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Framing Complexity in Environmental and Human Health

Summary and Keywords

Framing and dealing with complexity are crucially important in environment and human health science, policy, and practice. Complexity is a key feature of most environment and human health issues, which by definition include aspects of the environment and human health, both of which constitute complex phenomena. The number and range of factors that may play a role in an environment and human health issue are enormous, and the issues have a multitude of characteristics and consequences. Framing this complexity is crucial because it will involve key decisions about what to take into account when addressing environment and human health issues and how to deal with them. This is not merely a technical process of scientific framing, but also a methodological decision-making process with both scientific and societal implications. In general, the benefits and risks related to such issues cannot be generalized or objectified, and will be distributed unevenly, resulting in health and environmental inequalities. Even more generally, framing is crucial because it reflects cultural factors and historical contingencies, perceptions and mindsets, political processes, and associated values and worldviews. Framing is at the core of how we as humans relate to, and deal with, environment and human health, as scientists, policymakers, and practitioners, with models, policies, or actions.

Keywords: environment, human health, integrative frameworks, quality, framing

Introduction

Framing the complexity in human and nonhuman health, in the environment of organisms and in their mutual relations, and extending to the social sphere, is crucial because it involves key decisions about what to take into account when addressing environmental health issues and how to deal with them. Thus, framing is needed both for understanding and for acting. This is not only a technical process of scientific framing, such as in choosing model boundaries or focusing experiments, but also a more general methodological decision-making process with both scientific and societal implications. Mostly the benefits and risks related to environment and human health cannot be generalized or objectified and will be distributed unevenly, resulting in health inequalities (Brulle & Pellow, 2006). Even more generally, framing is crucial because it reflects and incorporates cultural factors and historical contingencies, perceptions and mindsets, political processes, and associated values and worldviews, as shown by Dake (1991) and Douglas (1996) regarding the cultural theory of risks (cf. Assmuth, Benighaus, Craye, Hildén, & Lyytimäki, 2009). Framing is at the core of how we as humans relate to, and deal with, environmental health, as scientists, policymakers, and practitioners, with models, policies, or actions.

An important property of complexity is emergence (Cilliers, 2005a): the presence of a great number of (often simple) system components that interact in a manner that cannot be explained by the characteristics of the individual components. Another important feature of complexity is nonlinearity (Cilliers, 2005a): due to partly nonlinear input−output functions, complex systems will show unpredictable behavior. Furthermore, complexity is characterized by temporality (Cilliers, 2006): complex systems echo their history and their memory of the past in the present and the future, although in a selective and nonlinear manner. Finally, there is the problematic issue of reduction (Cilliers, 2005a): any knowledge we have about a complex system is a reduction of its complexity. In order to come to terms with complexity, an evaluative and “translational” (explanatory and communicative) approach is needed, proceeding from framing to managing complexity and adapting to it. This requires embracing complexity and the associated uncertainty and ambiguity (for example, regarding health states, causes, effects and therapies), while complexity is also being reduced by the simplification appropriate to the particular situation, context, and purpose. This evaluative and active approach is important especially when dealing with increased and higher-order complexity in “wicked problems” (Kreuter, De Rosa, Howze, & Baldwin, 2004), such as far-reaching and value-laden issues in environmental management, public health, and health care.

This article illustrates environment and human health complexity with some examples, including health risks posed by environmental pollution, natural phenomena, and environmental and health management or governance, as well as the interplay among them. Importantly, these examples also include health benefits and opportunities arising from the “living environment,” particularly the natural environment.

The framing of complexity in environment and human health is analyzed by introducing some integrative frameworks that play, or may play, a prominent role in the broad field of environment and human health. These include Integrated Environmental Health Impact Assessment, Integrated Risk−Benefit Analysis, EcoHealth, One Health, and Nature’s Benefits to People. Related developments in policy integration, such as Health in All Policies (HiAP), and corresponding efforts to integrate and to mainstream environmental policy and practice, are also discussed briefly. There is also discussion of nontraditional and nonregulatory approaches to environment and human health, such as community-based and individual bottom-up and experimental approaches, identifying their strengths and weaknesses in dealing with complexity, and specifically their knowledge aspects.

The article more generally discusses approaches to complexity, highlighting some key differences among different approaches. Key ontological (concepts), epistemological (methods), and ethical (and political) principles and issues are outlined. The article interrogates how general complexity approaches can be conceived within environment and human health by introducing and commenting on some examples of practical approaches to dealing with environment and human health issues.

To properly address the above themes and to translate them into strategies for research, and more broadly for knowledge co-generation and use processes, the article concludes with a synthesizing discussion of the quality of knowledge. The term quality in this context is conceived broadly, and includes whether knowledge is fit for purpose, actionable, meaningful, and socially accepted.

Examples of Environment and Human Health Complexity

General Considerations

Complexity in environment and human health can be examined from different points of view. The points of view grasp complexity from different directions and complement each other. Examples discussed include health determinants, and specifically adverse and beneficial agents, as well as health outcomes (or conditions), such as obesity. Addressing complexity is essentially about models of causality and their limitations due to the multiple, intertwined, variable, and ambiguous processes involved. In confronting this complexity, various levels from biomedical to sociocultural are involved. By focusing on the quality, attainability, and meaning of knowledge, it can be shown that, even with improved information (e.g., from mechanistic models, accounts of variability, and corresponding specifications of the causal processes), complexity and the associated uncertainties and ambiguities challenge traditional notions and ideals of evidence-based care and generally “intervention” (which includes actions to enable care) within its social contexts. Finally, alternative avenues and complementary approaches embracing and making use of the inherent high-order complexities in the examples are identified.

Cocktail and Knock-On Effects of a Multitude of Agents and Cofactors on Health

The “Bad”

The study of the so-called “cocktail effects” of several pollutants (i.e., mixture toxicology) is an important example of the growing complexity in the field of environment and human health: environment and health issues are no longer reduced to single pollutants and their individual potential or observable health and environmental (or ecosystem) effects. This was not always the case: previously, pollutant-related health research was mainly focused on single pollutants, even as the interpretation of the research always faced the question of other possible causative and contributing factors (e.g., other pollutants, biological agents such as infections, individual vulnerabilities due, e.g., to a disease, population vulnerabilities, demographic factors, genetic factors, lifestyle factors, etc.), which often substantially decreased the explanatory power of the single-substance and single-effect studies. To the extent that multiple-substance studies were performed, additivity was usually assumed. Exceptions to this paradigm were rare (e.g., in the utilization of insights and tools from pharmacology, where mixture effects were traditionally a concern). Thus, the notion of the cocktail effects of mixed exposures developed. Although cocktail effects were originally applied to chemicals, it should be noted that such complexity extends to physical agents (e.g., noise, light, pollution) and biological agents (e.g., pathogens and parasites), as well as intermediates or hybrids (e.g., radionuclides, endotoxins), and it is shaped by cofactors in the affected organisms, including hereditary, nutritional, and lifestyle factors, and in their environment.

Recent insights show that cocktails of environmental pollutants have dynamic effects surpassing the additive effect levels of single pollutants: they may result in stronger combined health effects than would be expected when simply adding the single-pollutant effects (Kortenkamp, Backhaus, & Faust, 2009). Graillot et al. (2012) showed a combined genotoxic effect of pesticide mixtures at low concentrations, with a significantly higher effect of the mixture than would be expected from responses to the individual compounds. In some cases, as part of the dynamics, the effects of substances can be increased by subsequent, delayed, even intergenerational “knock-on” contributions from other exposures; in other cases, a critical window in the timing of the exposure can boost cocktail effects (Assmuth, Hildén, & Craye, 2010b). In still other cases, attenuation of the combined effect may take place, as when synergistic competition of the key agents dominates, or when inhibiting factors reduce exposures at target sites of action. The chain of events from exposure, including the internal effects (i.e., toxicokinetics), to the multiple stages of effects from internal doses (i.e., toxicodynamics) provides opportunities for unexpectedly high as well as unexpectedly low combined toxicity, such as through synergy in the former case and hormesis in the latter (i.e., the phenomenon that low doses of a toxicant may amount to beneficial effects; see Calabrese, 2004) and other nonmonotonic dose−response curves.

In response to such complexity, several approaches have evolved: the consideration of the specific modes of action of the chemicals in the cocktail and their corresponding quantitative dose−response functions; broad-spectrum test batteries for multiple agents and effects; and generally observation and modeling of multifactorial and multi-attribute effects. But all the approaches have limitations and problems, and therefore many challenges remain, including combined effects on particular potentially vulnerable groups, such as children (Vrijheid, Casas, Gascon, Valvi, & Nieuwenhuijsen, 2016).

This means that knowledge of both environmental and human health effects of individual pollutants and their behavior in organisms and the environment does not suffice as a basis for evidence-based policymaking. We can no longer conclude that safety is ensured when individual levels of pollutants are below specific individual thresholds that are believed to be safe, even when the agents’ modes of action are known to support inferences regarding the key agents and their combined effects.

The “Good”

Considerable research has been done and continues to be done on the linkages between experience of the natural environment and benefits for health (Bowler, Buyung-Ali, Knight, & Pullin, 2010; Gascon et al., 2016; Hartig, Mitchell, Vries, & Frumkin, 2014; Jackson, Daniel, McCorkle, Sears, & Bush, 2013; James, Banay, Hart, & Laden, 2015; Kuo, 2015; Lee & Maheswaran, 2011; Oosterbroek, de Kraker, Huynen, & Martens, 2016; Sandifer, Sutton-Grier, & Ward, 2015; Völker & Kistemann, 2011; Wheeler, White, Stahl-Timmins, & Depledge, 2012). Many of the findings are only associations or correlations in terms of evidence, statistically correlating improved health condition with experience of, and exposure to, nature or physical or virtual environmental elements that come close to nature (e.g., urban parks, botanical gardens, allotments, and playgrounds).

Many challenges still remain, including the limited number, size, representativeness, and specificity of the studies. Regarding specificity, the measures of both experience and effects have often been approximate, and the groups and settings studied have varied. Therefore, systematic reviews of the research (Lovell, Wheeler, Higgins, Irvine, & Depledge, 2014; van den Berg et al., 2015) have arrived at different conclusions about the direction and strength of association, due partly to different criteria for the inclusion/exclusion of studies, and have identified research gaps in this area. A prominent challenge is to explain the mechanism or mechanisms (there may be several, including various somatic and mental processes) behind an association or relation between human health and well-being (physical and mental) and exposure to the natural environment. According to Hartig et al. (2014), several candidate mechanisms or pathways may play a prominent role (see Figure 1).

Framing Complexity in Environmental and Human HealthClick to view larger

Figure 1. Several pathways for health benefits from nature (Hartig et al., 2014).

A potential pathway that was not explicitly incorporated in the study by Hartig et al. (2014)—and certainly not in a central position—is the immune system. Kuo (2015) regarded the immune system as crucial: apart from the role of the immune system, Kuo’s model (Figure 2) shows clear resemblance to the model developed by Hartig et al. (2014). The importance of exposure to natural environments for the development of immune competence has been hypothesized for some time, partly as an outgrowth of the realization that infections and other environmental challenges are vital to this development. In particular, as a version of the general so-called “biodiversity hypothesis of health” (Haahtela et al., 2013), the role of varied and well-functioning microflora around, on, and in humans (in the gut) has been emphasized and studied. There is increasing evidence (mechanistic, ecological, and epidemiological) of the importance and variations of the microbiome’s role; however, its exact nature, power, variations, and determinants remain unclear, and therefore information about interventions is similarly undetermined (Ruokolainen et al., 2017).

Framing Complexity in Environmental and Human HealthClick to view larger

Figure 2. Immune function as a central pathway for health benefits from nature (Kuo, 2015).

This shows how the same complex relationship can be framed and represented in similar models but with different premises regarding pathways. This does not mean that the models are in conflict; instead, they appear complementary and illustrative of complexity. What both models have in common is that, even if individual pathways have a limited beneficial effect on health, the cumulative cocktail effect can be quite substantial. However, as with the negative health outcomes of cumulative stressors, the compounded positive effect may alternatively, or also, be blocked, attenuated, or delayed by factors that work in the opposite direction, diminishing beneficial outcomes to health and well-being. The attenuating factors may be related to the beneficial factor or they may be unrelated. In either case, they can be difficult to distinguish, to foresee, and to establish. This is a key aspect of complexity: it increases and qualitatively alters the uncertainty of the basis, workings, and impacts of systems. Therefore, it inherently involves the possibility of “false negatives” and “false positives,” and thus also of negative and positive outcomes in decision models based on such expectations regarding the system under consideration. This is a general property of complex systems, yet it needs to be understood what specific obstacles and opportunities to unravel and deal with the multiplicity of outcomes and causes exist with regard to human health and the environment. These obstacles and opportunities pertain, for example, to the multitude of stressors and co-factors, to the multi-dimensionality and ambiguous valuations of outcomes, to the constrains on controlled trials, and to the alternative options for solving problems proactively, starting from decisions and interventions to better manage the complexity.

The Example of the Apparent Simplicity of Obesity Challenges

What might from a distance seem a relatively simple health concern, obesity, is clearly far from simple when studied more closely, especially from a problem-solving perspective: addressing obesity goes far beyond prescribing a healthy diet and sufficient physical exercise, as is shown in Figure 3.

Framing Complexity in Environmental and Human HealthClick to view larger

Figure 3. Obesity system map (Vandenbroeck et al., 2007).

Clearly a variety of factors are at play, and a substantial number of them are environmental, particularly when obesity is framed from a systems perspective and not merely as an individual issue. A systems approach is also needed for areas only partly associated with environmental factors, such as nutrition, and for the societal influences on obesity and potential approaches to it.

Several reviews have proposed the need for a more systemic approach. Frood, Johnston, Matteson, and Finegood (2013) pointed out how primary care practices are challenged by the complexity of obesity because they are structured to address simple or less complicated conditions. Frood et al. showed that, while individual behavior change is at the center of obesity management, an effective healthcare team is essential to ensuring that individuals receive the support, advice, and guidance they need to improve their health status. In addition, still broader support from family and community may be essential, taking the issue beyond the medical profession. Clarke et al. (2016) stress the need for a political science theory perspective to obtain a better view of the complexity of policymaking and the multiple influences on obesity prevention policy processes, in order to better guide policymakers as to potential leverage points and effective ways to influence obesity prevention policy. In their review, Cauchi, Glonti, Petticrew, and Knai (2016) show that research on childhood obesity seems to focus on schools as key sites for childhood and adolescent obesity prevention interventions. However, interventions in schools that were initially successful in reducing obesity have been shown to lose their effect over the summer break and are often difficult to sustain among the pediatric population in the long run. Taken together, these perspectives on obesity indicate its increasing complexity as qualitatively different emergent layers are added when the focus is extended from the biomedical to the sociocultural realms and from the individual to the community and policy level. Addressing obesity requires consideration of social processes and factors, as in more general terms in the case of risks (Luhmann, 2005), and the political processes in governing them.

The Example of Biodiversity and Infectious Disease Control

The relationship between biodiversity and infectious diseases is not straightforward; disease dynamics are complex and dependent on the system, which includes the infectious agents, their targets and hosts, their vectors, the environment (natural as well as technological and sociocultural), and the mechanisms and interactions connecting them. The variation and diversity in the different components/factors are key contributors to the complexity. It must be stressed that biodiversity, although important, is only one structural aspect of the ecosystem where agents and hosts reside and interact; therefore, its importance can be overrated or it can function as a symbol of more general ecological concerns. Furthermore, in addition to its structural aspects, the functions of the system influence infections and responses to them, and in both the structure and the function of ecosystems, abiotic as well as biotic components and processes are important.

Biodiversity may reduce the risk of infectious disease emergence or spread (this termed the dilution effect), while its loss or unsustainable exploitation can increase disease transmission (Keesing et al., 2010). Land use change and ecosystem disruption are widely recognized as drivers of infectious disease emergence. Furthermore, areas of naturally high biodiversity may serve as a source pool for emerging pathogens. The emergence of certain pathogens and their spread from wildlife to livestock and/or humans, along with related social and economic costs, have been well documented (see World Health Organization and Secretariat of the Convention on Biological Diversity, 2015). Examples include HIV, hantavirus, avian influenza, Lyme disease, malaria, dengue fever, leishmaniasis, Nipah virus, and Ebola. Hence, high biodiversity does not necessarily reduce disease risk.

Morand and Lajaunie (2017) illustrated how the complexity of the relationship between infectious disease and the environment was already understood during colonial times (Figure 4).

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Figure 4. The colonial scientific network of environmental management. Referred to in Morand and Lajaunie (2017).

Among Asia-Pacific countries, it has been shown that the prevalence of infectious diseases is positively correlated with the diversity of birds and mammals (Morand, Jittapalapong, Suputtamongkol, Abdullah, & Huan, 2014). However, the number of outbreaks of zoonotic diseases is positively correlated with the number of threatened mammal and bird species, and the number of outbreaks of vector-borne diseases is negatively correlated with forest cover. It appears that biodiversity is a source of pathogens, but that the loss of biodiversity, as measured by the amount of forest cover or the number of threatened species, seems to be associated with an increase in outbreaks of zoonotic and vector-borne diseases (Morand et al., 2014).

When the focus moves from the ecological to the social-ecological, many additional factors and levels of complexity emerge. The interactions of the ecosystem with humans both as biological agents and as social actors (within economic and political systems) radically alter the basic dynamics of infectious diseases, because humans are animals, part of the ecosystem and subject to natural factors, but they are also subject to society and culture. Furthermore, because humans reinvent themselves and their world through somewhat systematic (yet also erratic) information transmission and through technology (notably in health care), they are shaped much more by cultural evolution than by biological evolution. The sociocultural, economic, and political factors involved add so many levels of complexity that the ability to explain and predict is essentially limited: natural phenomena, even in complex and emergent systems (such as in ecosystems), nevertheless at least on some levels and to significant degrees obey some tractable laws. This is evident in pandemics (such as the bubonic plague), which are shaped by complex and highly dynamic spatiotemporal and social-ecological factors, where the complexity of the species involved (in the plague example, Yersinia pestis, fleas, rats, and humans) is greatly surpassed by the complexity of the social-ecological processes and factors (such as trade, wars, belief systems, and healthcare practices).

The Challenges of Statistical Proof and Mechanistic Understanding

As Matthews (2000) showed, although one can derive a highly statistically significant association between stork populations and human birth rates across Europe, the statistical association does not constitute scientific proof that storks deliver babies. A statistical association does not demonstrate causality when there is no mechanistic proof of the case. And, vice versa, a mechanistic explanation does not necessarily mean that the case can be easily supported by statistical proof. Furthermore, neither statistical association nor mechanistic proof necessarily has the capability to inform or otherwise contribute to health promotion in practice.

The limits of statistical association and mechanistic explanations (even in combination), especially in complex phenomena and relationships, such as multifactorial and multi-attribute health conditions and states, have prompted the search for other and more powerful strategies of explanation and prediction. In environmental and general epidemiology, an important strategy employs etiological criteria (based on Koch’s postulates) and their subsequent extended and refined versions that address the strength and direction and, importantly, the temporal sequence of association. Furthermore, improved metrics of exposure and effect, as well as measurement precision, are key to reducing measurement bias (Grandjean, 2015; Grandjean & Budtz-Jørgensen, 2010). To improve the plausibility of generalization from surrogate systems, such as animal models of a disease/health state, the mechanisms in the organisms and systems in question must be elucidated. This enterprise can be aided by integrating information from comparative biology and biochemistry (“omics” research and bioinformatics on higher levels of organization, such as population genetics).

Nevertheless, observational studies, especially of complex processes and phenomena in environment and human health, present specific difficulties for explanation and prediction. Observational studies, even well-designed, long-term follow-up studies of large and representative cohorts, are limited in their ability to provide proof despite the use of specific metrics corresponding to detailed mechanistic models and pooling of the information at all stages of the health-impairing or health-promoting processes, such as in “exposome” studies (for a review of this extended and integrative concept, see Wild, 2012).

Observational studies of health states, studies based on self-reported health and their syntheses, may be supported by clinical studies if controlled experiments can be done at the target population level or generally by intervention studies. Often, the resolution of complexity requires prospective cohort studies in large populations instead of cross-sectional studies (also in large populations). Even so, the variability and complexity of conditions, causes, and processes pose great difficulties for scientific explanation and prediction. Moreover, in environment and human health, a high level of control is often not attainable, and instead approximate natural experiments need to be resorted to and to be complemented by supportive information.

Importantly, intervention studies also introduce other challenges, statistical and otherwise, due to the complexities of human systems. This is particularly true for psychological and societal interventions, which inherently make it difficult to discern causality and reduce repeatability in these interventions, and thus generally reduce the certainty of explanation and prediction. This is due largely to the multi-dimensionality of phenomena in the socio-cultural sphere, and specifically to their subjective and value-laden elements that defy the very notion of objective proof. This invites other strategies of understanding, such as combining observation and explanation with precautionary (Harremoës et al., 2002) as well as experimental approaches (which are also tentative and open-ended) and turning the complex and unpredictable mental and social processes into allies in developing sensible, socially and culturally acceptable means of health promotion, including health promotion combined with the pursuit of other goals and benefits, such as environmental protection and care (Antonovsky, 1996).

A Turn to Statistical Rigor or to Precaution?

Although space limitations preclude detailed discussion of statistical techniques, models, and reasoning, to give the flavor of relevant debates, two perspectives are briefly presented. First, Horton (2015) discussed the danger of a lack of statistical rigor, as when statistical significance is too readily concluded in order to satisfy an investigator’s hunger for results and publications. This is related to publication bias, notably in medicine, and the propensity to claim effects (harmful and beneficial) even when they are not clearly demonstrated, which is obviously an example of bad scientific practice in response to the pressures of productivity (and authority and prestige) in terms of quantity (publications) not quality.

Second, Grandjean (2005, 2008) discussed what could be called the other side of the statistical split in the world of health-related science: this side, the precautionary side, is not as invested in questioning statistical rigor in general as it is interested in questioning the level of information needed to underpin statistical evidence and inference considering the complexity of environment and human health issues. Laboratory and clinical standards for statistical significance are useful as guidelines but are often not realistic as such for environment and human health issues, where one cannot easily reduce complexity without doing harm to the essence of the issues. Grandjean was especially critical of environmental health science from a problem-solving perspective: due to complexities, traditional science is not fit to tackle environment and human health problems:

Risk assessment must become less reductionist and less focused on obtaining complete information on all aspects of individual hazards. Statistical acceptance of the null hypothesis should never be interpreted as proof of safety. . . . Given that decisions will involve stakeholders, risk perception should receive increased attention as a crucial aspect that is not dependent on a formalized scheme of evaluation.

According to Grandjean, standard scientific approaches do not fully fit environment and human health issues, either in focus and methods (too much focus on simplified models and the single effects of single hazards) or in interpretation (overly strict analytical standards). Grandjean stressed the need for a different scientific approach and application in the policy practice of a precautionary principle. Other examples in support of the “better safe than sorry” precautionary turn can be found in the work of Gee (2008) and Harremoës et al. (2002).

However, precaution incurs considerable problems and dangers if exaggerated and applied in a one-sided manner. At worst, giving up the attempt to obtain scientific evidence may result in superstition and fear-mongering (or “hope-selling”), where any claim is justified, leading to the abandonment of well-tried criteria of care. This can lead, and frequently does lead (e.g., in the media), to indiscriminate panic and to the cherry-picking of arguments against certain products, technologies, or solutions, while others may be all too easily accepted, especially if they are styled as safe alternatives to those that are feared (cf. Douglas, 1996; Douglas & Wildavsky, 1983).

It should be understood that precaution, both as a general principle in risk governance and as an operational dictum (e.g., in preventive care), cuts two ways: it should also be applied to proposed alternatives, and ideally to address at some level also the nondescript escape from a risk without offering a real alternative. Many risks also incur rewards; thus, reducing risk can cause a loss of benefit. Furthermore, one risk often increases another risk. Both of these cases necessitate trade-offs. In most cases, unintended and even unexpected consequences and countervailing “backlash” risks of management need to be factored in at some level. Although lessons can be, and need to be, learned from previous mistakes, it is difficult to anticipate which risks of new products will materialize and which will not. It is also difficult to identify the decisive factors that determine this, even with the benefit of hindsight, and thus to distinguish “false alarms” from “true warnings” (Mazur, 2004). Instructive examples in environmental health include the substitution of one harmful substance for another: in gasoline, lead was replaced with MTBE (methyl tert-butyl ether); solvents were switched from flammable directly oil-based agents to chlorinated compounds; and in fire retardants, chlorinated (and other halogenated) compounds were replaced by nonhalogenated compounds. Although the examples cited were motivated by changed values about environmental impacts (as well as effects on health), a definite benefit was elusive, as side effects of the new, purportedly “green,” and healthier alternatives emerged. Thus, adaptive risk management requires learning as well as communication and negotiation about goals and means, especially when dealing with complex issues, such as those encompassing both human health and other valued entities, involving many sectors and levels of governance, and involving uncertainties and ambiguities. Fortunately, adaptive risk management also provides the opportunity to reframe questions and to engage in discourse on more radical alternatives, such as moving away from gasoline-powered cars and adopting materials and constructions not requiring flame retardants.

More generally, in the face of the complexity and unpredictability of the world (and of humans trying to make sense of it, function in it, and control it), trial and error remain an essential ingredient in social learning (which, besides formal and institutional learning, encompasses other dimensions in the build-up of knowledge, experience, and culture). This is true even in medicine, despite the alleged increased precision of personalized and general medicine. There is a large gray area (with many shades of gray) between evidence and pure conjecture (or prejudice) in decisions both on a personal level (e.g., regarding medical advice) and on the collective and policy level (e.g., regarding health care), notably due to the variation in, and impacts of, decisions in other areas (Assmuth & Lyytimäki, 2015). Thus, instead of seeing the precautionary approach as an alternative to the evidence-based approach, it should be seen as a complement, and their components and mutual relationships should be much more nuanced. The key issue is the kinds of evidence needed and available in a given context and with a given set of purposes.

Third, the alternative to a precautionary approach in environment and human health science may be what has been called “paralysis by analysis,” which results from an emphasis on scientific uncertainty, raising concerns about potential problems. Hardell et al. (2007) reflected on industry involvement in cancer research as one example of unmasking independent scientific judgments, and Michaels’ book Doubt is Their Product: How Industry’s Assault on Science Threatens Your Health (2008) is another. Hardell et al. (2007) referred to several cases in which scientists who were secretly paid by industry without transparency took a stance against scientific results critical of activities or products from the industry financing them. A Swedish professor was revealed to have worked for Philip Morris for 30 years (Diethelm, Rielle, & McKee, 2005), and even after initial evidence of his relationship was published in 2002, the professor still denied any ties. Hardell et al. (2007) presented another Swedish case, in which a consultancy firm acted as an intermediary between the chemical industry and scientists paid by the firm. Another example is the U.K. professor with ties to asbestos manufacturers and Monsanto (Hardell et al., 2007).

In addition to the secret ties between industry and experts, Hardell et al. also presented staggering figures about the amount of industry-funded scientific involvement. Industry paid scientists to attack negative outcomes for industry by presenting their results that showed opposite findings as “independent,” or to cast doubt by criticizing the quality of any research that conveyed serious risks. Some defense responses published by scientists accused of collusion with industry raised doubts about almost all claims of independence. The accused argued that everyone involved had some interest in the issues. Of course, this is correct. Scientists are also entrepreneurs who are dependent on funding for the research that makes their careers possible. In fact, one might cynically point out that scientist/researchers even have an interest in the existence of problems. Hardell et al. (2007) and others stressed the importance of rules about industry involvement. But the same applies to scientists and experts: studies (Tversky & Kahneman, 1974) have shown that experts regularly overrate the certainty of their judgments.

Besides manufacturing and overselling the certainty of claims, many actors (including, but not limited to, industry) also manufacture and oversell uncertainty (McCright & Dunlap, 2010), disputing other claims, in effect trying to sow, and benefit from, a manufactured confusion. This strategy is a key aspect of the present-day “post-fact” world, a bizarre outcome of anti-scientism and exaggerated relativism (and even partly resulting from well-meaning and well-deserved criticism of too much reliance on science) hijacked by powerful interests. It should be noted that industries and their motives and conduct are not uniform; some industries profit from one risk, others from another, and still others from perceived cures or alternatives, and all easily resort to selective evidence and argumentation while claiming to act for the common good. Importantly, in environment and human health, the same is true for special interest and advocacy groups, including consumer, citizen, and patient organizations, which may constitute powerful lobbies. While often portrayed (by themselves and others) as virtuous in comparison to industry, they also are prone to subjectivity and bias, precisely due to their role as advocates, and may therefore abandon careful and balanced scientific judgment. Similarly, it is by no means only “conservatives” (which is an ambiguous denomination, including many radical elements) who are manufacturing “alternative facts” and uncertainty. Their radical opponents do this as well in their claims for other facts (scientifically based to various extent) and in their eagerness to act (e.g., for precaution), sometimes also in their criticism of reason and of the conservativeness of science. Both stances, when unchecked, threaten to “throw out the baby with the bath water,” marginalizing the proper role of science, despite its imperfections, in resolving environmental and health issues.

It is well known from sociological and cultural studies of science that researchers are involved in, and influenced by (and influencing), these processes and the associated valuations, emotions, and cultures; they are far from being neutral outsiders and referees, despite their stated (or often only implicit) ideals. Such factors are particularly influential in the fields of environment and health (and in the combined area), both of which arouse strong emotions, such as hope and fear, are hotly contested, and are even emblematic of more general societal beliefs (Johnson & Covello, 1987; Vatn, 2009).

Particularly in medicine, evidence-based methods evolved to counter such factors, in order to provide maximal certainty to life-and-death decisions, while acknowledging and dealing with residual uncertainty, the role of emotions in positive terms, and the need for engagement, values, compassion, and action, thus cultivating positive influences but guarding against negative influences on judgment. However, the criticism of evidence-based methods and the questioning of rationality and objectivity more generally in a complex world, as well as the erosion of the authority of experts and science due to societal (also political) and technological (notably information and communication technology) developments, have recast the role of knowledge even in medicine, and have strongly shaped the development of environmental health as well as related contested areas, such as nutrition. For example, Internet diagnosis and counseling have opened up and made vulnerable standard medical and nutritional authority to a plethora of second opinions and competitive claims. The emergence of personalized medicine, based on individually specifying information (e.g., genetic) and targeted care, is another driver for this diversification of expertise and for its co-construction with the individuals involved. Yet, in many decision situations at both individual and community levels, such traditional uniform authority and certain answers to complex questions are still being sought. The coevolution of these different approaches to questions of health is in itself complex and dynamic, and its detailed courses remain to be seen (Spruijt et al., 2014).

Complexity Arising From Intentions, Purposes, and Values: The Tragedy of Good Will

The complexity of environment and human health issues is not at limited to scientific understanding; it is closely related to governance and practice within public health, health care, and environmental management. In this realm, complexity may result from opposing aims and stakes, as is the case with industry involvement in science. It may also follow from a tragedy of good will, when actions with good intentions may have trade-offs with other actions with similar good intentions. A classic example is the dilemma of poverty alleviation: alleviating the most dramatic effects of poverty may counteract the goal of addressing the structural causes of poverty. A similar environment and human health case was made at a conference where a specialist on the health effects of climate change complained about the negative effects of mitigating the health effects of climate change, which downsizes the “real” health impact of climate change and thus partly conceals the root of the health problems related to climate change. Similar problems may occur with prevention strategies for health: how can prove what was avoided or did not happen? (This is illustrated further in the One Health example.)

Several other types of complexity arise from conflicting or unclear purposes, intentions, and values, and generally from ethical and, in a more practical domain, political and legal dilemmas. The well-known political factors (Perreault, Bridge, & McCarthy, 2015) of power, agency, and autonomy are frequently encountered in health care, environmental management, and their intersection, environment and human health. Many key issues involve justice and fairness and the processes (from individual to collective and local to global levels) in building trust and in forging social contracts.

Furthermore, in aligning environmental and human health concerns and activities, a central question is anthropocentrism, the degree to which and how humans are put in the center of things and of value systems, and what the relations are between the impulses and imperatives to care for both humans and other organisms, and even for whole ecosystems. Difficult questions of conflicts and trade-offs emerge, in addition to apparent and less apparent synergies and common interests reflected in the notion that biophilia (Wilson, 1984) is an innate propensity of humans (and in some ways even nonhuman animals) to be attuned to, and to care for, all life. These questions are at the core of attempts to align the concerns and aims of human, veterinary, and ecosystem health (e.g., in One Health and other integrative approaches to health). Again, it is a matter of balancing risks and benefits for or to humans and other organisms from or through humans and other organisms, including beneficial and harmful organisms (such as pathogens and pests) and intermediates.

Thus, in general it can be said that many key principle-level and practical complexities are encountered within the realm of bioethics. Their resolution is not only, or sometimes even primarily, within the grasp of science, and definitely is not within the scope of exact and natural or applied natural (such as medical) science, but requires other foundations for policies and decisions, including collective definitions of acceptability and preferences. For instance, whether humans are considered to be justified to dominate, use, and (as claimed by some) abuse domestic animals, laboratory animals, or even wildlife for some human-centered purposes, notably medical and nutritional, is an ethical question that can be resolved only partly through understanding of “facts” (such as what suffering or even what economic values are involved). Nevertheless, science (including social, political, and legal science) evidently has a central role to play, in clarifying the complexity of issues and concepts, in interpreting them in connection with biomedical and ecological knowledge, and, importantly, with practical care or management, and in offering methodologies for their systematic treatment in society at large.

Example: The Mysterious Massive Death Among the Endangered Saiga Antelope Population

Nicholls et al. (2015) reported on a rapid and massive die-off among saiga antelopes in Kazakhstan, where the animals live in large herds. Nicholls quoted Richard Kock (wildlife veterinarian at the Royal Veterinary College in Hatfield, United Kingdom), who was involved in investigating the tragedy: “I have worked in veterinary diseases all my career and I have never seen 100% mortality. . . . We had a herd of 60,000 aggregated and they all died. That is extraordinary.”

The saiga antelopes were close to extinction at the end of the 19th century, due to widespread hunting. There was some recovery in the 20th century, but the end of the Soviet era brought about a dramatic collapse. With rural poverty, a willing Chinese market for meat and horns, and little law enforcement or management, people killed the saigas in huge numbers. All of this resulted in a 95% decline, which led to the saiga’s being listed on the International Union for Conservation of Nature’s Red List of Threatened Species in one of the highest categories: critically endangered. At the count announced in April 2014, the global population of saiga antelopes stood at 262,000, up more than 200,000 from their lowest point in the early 21st century. Much of the increase was driven by the growth in the population that is now being devastated. In the end, ca. 200,000 animals perished in the recent die-off (Dasgupta, 2016), thus almost completely wiping out the population. Luckily, the die-off was halted and the number of animals appears to be increasing again (Dasgupta, 2016).

In the context of this animal population tragedy, an unfortunate tragedy of good will (Richard Kock, personal communication; Karesh, Kock, & Machalaba, 2016) played a prominent role: the urgency to investigate the causes for the rapidly increasing saiga antelope die-off ran into conflict with international trade rules aimed at the protection of the same species. CITES (the Convention on International Trade in Endangered Species of Wild Fauna and Flora, an international agreement between governments, aiming to ensure that international trade in specimens of wild animals and plants does not threaten their survival) supports the protection of the saiga antelope with severe restrictions on the international trade and transport of the species. Yet, in the midst of the recent crisis, what in fact was urgently needed was transport of biological material from deceased animals to sophisticated research laboratories abroad. Despite the urgency and the catastrophic nature of the die-off, the CITES restrictions severely hampered a rapid diagnostic response to the disease outbreak, a situation illustrating that, even with good will, good outcomes are not always straightforward.

Framing Environmental Health Complexity: Integrative Frameworks

Integrative frameworks play, or may play, a prominent role in the broad field of environment and human health. Related developments in policy integration, such as HiAP (Dora, Pfeiffer, & Racioppi, 2013; Leppo, Ollila, Peña, Wismar, & Cook, 2013), are also discussed briefly.

Integrated Environmental Health Impact Assessment

Integrated Environmental Health Impact Assessment takes into account the interconnected nature of health problems rooted in environmental, social, and political systems and the precautionary nature of resulting policies. The approach departs from the notion that environment and human health problems are complex and systemic. It requires a diverse analytical approach: applying a range of different models to the complexity of a combined impact of multiple environmental factors on a number of different health outcomes. It also requires a deliberative approach involving a diversity of key stakeholders who evaluate the scientific findings with respect to societal/policy goals.

Briggs (2008) was one of the founders of this approach. He underlined that the key challenges of more integrated methods of assessment not only relate to the content of analysis, environment and health problems, but also to the involvement of relevant stakeholder perspectives. He criticized traditional forms of assessment and proposed to focus on a “real world” perspective in which problem framing is of central importance. According to Briggs, the relevant actors involved need not be limited to scientists: the involvement of stakeholders is equally important, and at an early stage. Based on two research projects funded by the European Union (INTARESE and HEIMTSA), a practical, stepwise process was developed: issue framing, design, execution, and appraisal (IDEA). For more details, see IEHIAS—the Integrated Environmental Health Impact Assessment System. According to Briggs (2008), despite numerous pleas and ambitious objectives with respect to environment and health, the application of integrated approaches in research practice was still in its infancy in 2008. A March 2017 search in the Web of Science for more updated overviews did not yield concrete results.

Integrated Risk−Benefit Analysis

Integrated and cumulative risk assessment has been around for a relatively long time, both in the field of health risks and in the combined and thus inherently integrative field of health, environmental, and safety risks, which are commonly combined (e.g., in industrial activities and other practical areas of risk management). Integrated studies and regulatory or nonregulatory risk management approaches have emerged in response to a variety of risk agents, notably chemicals, and then have been extended to address other stressors (Assmuth, Hildén, & Benighaus, 2010a).

The consideration of the societal aspects and processes in risk management (including management of environmental health risks) is still relatively new, in comparison with the plethora of studies and assessments of risks from natural scientific and technical points of view. There are important foundations for such an orientation, notably in economics and in decision sciences within which risk analysis has largely developed. Similarly, studies of the politics of risk and how they are perceived have a long history (Bradbury, 1989; Jasanoff, 1988). For instance, the basic structures and functions in the European Union (and supra- and sub-EU) regulation and associated multi-actor governance with respect to integrated risk assessment have been analyzed recently (Assmuth et al., 2010b).

A key development in the more integrated treatment of risks to health and (even simultaneously) to other entities, such as the environment, has been the joint consideration of risks and benefits from different agents and actions. A prominent example is the consideration of mixture effects of several compounds, but this is a special case of integrated risk assessment and management (Assmuth et al., 2010b). The aims are to make risk assessment more attentive to decision situations and to assess and to evaluate consequences of actions more comprehensively. This development is based partly on the traditional consideration of risk and benefit and associated uncertainties in economics, as in cost-benefit-risk analyses. It may also be seen as part of a general development in environmental management from problems to solutions, and in environment and human health and even other areas of health from a risk factor-oriented approach to an emphasis on salutogenic (i.e., health-promoting) factors and processes (Antonovsky, 1996). However, it may be argued that the growing attention to benefit is related to the overall preoccupation of societies, specifically politicians and enterprises, with economic value and the “bottom line” as factors trumping all others and requiring that other values be monetarized.

Integrated risk−benefit assessment is important conceptually, because it makes room for the notion that risks and benefits are not strictly separate, and not merely to be juxtaposed. Instead, most risks carry the possibility of rewards, and risks are also taken, more or less intentionally, for potential benefit, by individuals, by groups, and by whole societies. This becomes clear when risk is defined as per economic risk theory as the “probability of loss of opportunity” (cf. definitions of risk in other areas as a function of the probability and consequence of an adverse event; Renn, 2008). On the other hand, an intuitive and simple link between risk and benefit is the notion that reducing a risk and associated costs will generate benefits; thus it is natural that both aspects are considered jointly. Indeed, the potential benefits from reducing a risk are regularly used as an argument for action, in more or less explicitly stated and quantified (often uncertain and contested) estimates or conjectures of losses and gains. The intense debates on the economic benefits versus costs, especially to health care, of the European Union’s proposed REACH regulation on chemicals, as well as the appropriate methods for framing, assessment, and interpretation, is a case in point (Assmuth et al., 2010b).

But there are further links between risks and benefits to consider. Attempts to manage (prevent, avoid, reduce, and compensate for) risks, while intended to, and potentially able to, provide gains, also carry the possibility of unintended harmful consequences (i.e., countervailing risks of risk management), a routine consideration in decision analyses. Countervailing risks can significantly reduce the net benefit; at worst, they may become more severe than the risk originally set out to be reduced, a concept captured by the proverbial throwing out the baby with the bathwater or by the notion of a cure that kills the patient. When the frame is extended to environmental issues, countervailing risks may be encountered more often and may involve trade-offs that are not routinely addressed, such as in choices between the protection of human health (say, from vector-borne diseases) and the protection of ecosystems that the risk agents are part of. On the other hand, new kinds of synergies emerge.

EcoHealth

EcoHealth encompasses ecosystem approaches to health: it encompasses the biological, physical, social, and economic environments and their relation to human health. EcoHealth can be characterized by interdisciplinarity (e.g., involvement of health science, veterinary science, ecology, and social science) and transdisciplinarity (collaboration with nonacademic practice experts and stakeholders). Apart from the collaborative angle, originally the equity perspective was essential in EcoHealth (Lebel, 2003). Later, a more sophisticated set of EcoHealth principles was developed (Charron, 2012).

Systems thinking aims to support ordering the complex reality of health in the context of social–ecological systems, integrating several interrelated dimensions (ecological, sociocultural, economic, and governance). Transdisciplinarity aims to integrate a diversity of relevant knowledge, including a diversity of scientific disciplines as well as other professional fields and stakeholder expertise. Participation, close to transdisciplinarity, underlines the importance of locally rooted approaches through engagement of local communities. The “knowledge to action perspective” relates to the local anchoring in that it promotes the knowledge that is developed in relation to action, making it both context-specific and practical. The aim is less on developing perfect understanding than on creating an iterative and adaptive process of problem solving.

In such approaches, two other principles are considered crucial. The first is sustainability: protecting ecosystems and improving degraded environments are fundamental requirements for human health and well-being now and for future generations. The other crucial principle is gender and social equity: EcoHealth specifically addresses unequal and unfair conditions that impinge on the health and well-being of women and other disadvantaged groups in society. (For more information, see www.ecohealth.net.)

One Health

One Health also began by trying to cover a variety of expertise, stemming mainly from the health and veterinary sciences, but over time it broadened its perspective to the environment. Zinsstag, Schelling, Waltner-Toews, and Tanner (2011) proposed One Health as an approach aimed at tackling complex patterns of global change, in which the inextricable interconnection of humans, pet animals, livestock, and wildlife with their social and ecological environment is evident and requires integrated approaches to human and animal health and their respective social and environmental contexts. The World Health Organization Convention on Biological Diversity (WHO-CBD) state-of-knowledge review on biodiversity and health (2015) proposed One Health as an overarching framework for integrated efforts, while also recognizing and relating to other relevant approaches, such as EcoHealth. Earlier, a tripartite collaboration among FAO, and OIE and WHO (2010) proposed a similar integrated effort, also called One Health. Wallace et al. (2015) extended the concept of One Health to include the socioeconomic perspective more clearly, in what they labeled Structural One Health. They criticized the prior One Health concept for failing to address the fundamental structural political and economic causes underlying collapsing health ecologies.

Nature’s Contributions to People

Whereas several of the above-mentioned approaches mainly focus on health risks and are largely problem oriented, from a biodiversity conservation perspective, more attention has been paid to the contributions of nature to human well-being, in which health is an important (but not sole) element (World Health Organization, 2006). The idea of ecosystem services (Millennium Ecosystem Assessment, 2005) was developed as a fundamental concept for addressing this broadly, although with limited elaborated attention to human health, particularly in the early days. The framework of the EU Concept of Nature Based Solutions has given human health a more prominent role (Eggermont et al., 2015; Nesshöver et al., 2017). In the context of the Intergovernmental science-policy Platform on Biodiversity and Ecosystem Services (IPBES), the term Nature Contributions to People was coined, and it also incorporates explicit attention to human health and well-being (Pascual et al., 2017).

In the WHO-CBD state-of-knowledge review on biodiversity and health (2015), a broad overview is presented of nature−human health linkages, including ecosystem services related to both health benefits and risks. Biodiversity contributes to traditional and modern medical practice, and the utility of various species for medical research is considerable, as well as indirect (e.g., through the cumulative knowledge they have contributed to). Genetic and species diversity is functional in food production and can play an important role in addressing issues of nutrition security, including certain disease risks (e.g., obesity, diabetes), through dietary improvements. Biodiversity also plays a role in safeguarding air quality and access to freshwater and in disaster risk reduction, and it supports emergency responses and adaptation to climate change. Furthermore, diverse natural environments may enhance experiences that reduce stress, support the development of cognitive resources, stimulate social contacts, attract people for physical activity, and support personal development throughout an individual’s lifespan. Moreover, recent studies have shown that declining contact with some forms of (microbial and other) life may contribute to the rapidly increasing prevalence of allergies and other chronic inflammatory diseases among urban populations worldwide. Biodiversity thus can make an important contribution to both ecosystem services related to public health (health promotion) and the reduction of health risks (disease prevention and health protection). Biodiversity can also produce adverse effects on health, such as infectious diseases, allergies, or infestations of pests.

Health in All Policies

From the point of view of integration in the context of environment and human health, the Health in All Policies (HiAP) initiative (created by the WHO and taken up by many other international, national, and subnational organizations) plays an important role on many levels, both directly and indirectly. A good general description, analysis, and discussion of HiAP were provided by Leppo et al. (2013), who focused on the functional relationships between health care and other sectors from the point of view of policy coordination. Links between the HiAP approach and ecosystem services have been explored by Horwitz and Finlayson (2011) in the context of wetlands management.

Several parallel attempts and developments have occurred in the integration of other policies and approaches besides those in health care. Notably, in the field of environmental management, integration and coordination have been promoted based on the Cardiff Process of the European Union, being an “Environment in All Policies” mainstreaming effort that has also created European-wide legal and administrative procedures. The integrative perspective extends to other areas besides environment and policy, notably to sustainability science and policy, where integrated assessment (IA) has long promoted the joint consideration of ecological, economic, and social aspects of development. In this sustainability context and even separately, human health and welfare have been included in some of these IAs. Importantly, issues of complexity and uncertainty, as well as quality of knowledge and methods of knowing, have been analyzed actively in connection with IA (Rotmans & van Asselt, 2001).

On a higher and more institutionalized level of integration, one should note the generic requirements and guidance for the impact assessment of policies and other regulatory instruments (such as strategies, plans, and programs of the European Union), involving the development and deployment of improved policy indicators (Bauler et al., 2011). Thus, in health care, environmental management, and related sectors, various specific and operational indicators, as well as generic and strategic indicators, both pertaining to outcomes and to processes, have been adopted in the interaction of supranational (European Union) and national and subnational levels of governance. The monitoring of the state of health or of the environment is an obvious example, but process indicators and compounds are also commonly used (e.g., in the area of sustainable development). These partly detailed, but still rudimentary, procedures represent an attempt to aid policy formulation in the cycle through implementation to oversight and revision, and to make regulation more efficient. However, the procedures (in themselves complex takes on complexity) now face new problems due to the challenges of the structures and functions of the European Union as whole.

All these aspirations may be seen as a reflection of the connectedness and complexity of issues and of the growing importance of “wicked” systems issues.

Key Aspects of Framing Complexity

General Considerations

Some key differences between the various approaches to complexity include those characterized by the polarities reductionist or holistic, closed or reflective, positivist or relativist, constructivist or de-constructivist, essentialist or critical, as well as by the continuum between mono-, inter- and transdisciplinary approaches. For guidance to navigate between these, key ontological (concepts), epistemological (methods), and ethical (as well as political) principles and issues are outlined. The discussion investigates how general complexity approaches can be conceived in environmental health by introducing and commenting on some telling examples of practical approaches to dealing with environmental health issues, particularly evidence-based and precautionary approaches, expert-driven and deliberative approaches, and formal and informal approaches and their combinations.

According to Morin (2008), regarding complexity, the method should emerge from the research.” Here the word method is used in its original meaning as “path.” Morin (2008) “we must accept to advance without a path, to make the path by advancing” equivalents or interpretations of this methodological strategy in more formal scientific and applied terms include exploration, trial-and-error and adaptive governance, as well as clues as a traditional method of investigation also in medicine (Ginzburg, 1992). This does not mean that practice is sacred and methodologies and reflections from methodological expert debate are only of secondary importance. It means that they complement each other in serving the aims of the endeavor and addressing the challenges posed by practice along the way. Moreover, the nature of complexity challenges “textbook approaches” of strict and unambiguous application of methods, strict application of textbook methods is blind to unforeseen complexities, to that which cannot be captured, controlled or foreseen completely. With respect to method and complexity, the distinguished methodological thinker Patton (2002) referred to the metaphor used by Gleick (1987) to explain the nature of inquiry into chaos: “It’s like walking through a maze whose walls rearrange themselves with every step you take.”

From a critical complexity perspective, making choices is essential in two important respects. One is that we can never have perfect knowledge about complex issues: we choose a picture of reality but have to realize that each picture has limitations. The picture can have many forms (e.g., problem framing, a model, a research ambition, a policy action, or a public debate). Second, we cannot state which picture of complex reality is best or better than other pictures; therefore, knowledge will not be unambiguous. Does this mean that we should not reduce complexity in order to deal with it realistically and that we have to accept that in principle all knowledge is of equal significance? The answer to both questions is no. According to Cilliers (2005a):

“Limited” knowledge is not equivalent to “any” knowledge. If this were so, any modest claim, i.e. any claim with some provisionality or qualification attached to it, would be relativistic. . . . Modest claims are not relativistic and, therefore, weak. They become an invitation to continue the process of generating understanding.

And:

This does not imply that we can know nothing about complex systems, or that the knowledge claims we make about them have to be vague, insipid or weak. We can make strong claims, but since these claims are limited, we have to be modest about them.

In the process of knowledge generation, we constantly have to make interpretive choices: “Knowledge is interpreted data. This leads us to the next big question: what is involved in interpretation, and who (or what) can do it?” (Cilliers, 2005b).

By choosing our picture or reality, we draw boundaries. We draw ontological boundaries that frame the picture of complex reality: knowledge boundaries. And we draw epistemological boundaries with respect to the generation of knowledge on complexity: disciplinary and transdisciplinary boundaries. Moreover, we “perform” ethics in our boundary work: we choose what we consider to be relevant, important, just, better, best. Ontologically the boundaries can be bold or modest, flexible or inflexible. Epistemologically the boundaries can be closed and inward looking or open and an invitation to dialogue with others and other forms of knowledge.

Boundaries create a difference as they distinguish the inside of the picture of complex reality from the outside, and distinguish one picture of complex reality from another picture. A picture of the health effects of one pollutant is different to a picture of the health effects of another pollutant, and is different to a picture of the health effects of a cocktail of pollutants. A natural sciences picture of environment and health will focus on other aspects than a social sciences picture, even when looking at the same environment and health issue. In fact, scientists with similar disciplinary background can potentially create completely different pictures of similar environment and health issues. A scientific picture will probably focus on other characteristics of complexity than a picture from policy makers or other stakeholders.

This does not necessarily mean that some pictures are better than others, nor does it necessarily mean that we should fuse all pictures into one “super picture” of complex reality. Different pictures may complement and may enrich each other, but may also critique and compete with each other. The way we choose to deal with difference is of the utmost importance in the case of complexity. We can consider openness to the other, different pictures of complexity and other perspectives on complexity important as a test of one’s own picture: is our picture of complex reality robust when we compare it to other pictures, can we learn from other pictures and do we pass the challenge of being criticized by others about the robustness of our picture?

Theoretically this might imply that the more different viewpoints we take on board and the more critical mass we organize to test our endeavor, the more robust our end product, be it knowledge or be it (e.g., policy) action. This would indeed connect well to the ideal of integrated assessment proposed to us by Briggs (2008) and the involvement of stakeholders proposed both by Briggs (2008) and Grandjean (2005, 2008). In fact, we may broaden the basis of support for this openness with reference to other approaches in the familiar fields of risk governance and environmental science and policymaking that promote an “open arms approach,” such as the analytical-deliberative approach (Stern & Fineberg, 1996) and the extended peer-review approach (Funtowicz, Martinez-Aler, Munda, & Ravetz, 1999).

Cilliers (1998) proposed this theoretical ideal of openness to, and respect for, differences as an ethics of complexity. Cilliers (2004) nuanced this ideal by focusing on the notion of power: “The argument from complexity claims that a single story, or in the words of Lyotard, a ‘coherent meta-narrative’ cannot describe any social system fully. . . . The reason why a certain description is acceptable has to do less with rationality and more with power. We do not have to look hard to find examples of master-narratives which oppressed the ‘other’ in the system, whether they be of a different race, religion, gender or sexual orientation.” Kunneman (2010): “Difficulties become visible when we pose the question why we should prefer his ethics of differences above—for example—an ethics of care, or the discourse ethics propagated by Jurgen Habermas or for that matter, the aggressively ‘masculine’ ethics connected with the Hip-Hop scene, or the ‘tribal’ ethics practiced with great brutality and with great economic success by Italian Mafia-families?”

We therefore do not want to proclaim a critical complexity perspective (whatever it would mean in practice) just because of the intrinsic qualities of complexity, but merely propose it as a worthwhile companion when we picture complex realities. We propose to take the openness to and respect for differences as an ambition that is worth testing, but consider it not to be immune to one of the most important ingredients of critical complexity: critical reflection.

Integrating and Specifying Integrated Approaches

There has been a convergence of the notions of health regarding the organisms concerned—humans, domestic/lab and wild animals, plants and fungi, microbiota, communities and ecosystems (Zinsstag, 2012). This is linked with the onset of integrative approaches to health already described such as Ecosystem health, Eco-Health and One Health. This convergence involves concepts and symbols, but also direct links with practical integration programs. Some drivers are material (e.g., the intensified interaction of humans and other organisms); and some are immaterial (e.g., the complexity of issues, specialization of disciplines, and non-anthropocentric concerns). The notion of health has extended to the mental and social dimensions of wellbeing and beyond humans; importantly, it is often seen as a generative process, instead of one narrowly determined by risk factors (Antonovsky, 1996).

On the other hand, diversity in the approaches to health and well-being is evident. Strides toward unity have been accompanied by pleas for varieties, such as Structural One Health (Wallace et al., 2015) or extended One Health (Woldehanna & Zimicki, 2015), and by considering the gaps found between the emerging communities of practice. Some of this diversity will disappear, but some will emerge and persist as part of the evolution of these complex fields. Critics have also found indiscriminate holism in approaches to health, as a parallel to “One World-ism” as a specific Western construct (Hinchliffe, 2015). The sociocultural dependency of unification and generalization (similar to the dependency on the biophysical context), thus needs to be elucidated for feasible integration or for the interaction of concepts and practices of health. As a concrete example, the need to consider the social realities and political questions in One Health, such as those related to inequities and power, may be mentioned.

Along with integrated and even coordinated concepts and approaches, simultaneously attention needs to be paid to specificities such as those due to socio-economic, political and cultural circumstances and variability. Similarly, integrated approaches to health are accompanied increasingly by a personalized medicine and care, where the particular properties, requirements and capacities of the individuals being examined and treated are accounted for. The importance of this complementary line of investigation and intervention is underlined by the explosive growth of genetic knowledge, including that based on self-testing.

In all these regards, the extent and kind of integration are essentially influenced by the context and the purpose. The purpose needs not be fixed: the framing may be broad in some respects, even extending to meta-level umbrella concepts and unions of communities of practice (such as in One Health) and focused in others; and also in the diagnostic and therapeutic processes as well as in the processes of governance, there is usually a dynamic interplay between integration and specification. The goals and procedures in this interaction thus need to be worked out more clearly, in order to develop ways to deal with the complexities involved, and to turn them (at least partially) from obstacles and conundrums to assets. For instance, human and nonhuman animal (veterinary) medicine may cross-fertilize each other in new and better ways also through consideration of the ecological and social contexts and processes of both fields.

The Politics of Transdisciplinarity: The Case of Industry Involvement in the International Agency for Research on Cancer

Huff (2002, 2007) demonstrated how government bodies involved in environment and health research and policy have become increasingly influenced by industry interests and expertise. Huff (2007) discussed several cases of industry involvement with the U.S. National Institute of Environmental Health Sciences (NIEHS) and the International Agency for Research on Cancer (IARC). The focus here is on IARC (IARC). IARC is part of the WHO, and its mission is to coordinate and conduct research on the causes of human cancer, the mechanisms of carcinogenesis, and to develop scientific strategies for cancer control. The Agency is involved in both epidemiological and laboratory research and disseminates scientific information through publications, meetings, courses, and fellowships.

An important part of the work of the IARC is the Monograph Series. The IARC Monographs identify environmental factors that can increase the risk of human cancer. These include chemicals, complex mixtures, occupational exposures, physical and biological agents, and lifestyle factors. National health agencies use this information as scientific support for their actions to prevent exposure to potential carcinogens. Interdisciplinary working groups of expert scientists review the published studies and evaluate the weight of the evidence that an agent can increase the risk of cancer (http://monographs.iarc.fr/).

Huff (2002), a former chief of the unit responsible for the IARC monographs, wrote about the unprecedented and growing industry influence on the monographs (see also Pearce et al., 2015). In the case of chemical exposures, this resulted in a lower risk evaluation for chemicals. This has serious implications for workers’ and public health. According to Huff, the downgrading of chemicals by the IARC is done on the basis of little in-depth scientific evidence. Interestingly the evaluations of carcinogenicity of chemicals have been influenced by “mechanistic” considerations. This disputes the concept that the mechanisms of carcinogenicity in animals are similarly operative in humans. The increase of downgrading chemicals runs parallel to the increase of the percentage of industry experts in the expert groups assessing the health risks of chemicals. This uncovers the issue of trust: who is to be trusted, and how can we enhance trust and knowledge, assessments and action?

Issues and Opportunities in Defining Adequate Framing and Treatment of Complexity

Reductive or Holistic?

In terms of their scope and overall methodological grasp, approaches to complexity can be reductive, holistic, or of various intermediate degrees and kinds. It should be noted that reductive and holistic are not exact opposites, but have slightly variable dimensions. Thus, besides the scope in framing phenomena, reductive can refer to the reduction of detail, that is, the level of simplification of complexity within some phenomenological field, even a more restricted one. This epistemological aspect of reduction is connected to what is termed more generally, the reductive method.

Because complexity in many fields including environment, human health and their border-zones largely arises from the interconnectedness of various phenomena and fields of activity, it is logical that a more holistic approach has significant benefits and generally better possibilities to grasp complexity than a reductive approach in the ontological sense of scoping or framing.

Holistic approaches are particularly important in dealing with multidimensional and emergent phenomena (such as humans and their health and the environment or ecosystem and its health), all of these being composed of multiple levels of being and emergence, from physical over chemical to biological (with increasing complexity in living systems) to the psychosocial. Therefore, the reductive approach usually fails and even backfires, for example, in trying to replace models for explanation and prediction of human behavior with those geared to the behavior of simpler biological or even physical systems. Similar inherent limitations of reductionism are evident in psychosomatic conditions and processes: humans and societies are more than, and in some ways radically different from, biophysical systems.

With the increase of biochemical (including genetic) and physical knowledge, humans are yet increasingly being reduced to lower levels of emergence in terms of the knowledge considered to be relevant, for example, in adopting a predominantly neurophysiological view. Essential qualities and perspectives of humans are thereby downplayed, distorted or entirely lost, as they elude biophysical explanation, due to the fact that also cultural evolution plays a role and introduces new dynamics and aspects of complexity. This can backfire due to the perils in a reductionist natural scientific approach, for example, in downplaying cultural or ethical aspects (which easily occurs even though it is not a necessary consequence of a biological or ecological view).

This is not to say that the reductionist approach in these areas would be useless; it has much potential, if interacting with and informing a fuller view and understanding of humans and their environment as multi-dimensional and emergent systems. Similarly, disproportional emphasis on the socio-cultural aspects of health and environment evidently has limitations and risks, as it can lose key aspects such as the many important biomedical or ecological and generally “physical” phenomena. It should also be noted that in practical situations of decision making, considerable reduction in the ideal or objective holism takes place. Instead of trying to create the full or “big picture,” frequently one needs to limit the goal to creating a series of partial pictures, each of them sketchy. The key question is: whether this is adequate to the situation and decision at hand?

It should be stressed that pursuing and presenting things (such as health in an environmental setting) with bold holism, “trying to take it all in,” can be overwhelming to the individuals, organizations and communities to grasp and cope with. They may react to such visions of complexity by confusion, even hostility, and expect or even require reduction; in a similar way as they often react to uncertainty, in a desire or unconscious need to have a firm basis for their existence and activity. On the other hand, a holistic approach (e.g., to both human individuals and equally to their environment) can be intuitively satisfying, and able to respond to their needs. Thus, holistic approaches pose psychological and political problems, along with opportunities, and great challenges of communication. To find a balance in this regard requires trust, both on individual level (e.g., in medical professional client contacts) and on community and societal levels.

In a heuristic approach, holism can be fruitfully combined with necessary reductionism, according to the situation and purpose of deliberation and action. This is important both for experts and to others, including clients and other actors in society. They all need at times to look at both the forest and the trees, or to step closer to or farther away from the picture. Typically, the framing of issues can be shifted from holistic (in identifying issues) to more narrowly focused (in addressing them) and back again (in contextualizing). The dynamics in this process can be flexibly adjusted in an open interaction with those involved. Thus, holism with regard to the perspectives of actors can be achieved.

Positivist or Critical Complexity?

Fundamentally, there are two different approaches to complexity: one of trying to figure it out based on the positivist ideal of objective, verifiable scientific explanation and prediction of phenomena; and an alternative approach which implies adopting a critical or heuristic notion of complexity (Phoenix et al., 2013). As argued in the above discussion, the positivist ideal is severely limited or even breaks down under conditions of pronounced or radical complexity, such as those due to the need to account for extensive, inter-connected, dynamic and nonlinear systems on several levels ranging from biophysical to social. This choice is related to one of method: reaching out beyond scientific explanation and prediction to an alternative tradition in humanities: emphasizing interpretation. It is also related to the psychological impulse and aspiration of control: of “variables,” of life, of health, of the world—an ideal of control which is ingrained in the development of science, especially natural and applied natural science including medicine, and technology. As such, the idea of critical complexity and a critical approach to complexity are informed by critical theory, as formulated by the Frankfurt School and importantly developed thereafter for example by Kracauer (1995) regarding history (with extensions and applications to life history as well as to social history).

This does not mean that there would be no merit in the positivist ideal, even in addressing complexity: for some purposes, it can still contribute important insights and results, even though assumptions of value-free facts would be relaxed. Positivism can thus complement the preferred alternative of critical thinking, and together they can amount to what can be termed realism or pragmatism (as formulated notably e.g. by Pearce), and, with regard to the inter-subjectivity of many phenomena, rationalism defined in collective action as by Habermas (1984, see also Skollerhorn, 1998). For example, in environmental health, (interim) rational decisions may be achievable through the collective process of participation, communication and negotiation. In such as position, positivism would be put to proper service, without trying to establish rationality in cases where it is elusive, such as under conditions of radical complexity, or without trying to apply the positive ideal in areas where it is not suited (e.g., in social engineering or to optimization of phenomena and situations where no discrete, singular optimum can be found). The preference for critical complexity also does not mean that a diametrically opposite approach would be taken: that of unbridled relativism that would deny the possibility of all invariate and objective facts. As shown by Putnam (2002), the divide between facts and values is artificial and untenable, thus opening a way to a new balance and synthesis between objectivism and subjectivism as well as positivism and relativism.

Quality of Knowledge

To properly address the above themes and translate them into strategies for research and more broadly for knowledge co-generation and use processes, we include a discussion on the quality of knowledge, including the tension between relativistic stances and positivist stances. We address specifically the limitations and risks of relativism as far as it implies “anything goes” (which can also be misused to manufacture doubt, as noted above in the climate discussion and with many health claims); and the limitations and risks of positivism chasing objectivity and invariate truth, for example in proof of causality of effects, even in the face of high-order complexity that precludes such a method. We show how these stances interact and frequently reinforce polarity and “science wars” in the field of environmental health, and how a middle road can be found through notions of inter-subjectivity and collective rationality, traditions of realism and pragmatism, and especially by an open, socially embedded deliberative-reflective approach to complexity. We also comment on political and other societal aspects of the various views of complexity, such as transparency, autonomy and the self-corrective ability of science. In the field of environment and human health, specifically One Health and other such integrative and synthetic concepts, anti-anthropocentric and even post-humanistic notions of health and of associated realities, agents/actors and knowledges are contrasted with traditional notions and practices.

Dealing with complex issues per definition bears the burden of imperfection. Whatever comforting concepts may promise, real life complexity will take its messy toll once travelling from conceptual ambition to real life practice. Practice is messy and stubborn and the scientific method incapable of total control. Moreover, conflicting scientific standards and traditions may pose insurmountable ambiguities. A challenging issue in this respect is quality: how can we assess the quality of important but imperfect information. How can we balance ambition, importance, practicalities and imperfection?

With respect to the evaluation of analytical deliberative (or likewise) participatory processes, objectifying its quality criteria is considered very difficult. There may not even exist definite, invariate criteria and single discrete optima, especially in situations involving very complex and very ambiguous decisions (such as value-laden and controversial). The quality of deliberation then may vary widely depending on the perceptions of those deliberating. Renn and Schweizer (2009) pointed out that the diversity of concepts and background philosophies is one of the reasons for this. Rowe, Marsh, and Frewer (2004) concluded that the complexity of participatory processes makes it difficult to identify clear benchmarks for evaluation. Rauschmayer, Berghöfer, Omann, and Zikos (2009) stressed the fact that such processes involve a diversity of actors, and as such a diversity of preferences, also from the point of view of process evaluation. This may lead to the fact that process outcomes are valued differently from different actor perspectives. They propose the use of participatory evaluation.

What is crucial is to find a relevant balance between taking into account relevant complexity in order to not exclude important factors or actors, and on the other hand, taking a pragmatic turn in order to be relevant for practical action which cannot wait for perfect understanding (Keune, 2012; Keune et al., 2012). As one of the policy representatives pointed out when reflecting on an integrated science—policy interface procedure: “It looks rather complex to me, but I cannot think of any alternative in order to better deal with the challenge (of translating environment and health science into policy action) ahead of us.”

Acknowledgments

The authors thank Oxford Research Encyclopedia for inviting this article and for editing and finalizing it. The authors also thank several colleagues for providing telling examples or other food for thought on which the article could be built: Samuel Coenen, Adam Finkel, Richard Kock, Conor Kretsch, Serge Morand, Bram Oosterbroek, and Sophie Vanwambeke.

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