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DOI: 10.1177/0309132509336026

Progress reports

Health geographies I: complexity theory

and human health

Sarah Curtis* and Mylène Riva

Department of Geography, University of Durham, South Road,

Durham DH1 3LE, UK

Abstract: This paper is the first of two linked progress reports on the application of ideas from

complexity theory to health geography. In this paper we focus especially on research which seeksto explain variations in human health from a geographical perspective. We mainly discuss selected

studies of geographies of human health which illustrate how ideas from complexity theory are

applied empirically. In order to interpret more effectively the dynamic and recursive networks

of relationships anticipated by complexity theory, future research will be required to go further

in breaking down the divisions that are often assumed between research using different types of

empirical methods. We comment on the potential to do this by means of advanced approaches to

statistical and spatial modelling and by giving greater attention to the complementarity between these

methods and qualitative techniques. We also discuss the emphasis in these examples on research

which adopts an interdisciplinary strategy. Our conclusions refer forward to our companion report,

which focuses more on studies of geographies of health care and health policy, emphasizing that

complexity theory applied to health systems underlines the connections between health, health

care and health policy.

Key words: complexity, health, health geography, inequality, methods.

*Author for correspondence. Email: [email protected]

I Introduction

This paper is the first of two reviews of recent

progress in the application of ideas from

complexity theory to health geography,

focusing especially on developments in the

period since Gatrell’s critical assessment of

the state of the art (Gatrell, 2005). In this

paper we mainly discuss geographies ofhuman health, while our next progress report

(Curtis and Riva, 2009) focuses more on

geographies of health care and health policy.

Our conclusions to the second report,

however, emphasize that complexity theory

leads us to pay greater attention to the con-

nections between these three ‘fields’ of

interest for health geographers.

Gatrell (2005) commented on the growth

of interest in complexity theory in the social

sciences and discussed the potential of these

ideas for geographies of health. He pointed toa new research agenda, which would include

a move beyond abstract theorizing towards

greater emphasis on empirical applications of

complexity theory in areas such as disease

Progress in Human Geography 34(2) (2010) pp. 215–223

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216 Progress in Human Geography 34(2)

ecology, diffusion of health-related pheno-

mena and health inequality. We discuss below

some of the ways in which recently pub-

lished research on geographical aspects of

health has responded, directly or indirectly,

to this challenge. An interdisciplinary vision is

one of the key features of complexity theory(Waldrop, 1992), and some of the examples

reviewed illustrate how geographical ap-

proaches relate to work in other disciplines

concerned with aspects of human health.

We do not intend here to offer a compre-

hensive review of complexity theory as it

is applied in geography more generally (for

detailed overviews, we recommend to the

reader existing reviews by, for example,

Reed and Harvey, 1992; Thrift, 1999;

Manson, 2001; O’Sullivan, 2004; Mansonand O’Sullivan, 2006; O’Sullivan et al., 2006;

Portugali, 2006). There is a similarly exten-

sive literature which discusses the elements

of complexity theory from the perspective of

other disciplines such as sociology (Byrne,

1998; Blackman, 2006; Walby, 2007), health

and care services research and evaluation,

public health and epidemiology (Cilliers,

1998; Sweeney and Griffiths, 2002; Materia

and Baglio, 2005; Pearce and Merletti,

2006; Joyce, 2007; Lessard, 2007) andhealth promotion (Baranowski, 2006; Brug,

2006; Resnicow and Vaughan, 2006). Here,

however, we frame the discussion which

follows by summarizing the key elements

of complexity theory as they relate to geo-

graphies of health. According to the reviews

just cited, complexity theory encourages us

to consider geographies of health and health

care in terms of complex systems with the

following attributes: openness; components

with limited ‘knowledge’ of each other; self-organization; emergence; path dependence;

positive feedback and ‘lock-in’.

These attributes of health systems mean,

for example, that we should not consider

particular populations in particular places as

separate from, or closed to, the world around

them; rather they are open to external in-

fluences, which in today’s world might be

processes at the global level as well as at the

level of the society or nation in which they

are embedded. Despite this openness, the

people and the environmental attributes that

influence their health are not perfectly inter-

connected or ‘knowledgeable’ about all other

parts of the system. It is more likely that inter-actions will take place between the parts of

the system that are proximate in terms of

social or geographical position or in terms

of connectivity via communications systems.

For example, these attributes of openness

and ‘limited knowledge’ are reflected in the

propensity for communicable diseases to

spread relatively quickly among people within

the same community sharing spaces such as

home, school or workplace, but also among

those travelling between distant urbancentres tied by rapid transportation links.

Complexity theory also anticipates that

health systems are dynamic and have an

inbuilt capacity to organize and reorganize

themselves constantly (emergence and

re-emergence of human diseases being an

illustration). Every system also has a history

which influences its present behaviour, ie,

path dependence (for example, health-related

behaviours are rooted in long-established,

socially constituted practices). Thus, there islittle stability in these systems and they are in

a perpetual state of change, while sensitive

to initial conditions. The outcomes of these

processes are unpredictable so that novel,

unexpected developments emerge, giving

rise to new trajectories of growth or change,

some of which are short-lived, while others

generate ‘positive feedbacks’ that lead to

consolidation and intensification of certain

tendencies, at least until a new emergent

trend sets in (producing, for example, endemicdiseases). Some elements become ‘locked

in’ to the system and persist even though

they may no longer seem the best-adapted

structure as the system evolves (for example,

the present-day obesity epidemic arises

partly due to our genetically determined pro-

pensity to store energy as fat, which offers

advantages for survival in famine conditions,



Sarah Curtis and Mylène Riva: Health geographies 217

but can now present a risk for health in many

human societies today, where food supply

is reasonably secure and physical activity is

much less than in the past).

Furthermore, complexity theory offers

synergies with calls for health geography

to adopt a relational view of space, as inother areas of the discipline (Cummins et al.,

2007). It encourages greater sensitivity in

research to variability in time as well as space,

and envisages major trends as the outcome

of myriad minor changes and interactions in-

volving different parts of the system, including

people, disease risk factors, geographical

space, the physical fabric of health care set-

tings and health care personnel. Some

ideas in complexity theory are also broadly

compatible with theoretical frameworksoffered by actor-network theory (Murdoch,

1997), which have also been applied to inter-

pretation of health-related geographical

phenomena (Milligan, 2001).

II Examples from geography of health

risks and diseases

Geographical research on human health and

diseases is concerned with the processes and

relationships in space and time that govern

human interactions with their environmentand with each other, in complex and ‘non-

linear’ ways. Conventional disease ecology

stresses the idea of a dynamic equilibrium

between demographic, social and biophysical

factors in the environment (Mayer, 2000).

Complexity theory anticipates that such

systems may be far from stable. For example,

the diversity and interconnectedness of

human contacts is expressed in terms of

evolving ‘networks’ of open systems, through

which infectious disease diffusion operates.Also health geography continues to develop

ways to study the interactions between

processes operating at different sociogeo-

graphical scales. The emergence and resur-

gence of diseases needs to be set within

the wider context of economic, political,

social and environmental changes (Gatrell,

2005). Geographical research uses a range

of methodologies to tackle this research

agenda.

Geographers have demonstrated how, for

populations in different settings, health ad-

vantage or disadvantage can be understood

through a historically informed approach,

rather than one limited to examination ofthe immediate and localized ecological and

social circumstances associated with disease

outbreaks or sustained health disadvantage

for certain population groups. Conceptual

frameworks that are well suited to structure

this kind of thinking include political eco-

logy (Turshen, 1977; Mayer, 2000), socio-

ecological frameworks (Ali, 2004) and ‘health

histories’ (Andrews and Kearns, 2005). Polit-

ical ecology places health and diseases

within their broader political, social and eco-nomic contexts, while socio-ecological an-

alyses build on these by emphasizing the

importance of longer timescales and higher

levels of organization in the analysis of public

health issues. These frameworks assert

that health and diseases are the emergent

products of an extended set of ecological,

political, social and economic processes that

evolved over time and at different geographic

scales, and that new events can be difficult

to understand and predict. Examples includeHanchette’s (2008) application of a political-

ecology framework to explain the existence

and persistence of relatively high rates of

childhood lead poisoning in North Carolina,

which emerged from social, economic,

historical and political processes by which

local populations of African American

children came to be concentrated into older

housing with high risk of exposure to lead-

based paint.

Using a socio-ecological approach, Ali(2004) examined the events leading to an

outbreak of waterborne E. coli O157:H7,

which occurred as a consequence of eco-

logical processes (such as extreme rainfall,

factory farming, and new resistant E. Coli

O157:H7 bacterial strain) combined with

socio-economic conditions giving rise to negli-

gence in water testing, including privatization




of water management, weakening of gov-

ernment regulation, institutional inertia, and

forces operating in the global market eco-

nomy. Ali notes that the conditions giving

rise to the outbreak showed attributes of a

‘complex system’ since it emerged from in-

dependent processes unfolding at differentlevels that converged and interacted with

each other in unexpected ways to generate

new risks for health.

In a different vein, accounts by Andrews

and Kearns (2005) and Gesler (1998) are

examples of historical perspectives on the

development of certain towns with reput-

ations as healthy, healing settings, and the

intricate connections between these healthy

reputations and the social and economic

development of the towns.Geographers are also paying attention in

other ways to complex spatiotemporal rela-

tionships. For example, longitudinal study

designs, incorporating trends for both people

and places, are increasingly used to assess how

exposures to risk factors throughout the life

course may influence health outcomes. Curtis

et al. (2004) showed that socio-economic

conditions in the place of residence during

childhood showed persistent associations

with health in old age, independently of morerecent conditions. Research on migration and

health (Boyle et al., 2002; Cox et al., 2007a)

has also started to disentangle the degree to

which residential mobility may be important

for health differences between areas. To the

extent that people in good health show dif-

ferent migration patterns than people in poor

health, geographical inequalities in health

may be the result of unequal geographical

‘sorting’ of the population. The examples

cited illustrate how exposure and sensit-ivity to previous ‘hazard and risk’ conditions

may extend over the life course to influence

health and disease in ways that are consistent

with the concept of ‘path-dependence’ and

‘positive feedback’ in complexity theory.

In other research consistent with a rela-

tional view of space, connectivity is as im-

portant as distance for the diffusion and

spread of infections in human populations.

Analyses of contemporary epidemics such

as influenza, HIV/AIDS, and severe acute

respiratory syndrome (SARS) show that

transmission first occurs between highly

connected major cities around the world

before spreading more locally to the regionssurrounding the initial points of infection

(Pearce and Merletti, 2006). Emch et al.

(2008) have investigated the significance for

varying local cholera risk in Bangladesh of

connectivity of water systems, as well as con-

ditions in the immediate vicinity of each

locality.

Several authors report empirical strategies

designed to understand the links among risks

operating at different scales. To select one

illustration from a large field, a series of studieson childhood injury and accidents (reported

by Haynes et al., 2003; 2008; Reading et al.,

2008) considered risks as a function of child,

family and household characteristics, as well

as conditions of more proximal and more

distal communities. These studies showed

that risks were influenced by interactions be-

tween attributes of broader social settings

and characteristics of children, parents and

households, blurring the ‘artificial distinc-

tion between effects of ‘composition’ and‘context’ on health outcomes’ (Haynes et al.,

2008: 700). These studies also demonstrated

the significance of parental perceptions of

risk as well as the objectively measured con-

ditions, showing potential for this type of

extensive statistical analysis to complement

in-depth studies of individual risk percep-

tion and response (Christie et al., 2007;

Christensen and Mikkelsen, 2008). Research

focusing on these interactions between indi-

vidual and environmental attributes meetswith the call to ‘collapse the false dualism of

context and composition by recognizing that

there is a mutually reinforcing and reciprocal

relationship between people and place’

(Cummins et al., 2007: 1835).

Consistent with more complex theor-

ization of processes linking place to health

are recent advances in quantitative methods




of consumption and the habitus , ideas of

power relationships, social differentiation and

stigma, as well as epidemiological theories

of environmental risk factors and physio-

logical processes). Complexity theory may

increasingly use these explanatory theories

in combination rather than viewing them ascompeting paradigms.

This said, the discussion above aims to

illustrate how health geography is being

influenced by complexity theory. Gatrell

(2005: 2665) argued that ‘complexity is

about relationships that cannot be reduced

to simple linear models or their variants (such

as logistic regression). It counters much trad-

itional (geographical and environmental)

epidemiology and public health that relates

health outcomes to determinants at the indi-vidual level’ using methods assuming linear-

ity of the processes (ie, predictive methods)

giving rise to inequalities in health. If the aim

is to move away from conceptual to more

empirical application of complexity theory

in research in health geography, our meth-

odologies must continue to increase in sophis-

tication. In addition, the counterproductive

dualism between ‘quantitative’ and ‘quali-

tative’ methods will have to be abandoned

to integrate both approaches in the under-standing of the complex processes influe-

ncing population health.

All of the research discussed above reflects

the major challenges faced by geographers

and researchers in other disciplines working

on human health. Our increasing appreci-

ation of the complexity of the processes

involved highlights the limited potential for

conventional case-control studies of the type

that have conventionally been viewed as ‘gold

standard’ methodologies in medical research.It further requires that we rethink theor-

etical and empirical approaches about what

causes health variation and what might be

effective strategies to improve public health

and reduce health inequalities. Research

studies based on ‘natural experiments’ and

case studies of changes in health, as they

emerge in particular settings, may have

greater potential, but we argue that more

explicit attempts will be needed to address

directly the attributes of health and health

systems that are anticipated by complexity

theory, and summarized in the introduction

to this paper. Progress in this direction could

be made through further empirical applic-ations of complexity theory.

Our review suggests that this is gradually

being achieved through increased interdis-

ciplinarity in research on health and the ap-

plication of what have conventionally been

termed ‘mixed methods’, combining inten-

sive, qualitative and interpretative approaches

with extensive, quantitative modelling. In

fact, the theoretical basis for these methods

may be less divergent than might be com-

monly imagined given the different techni-ques employed. Arguably, there is ‘common

ground’ between, for example, Bayesian

modelling using theoretically informed prior

assumptions and research interpreting inten-

sive observations and interviews in light of

preconceived social theory. There can also

be synergies between different approaches

that are mutually reinforcing. Methods such

as multilevel modelling and geographically

weighted regression may prove helpful

in identifying specific local patterns of in-equalities in health, allowing us to identify

areas that share similar characteristics, as well

as those which differ from each other, and

showing where we need to direct qualitative

investigations of the interrelated processes

from which these inequalities in health have

emerged.

Statistical modelling techniques used in

health geography have developed signifi-

cantly in the level of sophistication that they

bring to exploration of complex relationshipsin time and space. Yet complexity theory

raises some challenging questions for ap-

proaches in health geography that proceed

using conventional assumptions that there

are certain health ‘outcomes’ which ‘result’

from the ‘effects’ of sets of ‘risk factors’ that

‘cause’ health variation. We expect further

developments to rely less on conventionally




structured statistical or non-statistical data

and a continuation of the current shift

towards methods which allow exploration

of mediating and moderating effects that

demonstrate and explain the complex causal

pathways that produce these associations

(for example, the ways in which area factorsimpact on health of individuals partly via their

effects on family processes).

Methods using multilevel structural equ-

ation modelling (Rabe-Hesketh et al., 2001)

are likely to become more widespread in

health geography to tackle these questions.

Techniques like loop analysis (Dinno, 2007)

and dynamic actor-network analysis (Titz

and Döll, 2009) are also beginning to impinge

on the field of health geography. These

techniques accept that causality does notalways flow in ‘one direction’ (ie, between

causal factors and outcomes), but that

feedback loops are recursive, so that out-

comes influence future vulnerability and risk.

Some of these techniques do not rely on con-

ventional ‘numerical’ data, although they

use computer technology. Alongside existing

software for processing qualitative infor-

mation, such as ‘NVivo’ and ‘Nudist’, com-

puterized techniques for dealing with

complicated information on human percep-tions and preferences, such as agent-based

and actor modelling, may in future be more

widely applied to the study of the rich and

complex interplay between different stake-

holders and health risks (Diez-Roux, 2008).

We also have to consider that some social

theory lacks a strong enough interpretation

of dynamic, emergent processes to help us

understand complex systems. Furthermore,

locally based intensive case studies of indi-

viduals in particular communities are notalways able to effectively situate processes

at the fine geographical scale within their

broader regional and global contexts. In our

next progress report (Curtis and Riva, 2009)

we argue that at a conceptual level this would

require more work to break down ‘sectoral’

perspectives focusing separately on health,

health care and health policy, and developing

‘whole system’ approaches that focus more

on the dynamics of ‘non-linear’ and recursive

relationships between the connected parts of

these systems.

Acknowledgement

The authors would l ike to thank Kim

Armstrong, Durham University, for her help

in organizing the material for this paper.

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