar-sweetened beverages were banned from schools, women hid soda in their children’s lunches by putting clear soda in single-use water bottles [Reference Roberts28]. These ethnographic observations demonstrated that questionnaire items, such as ‘how much soda did you consume last week?’, are not likely to produce accurate data. Instead, researchers might develop surveys and questionnaires that ask respondents to describe the crucial elements of different meals or eating/drinking events throughout the day. Or perhaps: who shares in a meal? What do people ideally drink at meals? Who buys it? How much does it cost? Which household members drink what beverages? All of these questions might provide a better portrait of when, how, and why soda is consumed. Additionally, if DOHaD researchers built in ethnographic research early on, even before the recruitment of pregnant women, they would know more about the environments of their study participants, which could help them avoid the unintended moralism so common to survey data collection.

Ethnography also made it easier to see how the abundance of pleasurable foods available to share in working-class households in Mexico City is produced through global processes and trade agreements. Retail and census data have demonstrated that the North American Free Trade Agreement (NAFTA) inundated Mexico City’s food landscape with cheap, mass-marketed goods. Following NAFTA, Mexico overall registered increases in caloric intake, particularly for low-income households [Reference Berrigan, Arteaga, Colón-Ramos, Rosas, Monge-Rojas and O’Connor29]. In addition, government subsidies in the form of tax incentives, sugar subsidies, and water rights have made soda nearly as cheap as purchased water, and Mexico is now one of the largest per capita soda consumers on earth [Reference Delgado30]. Public health researchers’ response to this rise in soda consumption continues to focus on individual behaviour as driving this change, in effect continuing to designate mothers (i.e. their soda consumption patterns during pregnancy and the amount of soda they provide to their children) as the relevant environment to understand children’s health and development. But what if, instead, DOHaD researchers used longitudinal surveys and biomarker data before and after NAFTA to test the hypothesis that trade agreements like NAFTA are environmental processes that impact disease incidence?

Ethnographic findings about study participants’ food environments allowed the team to carry out a new ELEMENT diet and nutrition analysis. In one paper, our bioethnographic team compared ethnographic data about eating with the FFQ data of 550 cohort adolescents to reassess assumptions about diet patterns that standard epidemiological studies correlate with the nutrition transition [Reference Jansen, Marcovitch, Wolfson, Leighton, Peterson and Téllez-Rojo31]. The nutrition transition tends to be understood as a process in which people ‘choose’ to forsake traditional diets for Western diets, which are categorised as distinct dietary patterns. Our bioethnographic approach to understanding eating among cohort participants told a different story.

We found that rather than moving from one dietary pattern to another, the patterns we identified likely reflected the economic status of a household. If we had only carried out an epidemiological analysis, we might have characterised participants with a higher score on the plant-based and lean protein dietary pattern as choosing to follow an overall ‘healthy’ or ‘traditional’ diet. By including ethnographic data, we found, however, that adolescents with a higher score on this pattern likely lived in more economically stable households, where there were enough resources to prepare a large afternoon meal for sharing, with leftovers remaining for subsequent days. Furthermore, it was evident that in all household diets and meals there were elements of ‘Westernised’ and ‘traditional’ foods. This co-occurrence suggests that instead of adopting a more ‘Westernised’ pattern of eating and living, households may simply be incorporating available and affordable ‘Western’ foods into their typical meals. In sum, our bioethnographic findings challenged understandings about the nutrition transition as coming from individual preference or that families make clear-cut distinctions between traditional and Western foods. Importantly, our findings allowed us to call for more attention to how economic processes alter eating.

In another paper, we examined the range of other factors besides maternal body mass (understood in DOHaD terms as the outcome of biology and behaviour) that contribute to children’s body mass [Reference Téllez-Rojo, Trejo-Valdivia, Roberts, Muñoz-Rocha, Bautista-Arredondo and Peterson32]. The rapid worldwide increase in obesity in the last three decades, particularly in Mexico, suggests that forces beyond the biology and behaviour of mothers are at play in shaping weight. Our ethnographic data showed how transformations in Mexico’s food landscape made it easier than ever before for parents to provide children with cheap pleasurable processed foods and that at least 38 per cent of children’s BMI is not linkable to heritable factors like mother’s BMI. Attempts then at intervening in ‘food’ choices of mothers and families are less likely to be effective without interventions on the upstream drivers of diet and food availability, such as curtailing tax subsidies to transnational food and beverage corporations.

The bioethnographic findings of these two papers helped elucidate our first two principles for bioethnographic research described above: (1) eating and nutrition must not be understood through the lens of individual choice, and (2) biological conditions are inseparable from social processes. The effect of NAFTA on body mass over time makes it clear that metabolic processes are not separate from political economic processes, and trying to tease out the biological and social determinants of body mass may lead to missing the larger context producing the phenomena under question [Reference Gálvez33, Reference Vaughan, Adjaye-Gbewonyo and Mika34]. In other words, the developmental origins of adult diseases such as obesity are not located solely, or even primarily, in the ‘maternal environment’.

Additionally, our initial papers on eating and nutrition provided support for our third principle that ethnography can become a key driver for iteratively producing research questions, collecting data, and interpreting results, which then can generate hypotheses that are locally situated in the lived experiences of the study’s participants. In 2017, we commenced a larger scale bioethnographic project – developed through initial ethnographic observations – that in working-class communities in Mexico City, water tends to arrive intermittently, with complex effects. Household members experienced water as unreliable and unhealthy even though state authorities declare that at least 85 per cent of the nation receives water that is safe to drink [Reference Espinosa-Garcia, Diaz-Avalos, Villarreal, Malvaez-Orozco and Mazari-Hiriart35]. We also found that within the context of the advertising, ubiquity, reliability, and palatability of soda, drinking tap water made little sense.

These observations about the complex reality of water in working-class neighbourhoods have formed the basis for the bioethnographic study, ‘Neighbourhood Environments as Socio-Techno-Bio Systems: Water Quality, Public Trust, and Health in Mexico City’ (NESTSMX). NESTSMX combines ethnographic, environmental health, and environmental engineering methods to better understand the discrepancy between health messaging on the benefits and safety of water and residents’ distrust in water. Over the course of three years, we carried out multiple visits in 60 ELEMENT households (a large ‘n’ by ethnographic standards), collecting water quality, real-time water sensors, biometrics, health biomarkers (epigenetic and cortisol), and ethnographic data pertaining to the household and neighbourhood water environment [Reference Martinez Paz, Tobias, Escobar, Raskin, Roberts and Wigginton36]. So far, our findings demonstrate that within these 60 households, water intermittency and low water pressure compel residents to install domestic water management infrastructure – that is storage units, tubing, and pumps – which can negatively impact water quality. When water stagnates at collection points, chlorine disperses, providing an excellent environment for bacterial growth. There are also indications that specific kinds of water intermittency might impact water quality: for example, receiving water a few days a week might encourage more harmful bacteria growth in storage units. Household residents, especially the adult women who manage water provisioning, are quite familiar with the signs of water quality deterioration, which contributes to their distrust of tap water. These complex biosocial findings point to how intermittency might contribute to making soda a more sensible choice than water and might contribute to the incidence of chronic diseases, like diabetes. Our team is currently collaborating with the Encuesta Nacional de Salud y Nutrición (ENSANUT) to examine the impact of water intermittency on health, gender, and economic dynamics at a national scale.

Our complex bioethnographic understanding of intermittency has been made possible through our open-ended ethnographic process. If we only carried out surveys about attitudes or beliefs about water, just collected biomarker data, or only conducted an ethnography of eating and drinking, we would have foreclosed the possibility of understanding the complex reasons people drink soda or bottled water. With NESTSMX, we can apprehend how food environments – now dominated by multinational corporations, as well as urban planning and domestic architecture – dramatically shape what and how people drink in Mexico City. NESTSMX’s bioethnographic approach demonstrates that taking time to ascertain the relevant complex early life environments is a powerful means to understand health and disease over the lifecourse.

15.3 Bioethnography and Causal Mechanisms

The open-ended and iterative nature of bioethnography serves as a ‘seed bed’ for understanding and potentially measuring ‘the how and the why’; in other words, what meaningfully shapes early life environments that contribute to later life disease [Reference Roberts37, 359]. Most epidemiologically informed DOHaD studies deploy standard regression techniques that attempt to isolate the unidirectional effect of an exposure (e.g. maternal diet during pregnancy) on an outcome (e.g. offspring BMI) [Reference Clark, Martin, Bulka, Smeester, Santos and O’Shea38, Reference Strohmaier, Bogl, Eliassen, Massa, Field and Chavarro39]. Few pay attention to participants’ bodies as dynamically situated in a specific time and space. By providing a means to examine how or why phenomena cause and are caused by more than one variable within a particular context, bioethnography enables the development and testing of context-specific theories behind these complex interrelationships.

Implementing an early open-ended ethnographic period can be used to develop theory-based hypotheses and to test causal mechanisms in specific contexts. For example, it is often assumed that proximity to supermarkets supports healthy diets. With this assumption in place, researchers have developed a suite of tools to measure the relationship of individual dietary intake to contextual factors like supermarket proximity. Ethnographic observations of ELEMENT participants revealed, however, that supermarket access might actually be detrimental to healthy eating patterns among people in working-class neighbourhoods in Mexico City. In these neighbourhoods, women procure fresh produce available from open-air mobile markets and procure sodas and processed food from supermarkets, where they are cheaper compared to their neighbourhood corner stores. In addition to measuring the proximity of supermarkets, which has become standard in food environment research, investigators could deploy ethnographic work early on to make more context-specific measures of food outlets and their role. By also including economic processes such as the displacement of mobile markets with supermarkets as part of the dynamic food environment, researchers can move beyond individual behaviour and develop a more accurate picture of the causal mechanisms behind nutritional intake that develop over time.

Open-ended bioethnographic research can identify more relevant, sensitive measures of behavioural mechanisms and improve upon a standard set of variables that are otherwise assumed to be universalisable from one context to another. After this open-ended stage, epidemiological methods can be implemented to test the generalisability of ethnographic observations in larger study populations. During survey question development and testing, bioethnographic research teams can test survey validity through cross-referencing responses to survey items with ethnographic observations of daily life on a sample of study participants. Such cross-referencing could also be used to further refine and extend survey instruments. Ultimately, the more comprehensive bioethnographically informed and highly granular data that are specific to the context and population under study can be used to statistically test causal mechanisms using traditional epidemiological methods. Validating and testing theories derived from ethnographic observations of mechanisms in the same population where they were observed can fill critical gaps in studies that associate environments with health and disease over the lifecourse.

15.4 Conclusion

As we have detailed elsewhere, there are enormous challenges to proposing, designing, and carrying out bioethnographic research [Reference Roberts, Sanz and Meloni16, Reference Roberts37, Reference Leighton and Roberts40]. Investigators in the life and social sciences are situated in radically different research ecologies with different obligations, incentive structures, epistemological assumptions, funding mechanisms, and research models and practices, all of which can pose challenges to interdisciplinary collaboration. Publishing can be difficult because of the specific disciplinary demands of journals around acceptable data sources and writing style. Perhaps the biggest challenge of all is how funding mechanisms are structured. For instance, in the United States, NIH funding requires researchers to narrow their research questions into specific aims and testable hypotheses in advance, which make it difficult to develop a comprehensive understanding of the complex environmental processes that shape the lifecourse. So far, our bioethnographic research within ELEMENT has been funded through the National Science Foundation and internal university sources. These sources, however, do not typically provide enough funds to carry out bioethnographic work with a large enough sample size for validity in life science research.

The challenges to bioethnographic research posed by structural issues like funding result in the exact reductionism and universalism that bioethnographic research seeks to overcome. Addressing these difficult issues is crucial, so that DOHaD researchers can adopt more open-ended and iterative approaches like bioethnography to ask better questions, produce better data, and arrive at more comprehensive knowledge about how environmental processes shape health and disease over the lifecourse.

Footnotes

Chapter 10 Lifecourse

Chapter 11 Syndemics

Chapter 12 Embodiment

Chapter 13 Causal Crypticity

Chapter 14 Intergenerational Trauma

Chapter 15 Bioethnography

The authors are deeply grateful for ELEMENT PI, Karen Petersen’s support and encouragement in developing this paper, and our bioethnographic approach over the last decade. The various projects described in this paper were made possible by members of the ELEMENT team in Mexico and the United States: Libni Avib Torres Olascoaga, Luis Bautista, Astrid Zamora, Laura Arboleda Merino, Ana Benito, and Adriana Mercado. The team from the NESTSMX project also provided insight and support for practising and theorising bioethnography: David Palma, Mary Leighton, Ernesto Martinez, Alyssa Huberts, Hannah Marcovitch, Faith Cole, Zoe Boudart, Paloma Contreras, Krista Wigginton, Branko Kerkez, and Lesli Scott. This chapter is much stronger through conversations with the editors of this handbook – Michelle Pentecost, Jaya Keaney, Tessa Moll, and Michael Penkler – as well as our workshop exchange buddies Chris Kuzawa and Ayuba Issaka, with members of the Biosocial Birth Cohort Network led by Sahra Gibbon. The bioethnographic efforts we describe here were funded and supported by the Instituto Nacional de Salud Pública, the National Institute of Health, the National Science Foundation, the Wenner Gren, and the University of Michigan through the Institute for Research on Women and Gender, the College of Letters Arts and Sciences, and the Institute for Social Research Center for Group Dynamics.

References

References

Banati, P. Bringing life course theory to the sustainable development goals. In: Verma, S, Petersen, A, editors. Developmental Science and Sustainable Development Goals for Children and Youth. Cham, Switzerland: Springer International Publishing; 2018. pp. 313328.CrossRefGoogle Scholar
Halfon, N, Larson, K, Lu, M, Tullis, E, Russ, S. Lifecourse health development: Past, present and future. Matern Child Health J. 2014;18(2):344–65.CrossRefGoogle ScholarPubMed
Elder, GH. The life course as developmental theory. Child Dev. 1998;69(1):112.CrossRefGoogle ScholarPubMed
Morgan, B, Kumsta, R, Fearon, P, Moser, D, Skeen, S, Cooper, P, et al. Serotonin transporter gene (SLC6A4) polymorphism and susceptibility to a home-visiting maternal-infant attachment intervention delivered by community health workers in South Africa: Reanalysis of a randomized controlled trial. PLoS Med. 2017;14(2):e1002237.CrossRefGoogle ScholarPubMed
Elder, GH, Shanahan, MJ. Handbook of Child Psychology. Lerner, RM, editor. New Jersey: John Wiley & Sons; 2006.Google Scholar
Halfon, N, Forrest, CB, Lerner, RM, Faustman, EM, Tullis, E, Son, J. Introduction to the Handbook of Life Course Health Development. In: Forrest, Christopher B., Halfon, Neal, and Lerner, Richard M., editors. Handbook of Life Course Health Development. Cham, Switzerland: Springer; 2018. pp. 118.CrossRefGoogle ScholarPubMed
Hertzman, C, Boyce, T. How experience gets under the skin to create gradients in developmental health. Annu Rev Public Health. 2010;31:329–47CrossRefGoogle ScholarPubMed
Hughes, K, Bellis, MA, Hardcastle, KA, Sethi, D, Butchart, A, Mikton, C, et al. The effect of multiple adverse childhood experiences on health: A systematic review and meta-analysis. Lancet Public Health. 2017;2(8):e356–e66.CrossRefGoogle Scholar
Sameroff, A. A unified theory of development: A dialectic integration of nature and nurture. Child Dev. 2010;81(1):622.CrossRefGoogle ScholarPubMed
Barker, DJP. The origins of the developmental origins theory. J Intern Med. 2007;261(5):412–7.CrossRefGoogle ScholarPubMed
Salsberry, P, Tanda, R, Anderson, SE, Kamboj, MK. Pediatric Type-2 Diabetes: Prevention and Treatment Through a Life Course Health Development Framework. In: Forrest, Christopher B., Halfon, Neal, and Lerner, Richard M., editors. Handbook of Life Course Health Development. Cham, Switzerland: Springer; 2018. pp. 197236.CrossRefGoogle ScholarPubMed
Fleming, TP, Watkins, AJ, Velazquez, MA, Mathers, JC, Prentice, AM, Stephenson, J, et al. Origins of lifetime health around the time of conception: Causes and consequences. Lancet. 2018;391(10132):1842–52.CrossRefGoogle ScholarPubMed
McEwen, BS. Protective and damaging effects of stress mediators. N Engl J Med. 1998;338(3):171–9.CrossRefGoogle ScholarPubMed
McEwen, BS. Effects of adverse experiences for brain structure and function. Biol Psychiatry. 2000;48(8):721–31.CrossRefGoogle ScholarPubMed
de Kloet, ER, Fitzsimons, CP, Datson, NA, Meijer, OC, Vreugdenhil, E. Glucocorticoid signaling and stress-related limbic susceptibility pathway: About receptors, transcription machinery and microRNA. Brain Res. 2009;1293:129–41.CrossRefGoogle ScholarPubMed
Ellis, BJ, Boyce, WT, Belsky, J, Bakermans-Kranenburg, MJ, van Ijzendoorn, MH. Differential susceptibility to the environment: An evolutionary – Neurodevelopmental theory. Dev Psychopathol. 2011;23(1):728.CrossRefGoogle Scholar
Boyce, WT. Epigenomic susceptibility to the social world: Plausible paths to a ‘Newest Morbidity’. Acad Pediatr. 2017;17(6):600–6.CrossRefGoogle Scholar
Boyce, WT, Ellis, BJ. Biological sensitivity to context: I. An evolutionary-developmental theory of the origins and functions of stress reactivity. Dev Psychopathol. 2005;17(2):271301.CrossRefGoogle ScholarPubMed
Boyce, WT. The Orchid and the Dandelion: Why Sensitive People Struggle and How All Can Thrive. London: Pan MacMillan; 2019.Google Scholar
Boyce, WT, Ellis, BJ. Biological sensitivity to context: I. An evolutionary–developmental theory of the origins and functions of stress reactivity. Development and Psychopathology. 2005;17:271301.CrossRefGoogle ScholarPubMed
Ellis, BJ, Boyce, WT, Belsky, J, Bakermans-Kranenburg, MJ, Van IJzendoorn, MH. Differential susceptibility to the environment: An evolutionary–neurodevelopmental theory. Development and Psychopathology. 2011;23(1):728.CrossRefGoogle Scholar
Masten, A, Cicchetti, D. Developmental cascades. Dev Psychopathol. 2010;22(3):491–5.CrossRefGoogle ScholarPubMed
Patton, GC, Olsson, CA, Skirbekk, V, Saffery, R, Wlodek, ME, Azzopardi, PS, et al. Adolescence and the next generation. Nature. 2018;554(7693):458–66.CrossRefGoogle ScholarPubMed
Kim, P, Evans, GW, Chen, E, Miller, GE, Seeman, T. How socioeconomic disadvantages get under the skin and into the brain to influence health development across the lifespan. In: Halfon, N, Forrest, CB, Lerner, RM, Faustman, EM, editors. Handbook of Life Course Health Development. Berlin: Springer; 2018. pp. 463–97.Google Scholar
Meijer, M, Röhl, J, Bloomfield, K, Grittner, U. Do neighborhoods affect individual mortality? A systematic review and meta-analysis of multilevel studies. Soc Sci Med. 2012;74:1204–12.CrossRefGoogle ScholarPubMed
Lopez, M, Ruiz, MO, Rovnaghi, CR, Tam, GK, Hiscox, J, Gotlib, IH, et al. The social ecology of childhood and early life adversity. Pediatr Res. 2021;89(2):353–67.CrossRefGoogle ScholarPubMed
Ulrich-Lai, YM, Herman, JP. Neural regulation of endocrine and autonomic stress responses. Nat Rev Neurosci. 2009;10(6):397409.CrossRefGoogle ScholarPubMed
Halfon, N, Forrest, CB, Lerner, RM. Life Course Research Agenda (LCRA), Version 1.0. In: Halfon, N. FC, Lerner, R., Faustman, E., editors. Handbook of Life Course Health Development. Cham, Switzerland: Springer; 2018. pp. 623–45.CrossRefGoogle ScholarPubMed
Halfon, N, Forrest, CB. The emerging theoretical framework of life course health development. In: Halfon, N, Forrest, CB, Lerner, RM, Faustman, EM, editors. Handbook of Life Course Health-development Science. Berlin: Springer; 2017. pp. 1943.Google Scholar
Ungar, M. Systemic resilience: Principles and processes for a science of change in contexts of adversity. Ecol Soc. 2018;23(4).CrossRefGoogle Scholar
Suleiman, AB, Dahl, RE. Leveraging neuroscience to inform adolescent health: The need for an innovative transdisciplinary developmental science of adolescence. J Adolesc Health. 2017;60(3):240–8.CrossRefGoogle ScholarPubMed
Braveman, P. What is health equity: and how does a life-course approach take us further toward it? Matern Child Health J. 2014;18(2):366–72.CrossRefGoogle ScholarPubMed

References

Singer, M. A dose of drugs, a touch of violence, a case of AIDS: Conceptualizing the SAVA syndemic. Free Inq Creat Sociol. 1996;24(2):99110.Google Scholar
Singer, M, Clair, S. Syndemics and public health: Reconceptualizing disease in bio-social context. Med Anthropol Q. 2003;17(4):423441.CrossRefGoogle Scholar
Milstein, B. An introduction to the syndemics: Implications for health promotion. Syndemics prevention network, centers for disease control and prevention. (2006). Available from: www.google.de/?gws_rd=ssl#q=Milstein+Introduction+to+syndemicsGoogle Scholar
Tsai, AC. Syndemics: A theory in search of data or data in search of a theory? Soc Sci Med. 2018;206:117122.CrossRefGoogle ScholarPubMed
Mendenhall, E. Syndemic Suffering: Social Distress, Depression, and Diabetes among Mexican Immigrant Women. Routledge, New York; 2012.Google Scholar
Lynch, EB, Fernandez, A, Lighthouse, N, Mendenhall, E, Jacobs, E. Concepts of diabetes self-management in Mexican American and African American low-income patients with diabetes. Health Educ Res. 2012;27(5):814824.CrossRefGoogle ScholarPubMed
Mendenhall, E, Seligman, RA, Fernandez, A, Jacobs, EA. Speaking through diabetes: Rethinking the significance of lay discourses on diabetes. Med Anthropol Q. 2010;24(2):220239.CrossRefGoogle ScholarPubMed
Soepnel, LM, McKinley, MC, Klingberg, S, et al. Evaluation of a text messaging intervention to promote preconception micronutrient supplement use: Feasibility study nested in the healthy life trajectories initiative study in South Africa. JMIR Form Res. 2022;6(8):e37309.CrossRefGoogle ScholarPubMed
Proctor, DA. Testing the waters: Syndemic gastrointestinal distress in Lambaréné, Gabon, 1926–1932. Soc Sci Med. 2022;295:113405.CrossRefGoogle ScholarPubMed
Newfield, T. Syndemics and the history of disease: Towards a new engagement. Soc Sci Med. 2022;295:114454.CrossRefGoogle ScholarPubMed
Roseboom, T, de Rooij, S, Painter, R. The Dutch famine and its long-term consequences for adult health. Early Hum Dev. 2006;82(8):485491.CrossRefGoogle ScholarPubMed
Heijmans, BT, Tobi, EW, Stein, AD, et al. Persistent epigenetic differences associated with prenatal exposure to famine in humans. Proc Natl Acad Sci USA. 2008;105(44):1704617049.CrossRefGoogle ScholarPubMed
Song, S, Wang, W, Hu, P. Famine, death, and madness: Schizophrenia in early adulthood after prenatal exposure to the Chinese Great Leap Forward Famine. Soc Sci Med. 2009;68(7):13151321.CrossRefGoogle Scholar
El Hajj, N, Schneider, E, Lehnen, H, Haaf, T. Epigenetics and life-long consequences of an adverse nutritional and diabetic intrauterine environment. Reproduction. 2014;148(6):R111R120.CrossRefGoogle ScholarPubMed
Mendenhall, E. Rethinking Diabetes: Entanglements with Trauma, Poverty, and HIV. Cornell University Press, Ithaca, NY; 2019.Google Scholar
Manderson, L, Ross, FC. Publics, technologies and interventions in reproduction and early life in South Africa. Humanit Soc Sci Commun. 2020;7(1):40.CrossRefGoogle Scholar
Douglas-Vail, M. Syndemics theory and its applications to HIV/AIDS public-health interventions. Int J Med Sociol Anthropol. 2016;6(1):001010.Google Scholar
Kalyani, RR, Golden, SH, Cefalu, WT. Diabetes and aging: Unique considerations and goals of care. Diabetes Care. 2017;40(4):440443.CrossRefGoogle ScholarPubMed
Mendenhall, E, Richter, LM, Stein, A, Norris, SA. Psychological and physical co-morbidity among urban South African women. PLoS One. 2013;8(10):e78803.CrossRefGoogle ScholarPubMed
Hardin, J. Faith and the Pursuit of Health: Cardiometabolic Disorders in Samoa. Rutgers University Press, New Brunswick; 2019.CrossRefGoogle Scholar
Gálvez, A. Eating NAFTA: Trade, Food Policies, and the Destruction of Mexico. University of California Press, Berkeley; 2018.CrossRefGoogle Scholar
Yates-Doerr, E. The Weight of Obesity: Hunger and Global Health in Postwar Guatemala. University of California Press, Berkeley; 2015.CrossRefGoogle Scholar
Moodley, G, Christofides, N, Norris, SA, Achia, T, Hofman, KJ. Obesogenic environments: Access to and advertising of sugar-sweetened beverages in Soweto, South Africa, 2013. Prev Chronic Dis. 2015;12:E186.CrossRefGoogle ScholarPubMed
Barnett, K, Mercer, SW, Norbury, M, Watt, G, Wyke, S, Guthrie, B. Epidemiology of multimorbidity and implications for health care, research, and medical education: A cross-sectional study. Lancet. 2012;380(9836):3743.CrossRefGoogle ScholarPubMed
Gluckman, PD, Hanson, MA, Mitchell, MD. Developmental origins of health and disease: Reducing the burden of chronic disease in the next generation. Genome Med. 2010;2(14):13.CrossRefGoogle ScholarPubMed
Cohen, E, Ware, LJ, Prioreschi, A, Draper, C, Bosire, E et al. Material and relational difficulties: The impact of the household environment on the emotional well-being of young Black women living in Soweto, South Africa. J Fam Issues. 2020; 41(8):13071332CrossRefGoogle Scholar
Bouvette-Turcot, AA, Unternaehrer, E, Gaudreau, H, et al. The joint contribution of maternal history of early adversity and adulthood depression to socioeconomic status and potential relevance for offspring development. J Affect Disord. 2017;207:2631.CrossRefGoogle ScholarPubMed
Bosire, EN, Cele, L, Potelwa, X, Cho, A, Mendenhall, E. God, Church water and spirituality: Perspectives on health and healing in Soweto, South Africa. Glob Public Health. 2022;17(7):11721185.CrossRefGoogle ScholarPubMed
Norman, RE, Byambaa, M, De, R, Butchart, A, Scott, J, Vos, T. The long-term health consequences of child physical abuse, emotional abuse, and neglect: A systematic review and meta-analysis. PLoS Med. 2012;9(11):e1001349.CrossRefGoogle ScholarPubMed
Miller, GE, Chen, E, Parker, KJ. Psychological stress in childhood and susceptibility to the chronic diseases of aging: Moving toward a model of behavioral and biological mechanisms. Psychol Bull. 2011;137(6):959997.CrossRefGoogle Scholar

References

Clarkin, PF. The embodiment of war: Growth, development, and armed conflict. Annual Review of Anthropology. 2019 21 Oct;48(1):423–42.CrossRefGoogle Scholar
Musolino, CM, Warin, M, Gilchrist, P. Embodiment as a paradigm for understanding and treating SE-AN: Locating the self in culture. Frontiers in Psychiatry. 2020 Jun 12;11:534.CrossRefGoogle ScholarPubMed
Mehta, N. Mind-body dualism: A critique from a health perspective. Mens Sana Monographs. 2011 Jan;9(1):202.CrossRefGoogle ScholarPubMed
Goldberg, L. Rethinking the birthing body: Cartesian dualism and perinatal nursing. Journal of Advanced Nursing. 2002 Mar;37(5):446–51.CrossRefGoogle ScholarPubMed
Scheper‐Hughes, N, Lock, MM. The mindful body: A prolegomenon to future work in medical anthropology. Medical Anthropology Quarterly. 1987 Mar;1(1):641.CrossRefGoogle Scholar
Csordas, TJ, Harwood, A, editors. Embodiment and Experience: The Existential Ground of Culture and Self. United Kingdom: Cambridge University Press; 1994 17 Nov.Google Scholar
Krieger, N. Theories for social epidemiology in the twenty-first century: An ecosocial perspective. International Journal of Epidemiology. 2001;30(4):668–77.CrossRefGoogle Scholar
Zigon, J, Throop, J. Phenomenology. The Cambridge Encyclopaedia of Anthropology. 2021 Aug. http://doi.org/10.29164/21phenomenologyCrossRefGoogle Scholar
Bourdieu, P. Outline of a Theory or Practice. Trans. Nice, Richard. Cambridge: Cambridge University Press; 1977:21–2.CrossRefGoogle Scholar
Gravlee, CC. How race becomes biology: Embodiment of social inequality. American Journal of Physical Anthropology. 2009 May;139(1):4757.CrossRefGoogle ScholarPubMed
Manderson, L, Ross, FC. Publics, technologies and interventions in reproduction and early life in South Africa. Humanities and Social Sciences Communications. 2020;7(1):19.CrossRefGoogle Scholar
Yates-Doerr, E. Bodily betrayal: Love and anger in the time of epigenetics. A Companion to the Anthropology of the Body and Embodiment. 2011:292–306.CrossRefGoogle Scholar
Groeneveld, IF, Solomons, NW, Doak, CM. Nutritional status of urban schoolchildren of high and low socioeconomic status in Quetzaltenango, Guatemala. Revista Panamericana de Salud Pública. 2007;22:169–77.CrossRefGoogle ScholarPubMed
Hall, KD. Challenges of human nutrition research. Science. 2020 20 Mar;367(6484):1298–300.CrossRefGoogle ScholarPubMed
Rubin, SE, Hines, J. ‘As long as I got a breath in my body’: Risk and resistance in Black maternal embodiment. Culture, Medicine, and Psychiatry. 2022 6 Apr;47(2):495518.CrossRefGoogle Scholar
Mutendi, M. ‘Making a Plan to Keep My Baby’: Navigating Maternal Health Policy Among South African Mineworkers. Bodies of Knowledge: Children and Childhoods in Health and Affliction. 2021 1 Dec:227-248.CrossRefGoogle Scholar
South Africa. Basic Conditions of Employment Act 75 of 1997Google Scholar
David, R, Collins J, Jr. Disparities in infant mortality: What’s genetics got to do with it? American Journal of Public Health. 2007 Jul;97(7):1191–7.CrossRefGoogle Scholar
Kim, AW, Mohamed, RS, Norris, SA, Richter, LM, Kuzawa, CW). Psychological Legacies of Intergenerational Trauma under South African Apartheid: Prenatal Stress Predicts Increased Psychiatric Morbidity during Late Adolescence and Early Adulthood in Soweto, South Africa. medRxiv. 2021.CrossRefGoogle Scholar
Foucault, M. Discipline and punish: The birth of the prison (Trans A. Sheridan). New York: Vintage Books. 1977 (Original work published 1975).Google Scholar
Kuzawa, CW, Sweet, E. Epigenetics and the embodiment of race: Developmental origins of US racial disparities in cardiovascular health. American Journal of Human Biology: The Official Journal of the Human Biology Association. 2009 Jan;21(1):215.CrossRefGoogle ScholarPubMed
Krieger, N. Ecosocial Theory, Embodied Truths, and the People’s Health. USA: Oxford University Press; 2021.CrossRefGoogle Scholar

References

Heijmans, BT, Mill, J. The seven plagues of epigenetic epidemiology. International Journal of Epidemiology. 2012;41(1):74–8.CrossRefGoogle ScholarPubMed
Lawlor, DA, Relton, C, Sattar, N, Nelson, SM. Maternal adiposity – A determinant of perinatal and offspring outcomes? Nature Reviews Endocrinology. 2012;8(11):679–88.CrossRefGoogle ScholarPubMed
Richmond, R, Relton, C, Davey Smith, G. What evidence is required to suggest that DNA methylation mediates the association between prenatal famine exposure and adulthood disease. Scientific Advances. 2018;eLetter to eaao4364.Google Scholar
Paneth, N, Susser, M. Early origin of coronary heart disease (the ‘Barker hypothesis’). British Medical Journal. 1995;310(6977):411–12.CrossRefGoogle ScholarPubMed
Lancet. An overstretched hypothesis? Lancet. 2001;357(9254):405.CrossRefGoogle Scholar
Geronimus, AT. Deep integration: Letting the epigenome out of the bottle without losing sight of the structural origins of population health. American Journal of Public Health. 2013;103:S56.CrossRefGoogle ScholarPubMed
Wilcox, AJ. On the importance – and the unimportance – of birthweight. International Journal of Epidemiology. 2001;30(6):1233–41.CrossRefGoogle ScholarPubMed
Birney, E, Smith, GD, Greally, JM. Epigenome-wide association studies and the interpretation of disease -omics. PLOS Genetics. 2016;12(6):e1006105.CrossRefGoogle ScholarPubMed
Davey Smith, G, Hemani, G. Mendelian randomization: Genetic anchors for causal inference in epidemiological studies. Human Molecular Genetics. 2014;23(R1):R89R98.CrossRefGoogle ScholarPubMed
Langley, K, Heron, J, Smith, GD, Thapar, A. Maternal and paternal smoking during pregnancy and risk of ADHD symptoms in offspring: Testing for intrauterine effects. Am Journal of Epidemiology. 2012;176(3):261–8.CrossRefGoogle ScholarPubMed
Lawlor, DA, Timpson, NJ, Harbord, RM, Leary, S, Ness, A, McCarthy, MI, et al. Exploring the developmental overnutrition hypothesis using parental-offspring associations and FTO as an instrumental variable. PLoS Medicine. 2008;5(3):e33.CrossRefGoogle ScholarPubMed
Richmond, RC, Timpson, NJ, Felix, JF, Palmer, T, Gaillard, R, McMahon, G, et al. Using genetic variation to explore the causal effect of maternal pregnancy adiposity on future offspring adiposity: A Mendelian Randomisation Study. PLoS Medicine. 2017;14(1):e1002221.CrossRefGoogle ScholarPubMed
Richardson, SS. The Maternal Imprint: The Contested Science of Maternal-fetal Effects. Chicago: University of Chicago Press; 2021. 310 p.CrossRefGoogle Scholar
Woodward, JF. Making Things Happen: A Theory of Causal Explanation. New York: Oxford University Press; 2003. vi, 410 p.Google Scholar
Lumey, LH, Stein, AD, Kahn, HS, van der Pal-de Bruin, KM, Blauw, GJ, Zybert, PA, et al. Cohort profile: The Dutch Hunger Winter families study. International Journal of Epidemiology. 2007;36(6):1196–204.CrossRefGoogle ScholarPubMed
Stein, AD, Zybert, PA, van der Pal-de, Bruin K, Lumey, LH. Exposure to famine during gestation, size at birth, and blood pressure at age 59 y: Evidence from the Dutch famine. European Journal of Epidemiology. 2006;21(10):759–65.CrossRefGoogle ScholarPubMed
Rundle, A, Stein, AD, Kahn, HS, van der Pal–de Bruin, K, Zybert, PA, Lumey, L. Anthropometric measures in middle age after exposure to famine during gestation: Evidence from the Dutch famine. The American Journal of Clinical Nutrition. 2007;85(3):869–76.Google Scholar
Lumey, LH, Stein, AD, Susser, E. Prenatal famine and adult health. Annual Review of Public Health. 2011;32(1):237–62.CrossRefGoogle ScholarPubMed
Ravelli, GP, Stein, ZA, Susser, MW. Obesity in young men after famine exposure in utero and early infancy. New England Journal of Medicine. 1976;295(7):349–53.CrossRefGoogle ScholarPubMed
Heijmans, BT, Tobi, EW, Stein, AD, Putter, H, Blauw, GJ, Susser, ES, et al. Persistent epigenetic differences associated with prenatal exposure to famine in humans. Proceedings of the National Academy of Sciences. 2008;105(44):17046–9.CrossRefGoogle ScholarPubMed
Tobi, EW, Slieker, RC, Luijk, R, Dekkers, KF, Stein, AD, Xu, KM, et al. DNA methylation as a mediator of the association between prenatal adversity and risk factors for metabolic disease in adulthood. Science Advances. 2018;4(1):eaao4364.CrossRefGoogle ScholarPubMed
Roseboom, TJ. Epidemiological evidence for the developmental origins of health and disease: Effects of prenatal undernutrition in humans. Journal of Endocrinology. 2019;242(1):T135–T44.CrossRefGoogle ScholarPubMed
Zimmer, C. The famine ended 70 years ago, but Dutch genes still bear scars. The New York Times. 2018 31 Jan.Google Scholar
Sharp, GC, Lawlor, DA, Richardson, SS. It’s the mother!: How assumptions about the causal primacy of maternal effects influence research on the developmental origins of health and disease. Social Science & Medicine. 2018;213:20–7.CrossRefGoogle ScholarPubMed
Bourdieu, P. The specificity of the scientific field and the social conditions of the progress of reason. Social Science Information. 1975;14(6):1947.CrossRefGoogle Scholar
Panofsky, A. Misbehaving Science: Controversy and the Development of Behavior Genetics. Chicago: The University of Chicago Press; 2014.CrossRefGoogle Scholar
Kuhn, TS. The Structure of Scientific Revolutions. Chicago: University of Chicago Press; 1962. xv, 172 p.Google Scholar
Knorr-Cetina, K. Epistemic Cultures: How the Sciences Make Knowledge. Cambridge, MA: Harvard University Press; 1999. xiii, 329 p.CrossRefGoogle Scholar
Fortun, M. Promising Genomics: Iceland and deCODE Genetics in a World of Speculation. Berkeley: University of California Press; 2008.CrossRefGoogle Scholar
Caulfield, T. Spinning the genome: Why science hype matters. Perspectives in Biology and Medicine. 2018;61:560–71.CrossRefGoogle ScholarPubMed
Jacob, CM, Hanson, M. Implications of the Developmental Origins of Health and Disease concept for policy-making. Current Opinion in Endocrine and Metabolic Research. 2020;13:20–7.CrossRefGoogle Scholar
Heeney, C. Problems and promises: How to tell the story of a Genome Wide Association Study? Studies in History and Philosophy of Science Part A. 2021;89:110.CrossRefGoogle ScholarPubMed
Penkler, M. Caring for biosocial complexity. Articulations of the environment in research on the Developmental Origins of Health and Disease. Studies in History and Philosophy of Science. 2022;93:110.CrossRefGoogle ScholarPubMed
Berkowitz, GS, Wolff, MS, Janevic, TM, Holzman, IR, Yehuda, R, Landrigan, PJ. The world trade center disaster and intrauterine growth restriction. JAMA: Journal of the American Medical Association. 2003;290(5):595–6.CrossRefGoogle ScholarPubMed
Engel, SM, Berkowitz, GS, Wolff, MS, Yehuda, R. Psychological trauma associated with the World Trade Center attacks and its effect on pregnancy outcome. Paediatric and Perinatal Epidemiology. 2005;19(5):334–41.CrossRefGoogle ScholarPubMed
Ohlsson, A, Shah, PS, the Knowledge Synthesis Group of Determinants of Preterm LBWb. Effects of the September 11, 2001 disaster on pregnancy outcomes: A systematic review. Acta Obstetricia et Gynecologica Scandinavica. 2011;90(1):618.CrossRefGoogle ScholarPubMed
Wesselink, AK, Wellenius, GA. Impacts of climate change on reproductive, perinatal and paediatric health. Paediatric and Perinatal Epidemiology. 2022;36(1):13.CrossRefGoogle ScholarPubMed
Cao-Lei, L, de Rooij, SR, King, S, Matthews, SG, Metz, GAS, Roseboom, TJ, et al. Prenatal stress and epigenetics. Neuroscience and Biobehavioral Reviews. 2017;117:198210.CrossRefGoogle ScholarPubMed
Derfel, A. Prenatal stress from extreme weather is having negative effect on babies. The Montreal Gazette. 2009 31 Jan;Sect. News.Google Scholar
Forestieri, S, Pintus, R, Marcialis, MA, Pintus, MC, Fanos, V. COVID-19 and developmental origins of health and disease. Early Human Development. 2021;155:105322.CrossRefGoogle ScholarPubMed
Roseboom, TJ, Ozanne, SE, Godfrey, KM, Isasi, CR, Itoh, H, Simmons, R, et al. Unheard, unseen and unprotected: DOHaD council’s call for action to protect the younger generation from the long-term effects of COVID-19. Journal of Developmental Origins of Health and Disease. 2021;12(1):35.CrossRefGoogle ScholarPubMed
Schoenmakers, S, Verweij, EJ, Beijers, R, Bijma, HH, Been, JV, Steegers-Theunissen, RPM, et al. The impact of maternal prenatal stress related to the COVID-19 pandemic during the first 1000 days: A historical perspective. International Journal of Environmental Research and Public Health. 2022;19(8):4710.CrossRefGoogle Scholar
Valdez, N. Weighing the Future: Race, Science, and Pregnancy Trials in the Postgenomic Era. Oakland: University of California Press; 2022. pages cm p.Google Scholar
Murphy, M. The Economization of Life. Durham, NC; London: Duke University Press; 2017. ix, 220 p.Google Scholar
Baedke, J, Nieves Delgado, A. Race and nutrition in the New World: Colonial shadows in the age of epigenetics. Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences. 2019;76:101175.CrossRefGoogle ScholarPubMed
Reiches, M. Reproductive justice and the history of prenatal supplementation: Ethics, birth spacing, and the ‘Priority Infant’ model in The Gambia. Signs: Journal of Women in Culture and Society. 2019;45(1):326.CrossRefGoogle Scholar
Richardson, SS, Stevens, H. Postgenomics: Perspectives on Biology after the Genome. Durham, NC: Duke University Press; 2015. ix, 294 p.Google Scholar
Stevens, H. Networks: Representations and tools in postgenomics. In: Richardson, SS, Stevens, H, editors. Postgenomics: Perspectives on Biology after the Genome. Durham: Duke University Press; 2015. p. 0.Google Scholar
Keller, EF. The Century of the Gene. Cambridge, MA: Harvard University Press; 2000. 186 p.CrossRefGoogle Scholar
Boyle, EA, Li, YI, Pritchard, JK. An expanded view of complex traits: From polygenic to omnigenic. Cell. 2017;169(7):1177–86.CrossRefGoogle ScholarPubMed
Richardson, SS. Maternal bodies in the postgenomic order: Gender and the explanatory landscape of epigenetics. In: Richardson, SS, Stevens, H, editors. Postgenomics: Perspectives on Biology after the Genome. Durham, NC: Duke University Press; 2015. pp. 210–31.Google Scholar
Gage, SH, Munafo, MR, Davey, Smith G. Causal inference in Developmental Origins of Health and Disease (DOHaD) Research. Annual Review Psychology. 2016;67:567–85.CrossRefGoogle ScholarPubMed
Müller, R, Hanson, C, Hanson, M, Penkler, M, Samaras, G, Chiapperino, L, et al. The biosocial genome? EMBO Reports. 2017;18(10):1677–82.CrossRefGoogle ScholarPubMed
Richardson, SS, Daniels, CR, Gillman, MW, Golden, J, Kukla, R, Kuzawa, C, et al. Society: Don’t blame the mothers. Nature. 2014;512(7513):131–2.CrossRefGoogle ScholarPubMed

References

Cerdeña, J, Rivera, L, Spak, J. Intergenerational Trauma in Latinxs: A Scoping Review. Social Science & Medicine 2021; 270: 113662.CrossRefGoogle ScholarPubMed
Bombay, A, Matheson, K, Anisman, H. The Intergenerational Effects of Indian Residential Schools: Implications for the Concept of Historical Trauma. Transcultural Psychiatry 2014; 51(3): 320–38.CrossRefGoogle ScholarPubMed
Atkinson, J. Trauma Trails, Recreating Song Lines: The Transgenerational Effects of Trauma in Indigenous Australia. Australia: Spinifex Press; 2002.Google Scholar
Redvers, N, Yellow Bird, M, Quinn, D, Yunkaporta, T, Arabena, K. Molecular Decolonization: An Indigenous Microcosm Perspective of Planetary Health. International Journal of Environmental Research and Public Health 2020; 17(12): 4586.CrossRefGoogle ScholarPubMed
Scorza, P, Duarte, CS, Hipwell, AE, Posner, J, Ortin, A, Canino, G, Monk, C. Program Collaborators for Environmental influences on Child Health Outcomes. Research Review: Intergenerational Transmission of Disadvantage: Epigenetics and Parents’ Childhoods as the First Exposure. Journal of Child Psychology and Psychiatry 2019; 60(2): 119–32.CrossRefGoogle Scholar
Gone, JP, Kirmayer, LJ. Advancing Indigenous Mental Health Research: Ethical, Conceptual and Methodological Challenges. Transcultural Psychiatry 2020; 57(2): 235–49.CrossRefGoogle ScholarPubMed
Van Der Kolk, B. The Body Keeps the Score: Mind, Brain and Body in the Transformation of Trauma. 1st ed. London: Penguin Press; 2015.Google Scholar
Caruth, C. Unclaimed Experience: Trauma, Narrative and History. Baltimore: Johns Hopkins University Press; 1996.CrossRefGoogle Scholar
Cvetkovich, A. An Archive of Feelings: Trauma, Sexuality, and Lesbian Public Cultures. Durham, NC: Duke University Press; 2003.Google Scholar
Hirsch, M. The Generation of Postmemory: Writing and Visual Culture After the Holocaust. New York: Columbia University Press; 2012.Google Scholar
Warin, M, Moore, V, Zivkovic, T, Davies, M. Telescoping the Origins of Obesity to Women’s Bodies: How Gender Inequalities Are Being Squeezed Out of Barker’s Hypothesis. Annals of Human Biology 2011; 38(4): 453–60.CrossRefGoogle ScholarPubMed
Yehuda, R, Lehrner, A. Intergenerational Transmission of Trauma Effects: Putative Role of Epigenetic Mechanisms. World Psychiatry 2018; 17(3): 243–57.CrossRefGoogle ScholarPubMed
Singh, G, Morrison, J, Hoy, W. DOHaD in Indigenous Populations: DOHaD, Epigenetics, Equity and Race. Journal of Developmental Origins of Health and Disease 2019; 10(1): 6364.CrossRefGoogle ScholarPubMed
Phillips-Beck, W, Sinclair, S, Campbell, R, Star, L, Cidro, J, Wicklow, B, Guillemette, M, McGavock, M. Early-Life Origins of Disparities in Chronic Diseases among Indigenous Youth: Pathways to Recovering Health Disparities from Intergenerational Trauma. Journal of Developmental Origins of Health and Disease 2019; 10(9): 115–22.CrossRefGoogle ScholarPubMed
Lewis, AJ, Austin, E, Galbally, . Prenatal Maternal Mental Health and Fetal Growth Restriction: A Systematic Review. Journal of Developmental Origins of Health and Disease 2016; 7(4): 416–28.CrossRefGoogle ScholarPubMed
Conching, AKS, Thayer, Z. Biological Pathways for Historical Trauma to Affect Health: A Conceptual Model Focusing on Epigenetic Modifications. Social Science & Medicine 2019; 230: 7482.CrossRefGoogle Scholar
Kellerman, NP. Psychopathology in Children of Holocaust Survivors. Israel Journal of Psychiatry Related Science 2001; 38(1): 3646.Google ScholarPubMed
Clarkin, PF. The Embodiment of War: Growth, Development, and Armed Conflict. Annual Review of Anthropology 2019; 48(1): 423–42.CrossRefGoogle Scholar
Uwizeye, G, Thayer, Z, DeVon, H, McCreary, L, McDade, T, Mukamana, D, Park, C, Patil, CL, Rutherford, JN. Double Jeopardy: Young Adult Mental and Physical Health Outcomes Following Conception via Genocidal Rape during the 1994 Genocide against the Tutsi in Rwanda. Social Science & Medicine 2021; 278: 113938.CrossRefGoogle ScholarPubMed
Perroud, N, Rutembesa, E, Paoloni-Giacobino, A. The Tutsi Genocide and Transgenerational Transmission of Maternal Stress. World Journal of Biological Psychiatry 2014; 15: 334–45.CrossRefGoogle ScholarPubMed
Kuzawa, CW, Sweet, E. Epigenetics and the Embodiment of Race: Developmental Origins of US Racial Disparities in Cardiovascular Health. American Journal of Human Biology 2009; 21(1): 215.CrossRefGoogle ScholarPubMed
Grossi, E. New Avenues in Epigenetic Research on Race: Online Activism around Reparations for Slavery in the United States. Social Science Information 2020; 59(1): 93116.CrossRefGoogle Scholar
Karpin, I. Vulnerability and the Intergenerational Transmission of Psychosocial Harm. Emory Law Journal 2018; 67(6): 1115–134.Google Scholar
Leys, R. Trauma: A Genealogy. Chicago: University of Chicago Press; 2000.CrossRefGoogle Scholar
Leitch, L. Action Steps Using ACEs and Trauma-Informed Care: A Resilience Model. Health & Justice 2017; 5(1): 5.CrossRefGoogle Scholar
Müller, R, Kenney, M. A Science of Hope? Tracing Emergent Entanglements between the Biology of Early Life Adversity, Trauma-informed Care, and Restorative Justice. Science, Technology, & Human Values 2020; 46(6): 1230–260.Google Scholar
Dubois, M, Guaspare, C. From Cellular Memory to the Memory of Trauma: Social Epigenetics and Its Public Circulation. Social Science Information 2020; 59(1): 144–83.CrossRefGoogle Scholar
Atkinson, J, Nelson, J, Atkinson, C. Trauma, Transgenerational Transfer and Effects on Community Wellbeing. In: Purdie, N, Dudgeon, P, Walker, R, editors. Working Together: Aboriginal and Torres Strait Islander Mental Health and Wellbeing Principles and Practice. Australia: Telethon Institute of Child Health Research and Australian Government Department of Health and Ageing; 2010.Google Scholar
Kim, A. How Should We Study Intergenerational Trauma? Reflections on a 30-Year Birth Cohort Study in Soweto, South Africa. Somatosphere, June 16, 2020, http://somatosphere.net/2020/intergenerational-trauma-birth-cohort-study-south-africa.html/. (Accessed 30 June, 2022).Google Scholar
Painter, RC, Osmond, C, Gluckman, P, Hanson, M, Phillips, DIW, Roseboom, TJ. Transgenerational Effects of Prenatal Exposure to the Dutch Famine on Neonatal Adiposity and Health in Later Life. BJOG: An International Journal of Obstetrics & Gynaecology 2008; 115(10): 1243–249.CrossRefGoogle Scholar
Heijmans, BT, Tobi, EW, Stein, AD, Putter, H, Blauw, GW, Susser, ES, Eline Slagboom, P Lumey, PH. Persistent Epigenetic Differences Associated with Prenatal Exposure to Famine in Humans. Proceedings of the National Academy of Sciences 2008; 105(44): 17046–7049.CrossRefGoogle ScholarPubMed
Sullivan, S. Inheriting Racist Disparities in Health: Epigenetics and the Transgenerational Effects of White Racism. Critical Philosophy of Race 2013; 1(2): 190218.CrossRefGoogle Scholar
Woodhouse, R, Ashe, A. How Do Histone Modifications Contribute to Transgenerational Epigenetic Inheritance in C. elegans? Biochemical Society Transactions 2020; 48(3): 10191034CrossRefGoogle ScholarPubMed
Frolows, N, Ashe, A. Small RNAs and Chromatin in the Multigenerational Epigenetic Landscape of Caenorhabditis elegans. Philosophical Transactions of the Royal Society B 2021; 376(1826): 20200112.CrossRefGoogle ScholarPubMed
Xing, Y, Shi, S, Le, L, Lee, CA, Silver-Morse, L, Li, WX. Evidence for Transgenerational Transmission of Epigenetic Tumor Susceptibility in Drosophila. PLOS Genetics 2007; 3(9): 1598–606.CrossRefGoogle ScholarPubMed
Ciabrelli, F. Transgenerational Epigenetic Inheritance: A Drosophila Tale. Heredity Genetics Current Research, 4th International Congress on Epigenetics and Chromatin, 2018; 7.Google Scholar
Remnant, EJ, Ashe, A, Young, PE, Buchmann, G, Beekman, M, Allsopp, M, Suter, CM, Drewell, R, Oldroyd, BP. Parent-of-Origin Effects on Genome-Wide DNA Methylation in the Cape Honey Bee (Apis mellifera capensis) May Be Confounded by Allele-Specific Methylation. BMC Genomics 2016; 17: 226.CrossRefGoogle ScholarPubMed
Horsthemke, B. A Critical View on Transgenerational Epigenetic Inheritance in Humans. Nature Communications 2018; 9: 2937.CrossRefGoogle ScholarPubMed
Miska, EA, Ferguson-Smith, AC. Transgenerational Inheritance: Models and Mechanisms of Non-DNA Sequence-based Inheritance. Science 2016; 354: 5963.CrossRefGoogle ScholarPubMed
Gapp, K, Jawaid, A, Sarkies, P, Bohacek, J, Pelczar, P, Prados, J, Farinelli, L, Miska, E, Mansuy, IM. Implication of Sperm RNAs in Transgenerational Inheritance of the Effects of Early Trauma in Mice. Nature Neuroscience 2014; 17: 667–69.CrossRefGoogle ScholarPubMed
Mendenhall, E, Kim, AW. How to Fail a Scale: Reflections on a Failed Attempt to Assess Resilience. Culture, Medicine, and Psychiatry 2019; 43(2): 315–25.CrossRefGoogle ScholarPubMed
Thunderbird Partnership Foundation. Indigenous Knowledge & Epigenetics. AFN Mental Wellness Forum 2019.Google Scholar
Gilbert, S. Ways of Seeing: An Insight into Aboriginality. 2017. www.newcastle.edu.au/profile/stephanie-gilbert (Accessed 30 January 2022).Google Scholar
Pentecost, M. The Politics of Trauma: Gender, Futurity, and Violence Prevention in South Africa. Medical Anthropology Quarterly 2021; 35(4): 441–57.CrossRefGoogle ScholarPubMed
Watego, C. 30 July 2020 tweet. Accessed 15 February 2022. https://twitter.com/drcwatego/status/1288674559852294145Google Scholar
Lappé, M. Epigenetics, Media Coverage and Parent Responsibilities in the Post-Genomic Era. Current Genetic Medicine Reports 2016; 4(3): 9297.CrossRefGoogle ScholarPubMed
Warin, M, Zivkovic, T, Davies, M, Moore, V. Mothers as Smoking Guns: Fetal Overnutrition and the Reproduction of Obesity. Feminism and Psychology 2012; 22(3): 360–75.CrossRefGoogle Scholar
Richardson, S, Daniels, C, Gillman, M, Golden, J, Kukla, R, Kuzawa, C, Rich-Edwards, J. Don’t Blame the Mothers. Nature 2014; 512: 131–32.CrossRefGoogle ScholarPubMed

References

Lock, M. The Epigenome and Nature/Nurture Reunification: A Challenge for Anthropology. Medical Anthropology. 2013;32:291308.CrossRefGoogle ScholarPubMed
Landecker, H, Panofsky, A. From Social Structure to Gene Regulation, and Back: A Critical Introduction to Environmental Epigenetics for Sociology. Annual Review of Sociology. 2013;39:333–57.CrossRefGoogle Scholar
Niewohner, J. Epigenetics: Embedded Bodies and the Molecularisation of Biography and Milieu. BioSocieties. 2011;6:279–98.CrossRefGoogle Scholar
Meloni, M. How Biology Became Social, and What It Means for Social Theory. The Sociological Review. 2014;62(3):593614.CrossRefGoogle Scholar
Jablonka, E, Lamb, MJ. Evolution in Four Dimensions: Genetic, Epigenetic, Behavioral, and Symbolic Variation in the History of Life. Cambridge, MA: MIT Press; 2005.Google Scholar
Lamoreaux, J. Reproducing Toxicity. Environmental History. 2021 Jul;26(3):437–43.CrossRefGoogle Scholar
Mansfield, B. Race and the New Epigenetic Biopolitics of Environmental Health. BioSocieties. 2012;7(4):352–72.CrossRefGoogle Scholar
Paxson, H, Helmreich, S. The Perils and Promises of Microbial Abundance: Novel Natures and Model Ecosystems, from Artisanal Cheese to Alien Seas. Social Studies of Science. 2014;44(2):165–93.CrossRefGoogle ScholarPubMed
Pentecost, M. The New Trial Communities: Challenges and Opportunities in Preconception Cohorts [Internet]. Somatosphere. 2021 [cited 9 Nov 2021]. Available from: http://somatosphere.net/2021/birth-cohort-studies-new-communites-pentecost.html/Google Scholar
Valdez, N. Weighing the Future: Race, Science, and Pregnancy Trials in the Postgenomic Era. First ed. Oakland: University of California Press; 2021. 284 p.Google Scholar
Krieger, N, Davey, Smith G. The Tale Wagged by the DAG: Broadening the Scope of Causal Inference and Explanation for Epidemiology. International Journal of Epidemiology. 2016 1 Dec;45(6):1787–808.Google ScholarPubMed
Zamora, AN, Arboleda-Merino, L, Tellez-Rojo, MM, O’Brien, LM, Torres-Olascoaga, LA, Peterson, KE, et al. Sleep Difficulties among Mexican Adolescents: Subjective and Objective Assessments of Sleep. Behaviour Sleep Medicine. 2021 13 May;2:121.Google Scholar
Chung, S, Wilson, KE, Miller, AL, Johnson, D, Lumeng, JC, Chervin, RD. Home Sleeping Conditions and Sleep Quality in Low-Income Preschool Children. Sleeping Medical Research. 2014 30 Jun;5(1):2932.CrossRefGoogle Scholar
Perng, W, Tamayo-Ortiz, M, Tang, L, Sánchez, BN, Cantoral, A, Meeker, JD, et al. Early Life Exposure in Mexico to ENvironmental Toxicants (ELEMENT) Project. BMJ Open. 2019 1 Aug;9(8):e030427.CrossRefGoogle ScholarPubMed
Goodrich, JM, Dolinoy, D, Sanhez, B, Zang, ZZ, Mercado-Garcia, A, Solano-Gonzalez, M, et al. Adolescent Epigenetic Profiles and Environmental Exposures from Early Life through Peri-adolescence. Environmental Epigenetics. 2016;2(3). https://academic.oup.com/eep/article/2/3/dvw018/2415066CrossRefGoogle ScholarPubMed
Roberts, EFS, Sanz, C. Bioethnography: A How To Guide for the Twenty-First Century. In: Meloni, M, editor. A Handbook of Biology and Society. London: Palgrave Macmillan; 2017.Google Scholar
Diez-Roux, AV. Multilevel Analysis in Public Health Research. Annual Review in Public Health. 2000;21:171–92.CrossRefGoogle ScholarPubMed
Cantoral, A, Téllez-Rojo, MM, Ettinger, AS, Hu, H, Hernández-Ávila, M, Peterson, K. Early Introduction and Cumulative Consumption of Sugar-sweetened Beverages during the Pre-school Period and Risk of Obesity at 8–14 Years of Age. Pediatric Obesity. 2016 Feb;11(1):6874.CrossRefGoogle ScholarPubMed
Jansen, EC, Zhou, L, Perng, W, Song, PX, Rojo, MMT, Mercado, A, et al. Vegetables and Lean Proteins-Based and Processed Meats and Refined Grains-Based Dietary Patterns in Early Childhood Are Associated with Pubertal Timing in a Sex-Specific Manner: A Prospective Study of Children from Mexico City. Nutritional Research. 2018 Aug;56:4150.CrossRefGoogle Scholar
Mulcahy, MC, Tellez-Rojo, MM, Cantoral, A, Solano-González, M, Baylin, A, Bridges, D, et al. Maternal Carbohydrate Intake during Pregnancy Is Associated with Child Peripubertal Markers of Metabolic Health But Not Adiposity. Public Health Nutrition. 2021 24 Nov;9:113.Google Scholar
Wu, Y, Sánchez, BN, Goodrich, JM, Dolinoy, DC, Cantoral, A, Mercado-Garcia, A, et al. Dietary Exposures, Epigenetics and Pubertal Tempo. Environmental Epigenetics. 2019 Jan;5(1):dvz002.CrossRefGoogle ScholarPubMed
Carsten, J. The Substance of Kinship and the Heat of the Hearth: Feeding, Personhood, and Relatedness among Malays in Pulau Langkawi. American Ethnologist. 1995;22(2):223–41.CrossRefGoogle Scholar
Weismantel, M. Making Kin: Kinship Theory and Zumbagua Adoptions. American Ethnologist. 1995;22(4):685704.CrossRefGoogle Scholar
Carney, MA. The Unending Hunger: Tracing Women and Food Insecurity Across Borders. Oakland: University of California Press; 2015. 272 p.CrossRefGoogle Scholar
Fielding-Singh, P. How the Other Half Eats: The Untold Story of Food and Inequality in America. New York: Little, Brown Spark; 2021. 352 p.Google Scholar
Kulick, D, Meneley, A. Fat: The Anthropology of an Obsession. New York: Jeremy P. Tarcher/Penguin; 2005. p. 246 p.Google Scholar
Yates-Doerr, E. The Weight of Obesity Hunger and Global Health in Postwar Guatemala. Oakland: University of California Press; 2015.CrossRefGoogle Scholar
Roberts, EFS. Food is Love: And So, What Then? BioSocieties. 2015;10:247–52.CrossRefGoogle Scholar
Berrigan, D, Arteaga, SS, Colón-Ramos, U, Rosas, LG, Monge-Rojas, R, O’Connor, TM, et al. Measurement Challenges for Childhood Obesity Research Within and Between Latin America and the United States. Obesity Review. 2021 Jun;22(Suppl 3):e13242.CrossRefGoogle ScholarPubMed
Delgado, S. México, primer consumidor de refrescos en el mundo [Internet]. Gaceta UNAM. 2019 [cited 16 Dec 2022]. Available from: www.gaceta.unam.mx/mexico-primer-consumidor/Google Scholar
Jansen, E, Marcovitch, H, Wolfson, J, Leighton, M, Peterson, K, Téllez-Rojo, M, et al. An Analysis of Dietary Patterns in a Mexican Adolescent Population: A Mixed Methods Approach. Appetites. 2020;CrossRefGoogle Scholar
Téllez-Rojo, MM, Trejo-Valdivia, B, Roberts, E, Muñoz-Rocha, TV, Bautista-Arredondo, LF, Peterson, KE, et al. Influence of Post-Partum BMI Change on Childhood Obesity and Energy Intake. PLOS ONE. 2019 Dec 12;14(12):e0224830.CrossRefGoogle ScholarPubMed
Gálvez, A. Eating NAFTA: Trade, Food Policies, and the Destruction of Mexico. 1st ed. Oakland: University of California Press; 2018. 288 p.CrossRefGoogle Scholar
Vaughan, M, Adjaye-Gbewonyo, K, Mika, M, editors. Epidemiological Change and Chronic Disease in Sub-Saharan Africa: Social and Historical Perspectives. London: UCL Press; 2021. 378 p.CrossRefGoogle Scholar
Espinosa-Garcia, AC, Diaz-Avalos, C, Villarreal, FG, Malvaez-Orozco, RVS, Mazari-Hiriart, M. Drinking Water Quality in a Mexico City University Community: Perception and Preferences. EcoHealth. 2015;12:8897.CrossRefGoogle Scholar
Martinez Paz, EF, Tobias, M, Escobar, E, Raskin, L, Roberts, EFS, Wigginton, KR, et al. Wireless Sensors for Measuring Drinking Water Quality in Building Plumbing: Deployments and Insights from Continuous and Intermittent Water Supply Systems. ACS EST Eng. 24 Oct 2021;acsestengg.1c00259.CrossRefGoogle Scholar
Roberts, EFS. Making Better Numbers Through Bioethnographic Collaboration. American Anthropologis. 2021;123(2):355–59.CrossRefGoogle Scholar
Clark, J, Martin, E, Bulka, CM, Smeester, L, Santos, HP, O’Shea, TM, et al. Associations between Placental CpG Methylation of Metastable Epialleles and Childhood Body Mass Index Across Ages One, Two and Ten in the Extremely Low Gestational Age Newborns (ELGAN) Cohort. Epigenetics. 2019 Nov;14(11):1102–11.CrossRefGoogle ScholarPubMed
Strohmaier, S, Bogl, LH, Eliassen, AH, Massa, J, Field, AE, Chavarro, JE, et al. Maternal Healthful Dietary Patterns During Peripregnancy and Long-Term Overweight Risk in Their Offspring. European Journal of Epidemiology. 2020;35(3):283–93.CrossRefGoogle ScholarPubMed
Leighton, M, Roberts, E. Trust and Distrust in Multi-disciplinary Collaboration: Some Feminist Reflections. Catalyst: Catalyst: Feminism, Theory, Technoscience [Internet]. 2020;6(2):127. Available from: https://catalystjournal.org/index.php/catalyst/article/view/32956/26855Google Scholar
Figure 0

Figure 13.1 ‘Overview of potential maternal prenatal stressors during the current COVID-19 pandemic as part of the early life course medicine’.

Source: Schoenmakers et al. [42]

Save book to Kindle

To save this book to your Kindle, first ensure [email protected] is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

Available formats
×