Conceptual Issues in Environmental Epidemiology and Environmental Health

8/6/2019 Conceptual Issues in Environmental Epidemiology and Environmental Health

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_____________________________________________________________

MSc Environmental Epidemiology & Policy _____________________________________________________________

PROJECT REPORT

Conceptual Issues in

Environmental Epidemiology

& Environmental Health

Salim Vohra1996-97



Conceptual Issues in Environmental Epidemiology and Environmental Health Cand. No. 1032

Contents

PageAcknowledgements

Background Summary 1

1. Introduction 2

2. The Process of Knowledge in Science 4

3. The Process of Knowledge in Epidemiology 7

4. Concepts and Definitions 11

5. Scientific Models, Frameworks and Metaphors 17

6. Methodology and Research 29

7. Theories 31

8. Mathematical Models 35

9. Environmental Health Frameworks 36

10. Conclusion 46

References 48




Acknowledgements

I would like to thank the staff of the Environmental Epidemiology Unit for helping to teach me the

core of Environmental Epidemiology and Policy and in particular my tutor and project supervisor

Helen Dolk.

My special thanks goes to Professor Tony McMichael for his insightful lectures, seminars and

articles for without them I would not have had the idea or impetus to undertake this project.

My thanks also to Nasim Valli and Tessa Kershaw, the long suffering Environmental

Epidemiology Unit Secretaries, for putting up with my silly requests throughout the year.

Lastly, and most importantly I would like to thank my fellow students on the course, especially

Trevor Leveridge, Meri Koivusalo, Andrea Radnai, Gabriele Munding, Hadijah Musa, Mireille

Toledano, Catherine Lillis and Ferdinando Vegni for the many, many enjoyable, interesting, silly,

serious and challenging chats we have had about “life, the universe and everything” in the

LSHTM refectory-canteen. Thanks for everything.




Page 1

Background Summary:

There has been some recent discussion in the epidemiological literature on the need to

elaborate a framework for theory that underpins the knowledge and information produced by

epidemiologists. Krieger specifically has argued that ‘epidemiology theory’ encompasses

theories that are different from both theories of causation (the basis for mathematical models of

disease causation) and error (the basis for study design and analysis). Epidemiology theory she

argues should encompass ecological, evolutionary, social, cultural and political dimensions in its

description of disease and health processes and so provide a broader, richer and deeper level of

explanation and prediction of health and disease. This would give useful insights not just for

epidemiology but for public health and health policy as well.

Other epidemiologists have highlighted different aspects of this perspective notably McMichael,

Susser, Pearce, Wing and many more. This has come about largely due to the emergence of

phenomena such as AIDS, the impact of global warming, the degradation of ecological life

support systems and the increased understanding of the socio-economic and political factors

impinging on health, research and health policy. Alongside this, over the last two to three

decades, has come a reassessment of the impact of better incomes, sanitation, housing, food

and water quality as compared to medical interventions as well as very recent work on the

impact of early life events, relative income differentials and social cohesion which have led to a

reappraisal of our understanding of health and disease as processes in space and time that

have more to do with relationships between social organisational structures and ecological

systems than single agent-host-environment or multiple risk factor-disease processes.

This is likely to have profound implications for environmental epidemiology and environmental

health as its traditional areas of focus are likely to change as our understanding deepens of the

complex, embedded and interdependent processes that are taking place at the global and local

levels even in the seemingly simple case of understanding the effects of single chemical

exposures on individuals in populations in the real world.




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1. Introduction

“...Not everything is equally worth knowing, …there are some central, architectonic forms of knowledge

without which others would have no value.” 1

This project aims to explore some important conceptual issues in environmental epidemiology

and environmental health. These issues have been framed in the broadest possible terms so

that their scope can encompass epidemiology and environmental health as a whole.

Over the last three decades in particular three interlinked ideas or theories have emerged

namely: systems theory, chaos theory and complexity theory. In the essentials these theories

deal with the understanding of, prediction of events in as well as the types of interventions

feasible in complex systems 2,3,4 . There is a growing literature on ‘complex’ systems in areas as

diverse as physics, mathematics, biology, economics, ecology, computers and

telecommunications.

Though there are a range of definitions of systems the basic one is that a system is a set of

interconnected elements such that a change in the state of any one element induces changes in

the state of the other elements. Hence systems are coherent entities in space and time with

interrelated elements that act as a whole 5. Complex systems therefore include cultural forms,

social systems, economic systems, politics, ecosystems and organisms. Hence health and

disease are phenomena and properties of complex systems (organisms) embedded within

larger complex systems (ecosystems, social and cultural systems).

Though there is some debate, my intuitive feeling is that the ideas developing in other disciplines

of how complex systems work are likely to have a significant, if not profound, impact on how we

look at health and disease and hence what kinds of research and policy frameworks we could or

are likely to use in the future 6. In a sense we already are looking in this direction because of the

need to look at how changes in global ecosystems are likely to have health impacts on

individuals and populations 7. Some of these ideas have already been developed from a “holistic”

and “ecosystem” perspective in some areas of public health and health promotion 8,9,10 . However




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very few of these ideas are seeping into the mainstream health arena and this includes

environmental epidemiology and environmental health.

Hence, my objective in this project is to attempt the development of a theoretical schematic

framework-model-map placing the various levels of analysis in context to provide a practical tool

for looking at the interaction, impact and importance of factors leading to health and disease.

To look at how a complex systems framework-model - a qualitative scientific model - can be

developed that encompasses these ideas and links up to and expands upon existing models in

epidemiology like the web of causation. I hope to show how this expanded framework-model not

only has implications for research epidemiology but also links up to the development of a

complex systems-based framework for environmental health.

Specifically, my objective is to clarify and attempt to place on a rigorous footing three important

intuitions: First, that the epidemiology and environmental epidemiology appear narrow and

fragmented because there has been little attempt to look at the process of how epidemiology

works and produces knowledge. Second, that the ‘web of causation’, first described by

MacMahon, needs to be and could be expanded to provide a more complete framework-model

of the interconnections and relationships that influence health and disease at individual and

population levels. Third, that this framework-model could be broad enough to provide a primary

framework for environmental health and hence environmental health policy.

These areas are complex and hence my task is not to produce a definitive statement, rather it is

a concerted attempt to practically integrate these various aspects and show that they are part of

a process and framework that can be seen, for what I believe they are, as parts of a coherent

whole.

Before we can do this however we need to step back and explore the nature and process of

epidemiology as a science i.e. how epidemiology works or seems to work. However, before we

can do that we need to look at how the process of science works in general.




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2. The Process of Knowledge in Science4

The levels of explanation and the process of science, at least in the physical sciences, is usually

seen as having a number of phases that flow back and forth between each other as shown in

Fig. 2.1 and 2.2.

2.1 Levels of Explanation in Science

Fig. 2.1: Stages of knowledge in science (Casti J, 1995) 10

Where:

Observation: “The observing of events or ‘happenings’ in the external world …where

most explanatory schemes, scientific or otherwise are anchored”. They

constitute what is termed facts and are usually multiple or sequential in

nature.

Empirical Laws: “Organisation of observations into some meaningful pattern and order”.

These laws are very provisional in nature and can easily be overturned.

Laws of Nature: These laws are “more concrete, fixed and immutable.” They are more

than just an organisation of observations as they predict events that

could occur but have not yet occurred.

Theories: “A law explains a set of observations, a theory explains a set of laws”.

e.g. Newton’s theory of mechanics explained Kepler’s laws of planetary

motion.

Observation Empirical Laws Laws of Nature Theories

EXPERIMENT THEORY




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2.2 Process of Knowledge in Science

The general process of science and the way scientific theories are employed to explain and

make predictions is shown in Fig. 2.2.

Fig. 2.2: Process of knowledge formation in science (Casti J, 1995) 4

Where:

Induction: Is the process of arguing from specific instances to general conclusions

and is employed on the experimental side of science to generate laws

from observation.

Deduction: Is the process of drawing conclusions from general instances and is

used to generate predictions and explanations from scientific theories.

Dotted Arrow Line: Represents the fact that we speak in everyday language when we

make predictions based on observations and also that we use methods

of science to test those predictions experimentally.

However this is an idealised portrait as in practice the starting point of the process of science is

generally hypothesis or theory not observation 11,12 .

2.3 Models in Science

Laws &Theories

INDUCTION DEDUCTION

“everyday language”

observations EXPERIMENT predictions && facts explanations






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3. Process of Knowledge in Epidemiology

The levels of explanation and process of science just outlined does not seem to match exactly

the process of knowledge formation in epidemiology.

3.1 Levels of Explanation in Epidemiology

Castellanos has provided a framework for the levels and types of explanations of health and

disease that could be developed and how they interact with each other as shown in Fig. 3.1 13 .

Fig. 3.1: Levels and types of explanations of health (Castellanos PL, 1990) 13

3.2 Process of Knowledge in Epidemiology

A process diagram of how epidemiology works does not seem to have been developed though

McMichael has looked at the levels of epidemiological investigations and the influences on it as

show in Fig. 3.2 14 . Where W represents social determinants of an outcome of interest Y and X is

a more proximal risk factor/ exposure.




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This diagram however does not deal explicitly with how epidemiology works and my own attempt

at a diagram of the process of epidemiology is shown in Fig. 3.3. Like the general science model

this is a linear framework which is not what happens in practice as there is continual interchange

between the various parts and the elements do not necessarily follow neatly one after the other.

The arrows do show however that each element feeds into both the element after it and the one

that precedes it. The dashed arrows show that research does not feed into policy in a direct way

but in a looser more diffuse manner 15 .

Fig. 6: Levels and influences on epidemiological investigations. (McMichael 1997) 14

Population-level influences

Mainstream aetio logical epidemiology

W X Y Population Policy

Health ActionImpact

incorporation in predictivemathematically modelling

“Social Determinants”

Molecular & geneticmeasurement techniques(high resolving power of studies)

Scientific Paradigms& Social Values




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Fig. 3.3: Process of knowledge formation in epidemiologyOther Disciplines• concepts• models• methodology, etce.g. toxicology, medicine, environmental science

Mainstream/ traditional area ofwork inepidemiology

Concepts&

Definitions

FrameworkMetaphor

Scientific Model

Hypotheses

Methodology

Research&

Observation

Associations

Theories(aetiology,

causation, error)

Mathematicalmodels

(deterministicnon-deterministic)

Policy Frameworke.g. Quantitative Risk

Assessment andManagement, etc

Policy Cycle

(problem identification,policy formulation,implementation,

evaluation)

RESEARCH-POLICYINTERFACE

1

2

3

4

5

6

Social &Cultural Context

& Values+

Scientific

Paradigms




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Using the framework in Fig. 3.3, I want to touch upon each of the elements numbered but

explore four of the areas in greater detail. These areas are:

• How definitions and concepts have an impact on developing and changing frameworks for

both epidemiology and environmental health (Element 1).

• How an expanded model of the web of causation could be developed that may be useful both

for epidemiology and environmental health (Element 2).

• Attempt to list the existing theories of disease and health and explore briefly how they might

be integrated together using the expanded model (Element 4).

• Finally how broad definitions and concepts have lead to interesting ecological and systems-

based models that are or could be used as policy frameworks for environmental health

(Element 6).




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4. Concepts and Definitions

4.1 Need for Concepts and Definitions

All sciences have certain core questions that they constantly return to. In physics they are about

the nature of matter. In biology they are about the nature of living organisms. Similarly for

epidemiology our questions relate to our conceptions of health and disease and how we should

look at them at an individual and population level.

Epidemiology is generally defined as “the study of the distribution and determinants of health-

related conditions or events in a defined population and the application of this study to the

control of health problems.” 16

Every so often there is a debate started within a scientific community about what its purpose is

and where it should be going. In epidemiology, these in their essence, seem to be about

different conceptions of health and disease. A number of authors have detailed a variety of

extensions and limitations to the current research effort and body of knowledge. Krieger has re-

articulated and advanced the model of the web of causation and attempted a revised model that

she terms an “eco-social framework” 17 . Wing and Pearce have argued for a broader framework

where epidemiologists deal much more with social, cultural and economic determinants of health

and disease 18,19 . Rose has argued for a population-based approach while Brown has advocated

for “lay epidemiology” where citizens and residents actively participate in the research

process 20,21 . Others have talked about using “upstream” as opposed to “downstream”

approaches in research and policy 22 . Taubes and Shy have catalogued some of the limitations of

current epidemiological methods and approaches 23,24 . Importantly McMichael has explored and

highlighted the need for incorporating global environmental factors by taking an “ecosystems

approach” 25,26 .

Susser and others have argued that concepts of health and disease have framed paradigms of

theory and action in epidemiology since the 19 th century 27,28 . How the idea of miasma shaped the

sanitation movement of the 19th century. How idea of the germ changed this focus to the




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individual, the search for Koch’s ‘magic bullets’ and away from population-based approaches to

understanding and intervening on diseases in communities. How this gave way in the 1950’s to

the idea of the ‘black box’ of multifactorial aetiology and how new ecological ideas are likely to

lead to a future “eco-epidemiology”.

These perspectives have their critics but at the heart of the debate is the common thread of

deciding how we should conceive of health and disease and hence what kind of frameworks,

theories and models of reality we should develop to understand and explore them 29,30,31,32,33 .

What I want to briefly explore here is: what our current definitions are; what new ones have been

developed that attempt to more adequately incorporate the complexity of health and disease;

and what the problems with these definitions are.

4.2 Definitions in Epidemiology

The standard WHO definition of health is that “health is a state of complete physical, mental and

social wellbeing and not merely the absence of disease or infirmity” 34 .

Jedrychowski and Goldsmith have stated that “health is a relative state, the baseline from which

disease is measured, and in theory this would be the optimum state of the organism” 35 .

The problem with most broad-based definitions of health is that they are difficult to operationalise

i.e. to use in practice as a framework for research. In research a definition-concept is needed

that allows health to be measured. Hence in epidemiology we find that most measures of health

are actually measures of disease e.g. mortality and morbidity, since it is easier to say what

health is not than what it is. This is compounded further by the problem that there are many

cases where there is no clear distinction between normality(health) and abnormality(disease) for

some measures e.g. blood pressure, organ function etc. Hence the importance of accurate

classification in terms of strict diagnostic and exposure criteria in study design and analysis. So,

in general it seems that health (and disease) definitions fall along a spectrum between

qualitative and hard to measure definitions to those that are quantitative and easier to measure.

Health is therefore seen as a measurable characteristic that individuals possess, that can be




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aggregated to give a measure of the health a given population. Health seems (at least in

everyday terms) to be a thing, a property of an organism that can be abstracted. Something that

could conceivably be plotted on a graph see Fig. 4.1.

Fig. 4.1: A theoretical graph of an individual’s state of health over time

Concepts define or frame the kinds of theories that are studied and developed hence with our

current ‘disease-based’ definitions the process of developing disease is seen in terms of

individual impacts and exposures as shown in Fig. 4.2.

Fig. 4.2: Process of developing disease at the individual and population levels

Individual impacts/ exposures

mum+ conception ageing death

dad

death illness

hencegene susceptibility adaptation

+ + +environment exposure disease

ageing

Population

Aggregate (sum) of individual level health/ disease

100%Health

Disease100%

conception

death

Time




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This individual focus means that factors that affect health and disease tend be classified in

simple terms such as internal and external factors as shown in Table 4.1.

Table 4.1: Internal and external factors that influence health and disease.

INTERNAL FACTORS EXTERNAL FACTORS

Genetic

Immune

Psychological

Other Systems

Unknown

Microbes/ Parasites/ Living Organisms

Chemical

Geophysical

Physical Injury

Nutritional & unknown

This brings us to the concept of population and what we mean by this term. The debate has

centred on whether populations should be treated as simply aggregations of individuals or

should be seen as systems made up of individuals that have complex relationships and

interactions with each other 18,19 . The implication being that we need to focus on other population

characteristics than those currently being studied. The complex-systems framework-model

described later emphasises this point by showing that populations are more than a collection of

individuals and hence there are population level characteristics that ‘emerge’ whenever

organisms are grouped together and these properties cannot be inferred from the individual level

characteristics of the organism concerned. Another way to put this is that populations are more

than the sum of the individuals that make it up.

4.3 Newer and More Encompassing Definitions

With the production of the Ottawa Charter and WHO initiatives such as the Healthy Cities

Programme newer definitions of health are being framed 36,37 . In these definitions health is seen

as resource rather than as a potential, a process, a set of complex relationships that an

individual or population has with their surrounding environment, not a thing apart but “a pattern

that connects” 38,39 . These definitions have been used and developed in the public health policy




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arena and especially in health promotion. This has led to the development of models like that

shown in Fig. 4.3 8.

Fig. 4.3: The Mandala of Health (Hancock, T 1985) 8

4.4 Problems with Definitions

The three major problems with these definitions are: firstly, the difficulty in operationalising them

for research; secondly, the difficulty in visualising and modelling these kinds of definitions and

concepts in terms of theoretical insights; and thirdly, these definitions tend to be placed in an

oppositional, antagonistic framework when compared to each other – they are treated as either/

or definitions rather than both being seen as having validity and usefulness depending on

context i.e. that they are part of a spectrum of concepts and definitions that are useful for

different tasks and approaches.

4.5 Implications

The question therefore is could a framework be developed that allowed both types of definitions

to co-exist and be placed in context. In the next section I attempt to do just this.

Before we move on there is also another important definition in epidemiology and environmental

health and that is the definition of the environment. What is the environment? As with health and

disease there are a lot of differing definitions and conceptions. Again the same problems crop




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up, the difficulty of using broad definitions in practice, the use of direct exposure-outcome

models excluding more complex aspects of the environment and the use of differing,

antagonistic definitions in other disciplines that are involved in health and environment issues 40 .

The issue of the environment will be covered later.








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• It is not necessary to understand all the causal mechanisms in their entirety rather

epidemiology and public health can work on and use those aspects that are easier to know or

modify.

• Rather than being used to provide explanations of causal links, the web model has been

used to depict and study the narrow relationship between distinct risk factors nearest the

outcomes of interest.

• Theories explain why phenomena exist and why they are inter-related while models attempt

to portray how these connections occur and are usually constructed with elements and

relationships specified by particular theories.

Krieger goes on to describe what she terms an ”eco-social” framework. What I would like to

explore is the development of an expanded model of the web of causation that allows the

integration of a variety of perspectives and that could be a framework-model for Krieger’s ‘eco-

social framework’.

The development of this expanded framework-model arose from a number of limitations that I

perceived of the web of causation. These are:

• Its two-dimensional and linear quality.

• It static nature that does not seem to incorporate a time element.

• All models are abstractions of reality but risk factors are an especially high level of

abstraction.• It collapses different levels of understanding that most of the authors quoted above have

called for. Hence social factors impacting on health are on the same level as infection by

micro-organisms.

5.2 Expanded Complex Systems Framework-Model

The expanded framework-model that I would like to propose is shown in Fig. 5.4.




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Fig. 5.4: Expanded complex systems framework-model of the levels of understanding &

interaction of factors affecting health and disease.

NODErepresents anycoherent entitythat forms partof a system

Exposure6. LEVEL OF

EXPOSUREOUTCOME

CONFOUNDER

5. LEVEL OF

NETWORK/ WEBOF CAUSATION

4. LEVEL OF

NETWORK/ WEBOF CULTURE

3. LEVEL OF

NETWORK/ WEBOF SOCIETY

2. LEVEL OF

NETWORK/ WEBOF LIFE

1. FLOW OFREALITY IN THE

SPACE-TIME CONTINUUM

INTER-LEVEL2-wayconnectionsrepresentingrelationshipsbetween nodesfrom differentlevels

WITHIN LEVEL2-wayconnectionsrepresentingrelationshipsbetween nodesat the same level

NODE represents risk/ protective factorsor and outcome ofinterest

Outcome

Confounder

ARROW OF TIMERepresents theabstraction process




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5.3 Workings of Complex Systems Framework-Model

• Each node is not fixed but represents some entity that can be seen in a coherent manner

from organisms and inorganic molecules to aspects of social structures and ideas.

• The framework-model allows the ability to zoom to different scales hence at the level of the

network/ web of life a node can represent an organism and within that node other nodes

could represent aspects at organ, cellular or molecular levels see Fig 5.5.

Fig 5.5: Different scales or levels that nodes can represent.

• The connections also occur between and pass through levels.

• The levels can be changed, narrowed, reduced or increased.

• The major conduit that connects the three levels of life, society and culture is the brain-mind

that binds the biological, social and cultural together.

Explanation of the levels as shown in Fig 5.4:

1. Flow of Reality: As stated earlier all theories, models and frameworks are abstractions and

hence simplifications of reality. Hence the ‘flow of reality’ in the space-time continuum is the

base from which we take our observations and for which we develop our ideas. Hence the

arrows in the diagram represent levels of abstraction. At the first level we have the network of

Organism levelnode

Organ levelnode

Cell level node




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life, society and culture. The next level of abstraction is that of the web of causation. While an

even higher level of abstraction is the exposure-outcome-confounder model.

2. Network of Life: The network or web of life is a visualisation of the interconnections and

interdependent relationships that living organisms have between themselves and the

inorganic world around them. (stratosphere -biosphere-lithosphere).

• This level places the molecular on the same level as the global ecosystem. They are both manifestations of life

and are more a matter of scale - the micro and the macro- at one level rather than different levels one on top of

the other 38 .

3. Network of Society: The network of society is the level at which humans have added social

systems and processes (social organisation, technology, political and economic systems and

processes, etc.) upon existing natural systems and processes (evolution, ecosystems, etc.).

• At this level theories such as social cohesion, income inequality, and psycho-social factors may be placed.

4. Network of Culture: The network of culture is the level that encompasses the

interrelationship between individual and population worldviews, values, ideas, knowledge,

ethics, beliefs, perceptions, ideologies, religions, etc. that shape human behaviour and hence

social and natural systems.

5. Web of Causation: This is the level of the web of causation which abstracts nodes

perceived of as individual risk or protective factors from the earlier three networks and linksthem to other nodes which are outcomes of interest.

6. Standard Model: This is the standard exposure, outcome and confounder model used in

study design and analysis (the agent-host-environment model fits here as well).

The advantages of the framework-model are that:

• It is a dynamic 4-dimensional network in space and time.

• Moves beyond an exposure-outcome model or a multifactorial exposures-outcomes model

towards a more integrated approach that encompasses both the ‘reductionist’ biomedical

approach and more systems-based ‘ecological’ approaches.

• It is flexible in allowing nodes to represent differing entities at various levels.

• Allows networks of relationships and impacts to be visualised. Though it is crude at the

moment it has the potential to be refined.




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• It shows how relationships can not only change over time but that the complex network of

relationship is unlikely to be exactly the same for different populations. Hence relationships

and interactions are context-specific, a point argued by Wing and Pearce 18,19 .

5.5 Examples of the Utility of the Complex Systems Framework-Model

How this framework-model might work in practice is shown in Fig. 5.6 and Fig. 5.7 though they

are crude development and there is not time to develop it further in this project.

Fig. 5.6: Generalised example of expanded model in action.LEVEL OF


LEVEL OF


LEVEL OF

NETWORK/ WEBOF LIFE

Organism

LEVEL OF

INDIVIDUALORGANISM

Organ/ PhysiologicalSystem

Cell

Gene/ Molecular level




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It is important to note that the levels are only one on top of each other for clarity and

convenience and in reality there is no necessarily permanent hierarchical relationship between

the levels described above. Though having the network of life at the base does incorporate the

value and idea that social and cultural systems are built upon natural ones.

Secondly, the diagram shows that ideologies, values and perceptions impact on social,

economic and political systems which in turn impact on human populations and natural

ecosystems. Hence relationships and impacts can go from the molecular to the global and from

the biological to the cultural and vice versa. Also, perhaps more importantly ideologies, values

and perceptions occur in certain social, economic and political contexts which themselves are

placed in wider local and global natural ecosystem contexts.

Fig. 5.7: Crude example of smoking and air pollution using the expanded model.

LEVEL OF


LEVEL OF


LEVEL OF

NETWORK/ WEBOF LIFE

Individual

LEVEL OF

INDIVIDUALORGANISM

Lung/ RespiratorySystem

Lung Cell

Gene/ Molecular level




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5.6 Some General Properties of Complex Systems44

The expanded complex systems model is a network of complex systems whose general

properties include:

• Like a cell or person it behaves as a unitary whole, maintaining its identity in space, resisting

dissolution…neither a thing nor a concept but a continual flux or process.

• Higher-level complexities cannot be inferred by lower level existencies without actually

watching/playing out the network in space and time hence society and social organisation

cannot be inferred from individual humans neither can population properties like herd

immunity. Hence populations are not aggregations of individuals but are complex network

systems see Figs. 5.8 and 5.9.




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• Chains of causation are linear, sequential and fixed while Nets/Webs of causation are non-

linear, parallel and in flux.

Four important general characteristics are:

1. Absence of imposed centralised control.

2. Autonomous nature of nodes.

3. High connectivity between nodes.

4. Webby, non-linear causality of peers influencing peers.

• Systems are collections of many autonomous nodes that react to internal rules and their local

environments, are highly connected, form smaller peer networks within the overall systemand the control/management of the systems is distributed throughout the system.

• Systems produce nested hierarchies that occur from bottom up and can be visualised as a

“chunking” of nodes i.e. nodes with greater and/or specific types of connection that can be

seen as distinct sub-systems.

• Systems have complex feedback loops that encompass all the nodes in the system hence

causality is difficult to abstract out.

The advantages and disadvantages of complex systems is shown in Table 5.1

Table 5.1: Advantages & disadvantages of complex systems compared to linear systems

ADVANTAGES DISADVANTAGES

• Adaptable

• Evolvable

• Resilient

• Boundless

• Novelty

• Non-optimal

• Non-controllable (but can be guided)

• Non-predictable (in the medium/long term)

• Non-understandable (i.e. completely because of

circular/horizontal causality due to complex feedback

loops)

• Non-immediate (incorporates time)




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Three general properties of node connections are:

1. Number of connections per node

2. Connectance i.e. strength of coupledness between pairs of nodes, strength of association.

3. Type and quality of connections e.g. informational, energy, etc.

5.7 Development of Expanded Complex Systems Framework-Model

The ideas and expanded framework-model developed here are a tentative first step towards

producing an integrated framework and it is important to remember the words of G. Davey

Smith 45 :

“Leaping forward to the big picture of how it all fits together

represents an attractive alternative to merely continuing with this laborious spade work.”

Though Davey Smith was criticising certain approaches in the development of psycho-social

theories of health and diseases it is a valid and important point. However, it is important to

attempt the development of flexible frameworks and models that look at how the various

theories and knowledge’s derived from research might fit together as they may provide greater

insights even if the framework-model is flawed. The complex systems framework-model may

have the potential to allow us to do this.

The metaphors, frameworks and models we use are at the heart of the process of knowledge

formation. Hence their implications ripple through the process and the other elements. Models

are “a tool that helps us typify and clarify the way we think about certain phenomena and the

intrinsic and extrinsic relationships with other phenomena.” Hence “presenting models in

simplified form encourages scientists to be more explicit about their assumptions and

expectations, thus playing an important role in hypothesis generation, testing and further

refinement.” 40 The same can be said for metaphors and frameworks.

Hence complex systems framework-model could act as a primary framework for epidemiology

and help explain more clearly the current debates in terms of it being about the kinds of nodes

and connections we are examining and whether we should be looking at other nodes and other




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types of connections that are more likely to provide us with a richer and deeper understanding of

health and disease. It could act as the primary general framework into which all or most other

frameworks and models could be fitted into. The complex systems framework-model could allow

us to map out what nodes and connections are being examined and which are being ignored

and whether the reasons are scientific (in terms of nodes that are easier to study and

connections that are easier to modify or intervene on, etc.), social (in terms of acceptability to the

public, etc.), economic (research funding cycles and fads, etc.) or political (in terms of fitting in

with current political ideologies, etc.)

The implication for research is to allow a more complex and coherent framework-model to be

envisioned which shows and allows for the validity of current (and future) techniques and

methodologies whilst also allowing for a broader and more diverse range of factors that impact

on health and disease to be explored.

It could also allow us to explore how the major theories of health and disease might fit together.

Though this task is beyond the scope of this project I do attempt to list the major theories of

health and disease later.

Lastly, it also has the potential to act as a primary framework for environmental health which is

also discussed later.




Page 29

6. Methodology and Research

The issues in this area are well-covered in the literature and include issues of concepts,

definitions, models and methodology in the design, statistical analysis and interpretation of

studies and hence will only be touched on briefly 46 .

There is however the important question of how different concepts and models of health and

disease would change research and methodology. In answer, as stated earlier, it is likely to

change the type of research questions asked and the subject area of any research but it is more

problematic to answer whether it would change current approaches in methodology and

analysis. My tentative conclusion is that at this level it would provide a more coherent framework

but not change the methodology fundamentally though newer techniques and rigorous

qualitative research is likely to provide insights not found in existing quantitative methods 47 .

However there has been discussion by Wing, Pearce and McMichael about whether

epidemiological studies are studies of populations or aggregates of individuals. Are we seeing

populations as collections of individuals without considering the complex relationships that they

have between each other and other systems (e.g. social, economic, environmental ). That

populations are context specific groups that have dynamic changing relationships within them

over time and hence a history of experiences that extends into the past 18,19,25 .

There has also been a reappraisal of the role and value of ecological studies as an important

and vital part of epidemiological thinking 48,49,50,51 .

Finally there has been growing literature on the value and limitations of new molecular biological

techniques that could enable us to develop biomarkers that more accurately measure exposure

and disease 52,53 .

More concretely our current research answers give rise to multi-factorial associations between

each factor and a given outcome/ outcomes of interest. In cohort studies we get Fig. 6.1.




Page 30

Fig. 6.1: The exposure outcome relationship in a cohort study

While in case-control studies we get: Fig. 18.

Fig. 6.2: The exposure outcome relationship in a case-control study

The questions is can we map the information on associations and link them up so that we can

see visually the interaction between exposures and outcomes i.e. a multi-part web of causation. I

think so, and a general example of one part of this kind of map is shown in Fig. 6.3.

Fig. 6.3: Visual mapping of one set of exposure, morbidity and mortality associations

Exposure

Outcome 1

Outcome 2

Outcome 3

Outcome 4

Time Flow

Outcome

Exposure 1

Exposure 2

Exposure 3

Exposure 4

Time Flow

Exposure 1

Morbidity 1

Exposure 4Exposure 2

Exposure 3

Morbidity 2 Morbidity 3

Mortality

interactionsbetween exposures

association betweenexposure & morbidity

association betweenmorbidity & mortality




Page 31

7. Theories

“Theories are not about truth, they are about explanation and must be judged by their utility.”40

“all theories are wrong which promote, justify, or tolerate injustice.”75

Going back to Chapter 1 Fig. 2.1 the levels of explanation and knowledge in science was framed

in terms of the discovery-production of empirical laws and laws of nature. Stretching these ideas

we could say that association in epidemiology are analogous to empirical law while causation is

analogous to laws of nature in the physical sciences. Of course the degree of provisionality in

epidemiology is overall much greater than that in the physical science.

There are two important issues to be considered here: first as stated in the background

summary Krieger has argued for the development of epidemiologic theory and secondly on

attempting to integrate and fit together the current theories of health and disease into a coherent

framework.

7.1 Conceptual and axiomatic foundations of Epidemiology

There has been some work done on systemising epidemiology and providing some conceptual

and axiomatic foundations by Lower 54 . Lower and Karanek then go on to develop a ‘unified’

criteria of causality applicable to infectious and neoplastic (chronic non-infectious) diseases that

provide a different perspective from the more well known Bradford-Hill criteria 55,56 . Interestingly

they state four axioms and their corollaries that they feel are the foundations of epidemiology as

shown in Table 7.1.

Table 7.1 Axiomatic foundations of Epidemiology

Axiom 1: Disease exists in human populations as a result of antecedent causes.

Corollary 1: Antecedent causes are actual and necessary.

Presupposition 1: Antecedent causes occur as a result of cultural-environmental characteristics.




Page 32

Axiom 2: Disease is distributed non-randomly in human populations.

Corollary 2: Non-random aggregations of disease are a manifested along axes of measurement in spaceand time and in relation to cultural-environmental and host biological characteristics.

Presupposition 2: Variations in the incidence of human disease occur in response to variations in the intensity ofexposure to causal agents and/ or variations in the susceptibility of individuals to the operation ofthose causes.

Axiom 3: Disease is manifested non-uniformly in individuals in relation to variable underlyingprocesses and mechanisms of pathogenesis.

Corollary 3: Disease processes and mechanisms are initiated by actual and necessary interactions of causalagents with host tissues and are manifested over a spectrum of host responses in relation tocultural-environmental and host biological characteristics.

Presupposition 3: Variations in the severity and extent of human disease occur in response to variations in theintensity of exposure to causal agents and/ or variations in the susceptibility of individuals to theoperation of those causes.

Axiom 4: Disease is not necessary in human populations.

Corollary 4: Disease is preventable by intervention with cultural-environmental determinants of the existenceand/ or degree of risk, and/ or intervention with host biological determinants of susceptibility.

Presupposition 4: Antecedent causes occur as a result of cultural-environmental characteristics.

7.1 Frameworks for Theory

In general the types of listing of theories of health and disease or influences on health is given in

Table 7.2 described by MacCarthy 57 . MacDowell shows a framework that is similar see Fig.

7.1 58 . Krieger describes MacKeown’s ‘evolution, adaption and man-made environment’

framework and its counterpart that explores the areas not covered by MacKeown’s framework

‘social and political determinants’ framework that emphasise the political economy of health and

the social production of disease 17 . While Pederson has attempted a chronological view of the

types of theories that have emerged over the last century or so 59 .

Table 7.2 Four major influences on health

1. Genotype/ inherited health potential or human biology = internal aspects

2. Individual behaviour/ lifestyle

3. The socio-economic and physical environment = factors outside the body over which the

individuals has little control.

4. Health and medical services or the health care system.




Page 33

Fig. 7.1 Influences on Health and Disease (MacDowell ME, 1987)

However the attempts at a framework in table 7.2 and Fig. 7.1 concentrate on the individual

rather than the population level and are not an attempt to look at and see how we might fit

together the various theories of health and disease and examine how they might be seen as

parts of a coherent whole.

Looking at the Table 7.2 specific factors like genotype are listed with the wide ‘all-encompassing’

factor of the socio-economic and physical environment. As Tesh has criticized what exactly do

we mean by the social or economic environment. What parts or aspects of it are causing a

specific disease? 32 A first step would be to list the kinds of theories that are currently in use and

are acceptable, this I have briefly attempted and is shown in Table 7.3

Table 7.3 Partial list of some of the theories about health and disease

• Genetic• Lifestyle• Physical Environment• Social Environment• Mutation• Germ/ infectious agent

• Health Care Provision• Social production of

Disease• Biomedical• Psycho-social• Bio-cultural

• Transition theories• Early Life programming• Life events• Adaptation• • Unknown

These are just the standard theories there are also more speculative ideas such as

Antonovsky’s theory of complexity, conflict, chaos, coherence, coercion and civility or Barke and




Page 34

Potter’s ideas about freedom and responsibility 60,61 . Unfortunately there is not time or space to

give a brief summary of each of these theories and attempt to look at them in a more systematic

and coherent manner. However the complex systems framework-model could be used to see at

what level specific theories are acting and how they link the various levels. As an example

psycho-social theories of disease link social organisation and environment with biological

processes through the means of psychological processes such as stress.




Page 35

8. Mathematical Models

Again I will touch upon this element only briefly. This area includes the modelling of infectious

disease transmission from malaria to AIDS as well as newer integrated systems- and scenario-

based modelling such as those for climate change impacts on malaria transmission and

increases in skin cancer rates from ozone layer depletion. A conceptual representation of a

modelling framework for looking at the impact on population health of climate change is shown

in Fig. 8.1 62 .

Fig. 8.1: Conceptual representation of the modelling framework for the health impact

assessment of man-induced atmospheric changes (MIASMA)

The most important consideration in the development of mathematical predictive models is the

underlying cumulative increase in uncertainty at each step in modelling process see Fig. 8.2 63 .

Fig. 8.2: Layers of uncertainty underlying climate change impact assessment.

(due to the complexity and range of relationships and connections within and between the dynamic complex systems that have an impact

on health)




Page 36

9. Environmental Health Frameworks

9.1 Definitions of the Environment and Environmental Health

The environmental health framework (generally the health framework) element straddles both

the research and the policy area. Research probably has the greatest impact on policy in that it

can assist in the development of a knowledge-based framework for policy development.

However this is at the very least a diffuse and crooked pathway if not deeply problematic

process 15,64,65 .

In this section I will concentrate here on frameworks for environmental health. Environment has

been defined in as many ways as there are disciplines working on the subject see Fig. 9.1 66 .

Fig. 9.1: Layers of uncertainty underlying climate change impact assessment.

McMichael has described the environment as minimally being “the physical and chemical

conditions in the living space around us such as the quality of local urban air, freshwater

supplies and the concentrations of chemical residues in food” while a more broader definition

“includes the conditions of the social environment ... encompassing housing quality, transport,

recreational amenities, population density, social networks and political and distributive equity” 67 .




Page 37

Moeller has defined the environment into four categories 68 :

• the inner vs. outer environments,

• the personal vs. ambient environment,

• the solid, liquid, and gaseous environments and

• the chemical, biological, physical and socio-economic environments.

Eyles has argued that definitions are about core values and life concerns, hence environment

can be seen be viewed from three perspectives: cosmic (where there is a magical and mystical

relation between environment and gods to ensure harmony and order in the cosmos); machine

(where there are interdependent, repairable parts the stability of which is ensured by their

predictability); and the organic (argues for a dynamic self-regulatory entity the health of which isdetermined by a balance of diverse elements and encompasses the ‘ecosystem’ perspective) 40 .

Similarly environmental health has been defined in diverse ways. Eyles describes environmental

health as “the health and wellbeing of human populations in specific environments (physical,

social, and societal).... the relationships between environment and health are multi-directional,

and that just as environments affect human health so too do issues of human health and

wellbeing affect environments.” 40

One of the WHO definition of environmental health which includes these words environmental

health includes “….the effects (often indirect) on health and well being of the broad physical,

psychological, social and aesthetic environment, which includes housing, urban development,

land use and transport” and goes on to say “the environment should be considered as a

resource for enhancing health and well being. People aspire to live in communities free of

environmental hazards, with decent homes in which to raise their families, with opportunities for

employment, education and culture, and with pleasant and harmonious surroundings that

facilitate recreation and social intercourse. Effective environmental protection in its widest sense,

provides a framework for many of these aspirations as part of enlightened and sustainable

socio-economic development.” 69




Page 38

Definitions are important in framing issues and in giving a complete global perspective of what a

concept means and what is aimed for. Having a broad context then allows a narrower strategy to

be followed without the loss of perspective on the critical issue.

Eyles shows a particularly interesting example of this because he then proceeds, using a

medical geographic perspective, to develop five building blocks through which we can look at the

relationships between environment and health as shown in Table 9.1 40 .

Table 9.1 Five integrated building block for environmental health knowledge and research

BUILDING BLOCK ONE USEFULTHEORY

ILLUSTRATIVEEXAMPLE

ONE SUGGESTEDRESEARCH TOPIC

1 Language & Perception Symbolic Interactionism Risk, Anxiety,Uncertainty

Language & perceptionof environmental risk

2 Agency & Negotiation Structuration Lay beliefs and actions ineveryday life

Living in a stigmatisedcommunity

3 Structure & Power Structuralism &Poststructuralism

Conceptual & MaterialDomination

“Environment” & “Health”

4 System Integration Functionalism FunctioningEnvironments

Consensus & conflict inenvironmental healthpolicy

5 Ecosystem &Wellbeing

Ecologism Environmental qualitydefinitional questions

Connecting ecosystemand human well-being

9.2 Existing Frameworks and Potential Limitations

Quantitative Risk Assessment (QRA) and management is the cornerstone of much work in

environmental health. It is an important and valuable technique however there is a need for a

broader framework that encompasses QRA and goes beyond it 70 . O’Riordan has described one

way of looking at how the risk assessment and management process works 71 .

This is where the complex systems framework-model described earlier is likely to help as there

seems to be at the very least some confusion if not lack of a coherent framework in current work

in environmental health as exemplified by the WHO summary document “Concern for Europe’s

Tomorrow” 69 . Perhaps it is a little unfair to take look at the subheadings of two sections of the

document namely “Effects on Health of Environmental Exposure” and “Environmental

Exposures” however they are instructive in highlighting some contradictions and perhaps




Page 39

deficiencies in existing frameworks see Fig 9.2.The WHO is an important international health

agency and as such its ideas and documents have a high degree of credibility, distribution and

impact around the world.

Table 9.2: Subheadings in two sections of Concern for Europe’s Tomorrow Summary

Document

Effects on Health of

Environmental Exposure

Priority Issues Environmental Exposures

• Cardiovascular disease

• Cancer

• Respiratory Diseases

• Communicable Diseases

• Injury & Poisoning

• Nervous System & Mental

Disorders

• Musculoskeletal Disorders

• Birth Defects & Reproductive

Effects

• Wellbeing

• Effects on health of non-

environmental factors

• Lack of information about

environmental health

• Microbiological contamination of

water and food

• Air Pollution

• Road Traffic

• Housing & Urban Development

• Transboundary Issues

• Air Quality

• Water Supply & Quality

• Waste & Surface water

• Wastes

• Contamination of food & drink

• Selected Chemicals

• Ionising Radiation

• Non-ionising Radiation

• Residential Noise

•

Housing & the Urban Environment

(aspects of exposures presented earlier in

table)

• Occupational health

• Accidents & man-made disasters

• (psychological overload)

• (physical workload/ ergonomic conditions)

• (allergens)

There seems to be three important problems with this listing which makes it contradictory and

perhaps shows that a coherent framework was not followed. The first point is that air quality and

water quality are mixing two issues together. The chapter is on environmental exposures and

hence on the whole should either be a listing of specific exposures that are hazardous to health

that produce the specific conditions mentioned in the earlier chapter on “Effects on Health of

Environmental Exposure” or be broader-based “social, economic, and political” exposures and




Page 40

their more indirect effects. Air and water quality is actually talking about contaminants in air and

water rather than the ‘natural’ components of the air and water being hazardous. Hence perhaps

a better framework could have been the one outlined below in Fig. 9.2.

Fig.9.2: Revised layout and framework for looking at the effects of environmental

exposure

TYPES OF EFFECT

• Cardiovascular Disease

• Cancer

• Respiratory Diseases

Effects on health of non-environmental

factors

• Communicable Diseases

• Injury & Poisoning

• Nervous System & Mental Disorders

• Musculoskeletal Disorders

• Birth Defects & Reproductive

Effects

• Wellbeing

•

ROUTE OF TRANSMISSION

• Air (pollution) • Water (contamination) • Soil (contamination) • Food (contamination)

TYPE OF EXPOSURE

• Selected Chemicals

• Ionising Radiation

• Non-ionising Radiation

• Residential Noise

• (psychological overload)

• (physical workload/ ergonomic conditions)

• Housing & the Urban Environment (aspects of

exposures presented earlier in table)

• Occupational health

• Accidents & man-made disasters

• (allergens)

• Waste

SOURCE OF EXPOSURE

• Manufacturing Industries

• Service Industries

• Agriculture & Agricultural Practices

• Transport Usage

However, this still leaves the second more important point that radiation is considered in the

same breath as housing and the urban environment i.e. complex issues like housing and urban

environment seem to be reduced to the same level as dealing with radiation exposure. Clearly

they are not in any sense a similar level or type of exposure because housing and urban

environments covers a diverse range of factors social, political and economic that impinge on

health. The question is why was this done?




Page 41

There could be two general answers, firstly that environmental exposures are not being seen in

a coherent ecological and complex systems framework and/ or secondly that political factors are

implicated in the broader determinants of environmental exposures and that this was a

roundabout way of dealing with this fact. These could be internal WHO factors or more general

international political factors.

Thirdly, in the list of priorities though mention is made of lack of information on environmental

health no mention is made of a framework for it. So no framework is suggested either for the

information that would allow for a proper and adequate use and assessment of the value of the

information. Nor in the broader terms of a framework for creating policy and managing

environmental health intervention programmes. An example of an informational framework is

shown in Fig. 9.3 and one for developing, managing and more broadly looking at environmental

health programmes is shown in Fig. 9.4 72,5 .

Fig. 9.3: Framework and concept of the environmental health matrix




Page 42

Fig. 9.4 A systems-based view of environmental health

9.3 A Complex Systems Framework

The general complex systems framework-model can act as a primary framework for

environmental health and this is shown by the framework already developed by Schaefer see

Fig. 9.4. What is interesting is that there seems to have been no development of Schaefer’s

perspective since he first described it 73 . This framework echoes the structure of the complex

systems framework-model described earlier and hence can and should be developed further

and is likely to provide useful insights into environmental health issues and problems at the

research and intervention levels.

However environmental health also involves policy-makers and communities in its work and

Schaefer’s framework is likely to be too complex to use when communicating with these groups

in the policy framing and formulating process. Hence a simpler version of this framework can be




Page 43

developed from the complex systems framework-model which is shown in Fig. 9.5, Fig. 9.6 and

Fig. 9.7.

Fig. 9.5: Two-dimensional version of the complex systems framework-model

Figs. 9.5 shows in simpler form the way local ecosystems, societies and cultures are embedded

within larger global systems and this links to Fig. 9.7 (page 43) which shows the systems that

need to be considered when assessing environmental health at a local and global level.

Fig. 9.6: Simple framework-model of the interactions between natural systems, social

systems and cultural systems






Page 45

A proper development of Schaefer’s framework or my own simpler version is beyond the scope

of this present projects but I do feel that the merits of a systems-based perspective are clear

especially in visualising interconnections and hence in the communications and interactions of

researchers, policy-makers and communities with each other.

Using a common framework across research, policy-making and affected community

boundaries can ensure that each set of ‘actors’ in the process see the differing but valid

perspective of the other actors. Hence there is likely to be less misunderstanding as the views of

each of the participants can be taken into account. This is likely to lead to greater trust and

cooperation between actors and stakeholders and perhaps more importantly it also begins to

educate policy-makers and communities about the complexity, difficulties and hence limitations

of research and hence its provisional nature.








Page 48

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Documents

Conceptual Issues in Environmental Epidemiology and Environmental Health