Using systems science to understand the determinants of inequities in healthy eating
Using systems science to understand the determinants of inequities in healthy eating
Sharon Friel 0 1 2
Melanie Pescud 0 1 2
Eleanor Malbon 0 1 2
Amanda Lee 0 2
Robert Carter 0 2
Joanne Greenfield 0 2
Megan Cobcroft 0 2
Jane Potter 0 2
Lucie Rychetnik 0 2
Beth Meertens 0 2
0 Funding: This research was supported by The Australian Prevention Partnership Centre through the NHMRC partnership centre grant scheme (grant ID: GNT9100001) with the Australian Government Department of Health, New South Wales Ministry of Health, Australian Capital Territory Health, HCF, and the HCF Research Foundation
1 School of Regulation and Global Governance (RegNet), Australian National University , Canberra , Australia , 2 Sax Institute , Sydney , Australia , 3 Deakin University , Melbourne , Australia , 4 ACT Health, Canberra , Australia , 5 NSW Health, Sydney , Australia , 6 National Heart Foundation, Melbourne , Australia
2 Editor: Karin Bammann, University of Bremen , GERMANY
Systems thinking has emerged in recent years as a promising approach to understanding and acting on the prevention and amelioration of non-communicable disease. However, the evidence on inequities in non-communicable diseases and their risks factors, particularly diet, has not been examined from a systems perspective. We report on an approach to developing a system oriented policy actor perspective on the multiple causes of inequities in healthy eating.
Data Availability Statement; All relevant data are within the paper
Collaborative conceptual modelling workshops were held in 2015 with an expert group of
representatives from government, non-government health organisations and academia in
Australia. The expert group built a systems model using a system dynamics theoretical perspective. The model developed from individual mind maps to pair blended maps, before being finalised as a causal loop diagram.
The work of the expert stakeholders generated a comprehensive causal loop diagram of the
determinants of inequity in healthy eating (the HE2 Diagram). This complex dynamic system
has seven sub-systems: (1) food supply and environment; (2) transport; (3) housing and the
built environment; (4) employment; (5) social protection; (6) health literacy; and (7) food
The HE2 causal loop diagram illustrates the complexity of determinants of inequities in
healthy eating. This approach, both the process of construction and the final visualisation,
can provide the basis for planning the prevention and amelioration of inequities in healthy
eating that engages with multiple levels of causes and existing policies and programs.
Systems thinking has emerged in recent years as a promising approach to understanding and
acting on the prevention and amelioration of non-communicable disease (NCDs). The interest
in systems thinking arises from the growing body of evidence acknowledging the multiple,
systemic and complex causes of NCDs; and that to address them, actions are required at the
individual and societal level [1±5]. The lack of explicit attention to the function of the system as a
whole has led public health professionals, policy makers and researchers to call increasingly for
more systems oriented analyses for public health issues [2, 6±13]. For example, the UK
Foresight study worked across sectoral boundaries to create a systems diagram of the variables that
contribute to obesity [
]. A recent study from Allender et al. demonstrated the effectiveness
of using systems methods to identify the determinants of childhood obesity within local
]. However the evidence and perspectives on inequities in NCDs and their risks
factors, particularly diet, has not been examined from a systems perspective.
An unhealthy diet is one of the top risk factors for cardiovascular disease, Type 2 diabetes,
certain cancers, and osteoporosis [16±18]. There has been a large global shift towards diets of
highly refined and often ultra-processed foods, and higher intakes of meat and dairy products
]. This transition has been accompanied by large numbers of people consuming excess
energy, contributing to overweight and obesity in more than two billion people in 2013 .
These dietary health risks are not experienced equally. In high and middle income countries,
people who are socially disadvantaged are more likely to eat unhealthy diets and have higher
levels of nutrition-related disease compared to people further up the social hierarchy [5, 22±
Research and policy approaches to diet-related health issues have, to date, given primary
emphasis to the role of individuals and their knowledge, preferences and behaviours [
more recent socio-ecological conceptualisation of dietary behaviours and inequities in healthy
eating has identified many important factors at the societal level that shape individual
preferences and behaviours [27±30]. The socio-ecological model posits that the systematic evolution,
continuation and, occasionally, improvement in the social distribution of dietary intake and
related health outcomes illustrates the influence of broader societal issues on daily practices,
such that people's ability to pursue healthy behaviour is compromised with decreasing social
status. What, where and how much people eat are responses to their economic, environmental
and cultural contexts [5, 31±34]. The limitation of the socio-ecological approach is that it does
not explicitly capture the interactions between the different factors that influence inequities in
Systems science helps organise and analyse complex information with an emphasis on the
whole picture and the interactions between variables. Systems approaches are thus well suited
to understanding public health issues, including inequities in healthy eating [35±37]. Systems
science considers an observed phenomenon, such as inequities in healthy eating, to be part of,
or emerging from, the structure of complex adaptive systems. A `complex adaptive system'
refers to a collection of elements (e.g. sub-systems, sectors) and the interconnections between
those elements that give rise to dynamic behaviour [37±39]. The adaptive part of a complex
adaptive system refers to the ability for a system to change, e.g. in response to external
]. The value of calling an observed situation a `system' is to emphasize that it is not
possible to understand the phenomena by studying its parts or elements in isolation; attention
to the dynamics between the parts is fundamental [
]. It is important to note that properties
that emerge from systems that involve humans do not do so automatically or passively; rather
the use of the term ªemergeº draws attention to the human decisions, including policies, that
have caused a system to be structured in a way that gives rise to certain outcomes, such as
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inequities in dietary behaviours. Unlike the socio-ecological conceptual approach, a systems
approach also enables consideration of feedback loops within the system that drive inequities
in healthy eating [
While some of the links between specific aspects of the food system, social and individual
level factors have been studied in detail, the interconnections between these factors and the
effects of the whole system on inequities in healthy eating have not been investigated. This
study sought to organise, from a complex systems perspective, current understandings of how
individual and societal level factors interact to create inequities in healthy eating. It also sought
to identify policy relevant factors and their dynamic interactions. This was achieved using an
established method in system science, collaborative conceptual modelling (CCM) [
develop a causal-loop diagram that is representative of a complex adaptive system. The
purpose of doing this was to understand the whole system (hereafter referred to as the HE2 system,
with the H referring to `healthy' and the E2 to `equitable' and `eating') and to begin to identify
key leverage points to more effectively address inequities in healthy eating.
In this paper we present the results of research conducted with an expert group of policy
actors (policy makers, practitioners and researchers), which is part of a larger study looking at
policy development and implementation challenges associated with action on inequities in
healthy eating. The larger study seeks to answer the overarching question `What kind of insight
can policy actors gain about causes of, and solutions to, inequities in healthy eating using
systems science methods?'
This study used qualitative methods. We have followed the Consolidated Criteria for
Reporting Qualitative Research (COREQ) checklist for reporting qualitative research [
Participants provided written informed consent to participate in this study. The study received ethics
clearance from the Australian National University Human Research Ethics Committee,
reference number 2014/343 `HE2: A systems approach to healthy and equitable eating'.
Research team and reflexivity
The study was designed and conducted by a core team (SF, EM, MP) who consulted with a
larger project team consisting of public health academics and health practitioners through the
design, data collection and analysis steps. The disciplinary backgrounds of the core team
comprised systems science, public health and epidemiology and population nutrition. EM
facilitated the CCM work and digitalised the HE2 system.
Systems methods can be both qualitative and quantitative in nature, including the formation
of dynamic systems models, causal loop diagrams, agent-based models, network analyses and
time series analyses [
]. In this study we use a qualitative soft systems method, based on the
principles of system dynamics known as `Collaborative Conceptual Modelling' (CCM), to
create a causal loop diagram relating to inequities in healthy eating [
]. The method enabled the
integration of the knowledge and experience of key stakeholders/experts from different sectors
about the drivers of inequities in healthy eating and identify relationships, feedback loops and
possible unintended consequences. We describe below the steps followed in the construction
of the diagram according to the CCM method.
Selection of key stakeholders / policy actor experts. The HE2 system and development
of the causal loop diagram was informed by a group of policy experts working in government,
non-government health organisations and academics in Australia, who were united by a
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concern for reducing inequities in healthy eating. The experts were linked by their
involvement in The Australian Prevention Partnership Centre (TAPPC)Ða national initiative
supporting the prevention of lifestyle related chronic disease through the co-production of
knowledge by academics, health system practitioners and federal and state-level policy makers
]. The experts were recruited through the TAPPC network and were selected based on their
expertise in the issue and availability for participation.
As outlined in the CCM method [
], we used an inclusive definition of `expert' to refer to
a person who has observed and thought seriously about how parts of the system relate to
inequities in healthy eating. The disciplinary backgrounds of the expert group included public
health and epidemiology; population nutrition; health economics; social marketing, and public
policy. This disciplinary diversity strengthened the likelihood of capturing a range of
perspectives in the systems diagram. Due to the challenges of creating causal loop diagrams with large
numbers of people [
], the expert group was limited to 12 people plus three members of the
core research team. This number of participants served to promote interaction and discussion
between all participants. It also facilitated effective communication between members, with a
balance of voices and perspectives being heard throughout the process of creating the diagram.
The professional roles of the participants are described in Table 1. The potential perspectives
represented in the group were not exhaustiveÐthey did not include, for example, food retailers
or manufacturers, food service providers (although two of the members previously worked in
the food industry) or the general public/consumers.
Data collection and analysis. Data were collected and analysed over two three-hour
participatory workshops±the first in May 2015 and the second in November 2015. Both
workshops were held at the Australian National University in Canberra and were facilitated by EM.
In the May workshop, participants received an overview of the project and an explanation
of system science approaches to the study of complex problems such as inequities in healthy
eating. The experts were asked to: i) discuss the problem of inequities in healthy eating and the
various factors/variables that affect it; and ii) develop their individual `mental models' and
combined `pair blended' models of connections between variables, and the nature of the
relationships between variables (see Table 2). The construction of individual mental models
Academic, public health nutrition
Academic, health economics
Academic, public health nutrition, health policy
Academic, social determinants of health, policy
Academic, public health nutrition, health policy
Academic, systems modeller
Academic, health policy and practice
Academic, child obesity
Policy officer, health promotion and public health
Policy officer, food policy
Policy officer, food policy
Policy practitioner, food and public health nutrition
Policy practitioner, health equity policy
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followed by pair blending is a distinguishing feature of the CCM method, which allows for
increasing levels of collaboration as the method progresses.
Individual mental models. Participants were required to first independently draw
diagrams of factors that influence inequities in healthy eating. The creation of individual mental
models allowed for all individual ideas and perspectives to emerge that may have been lost if
the group worked together from the beginning.
Pair blending. After the initial individual mental models were drawn, participants were
paired together and each pair were invited to combine their two individual diagrams into one.
The group then used the pair-blended diagrams to continue to combine models until a single
(extensive) mind map was achieved of the group's understanding of the influence and
interactions between different variables in the HE2 system.
After the first workshop, the systems modeller (EM) transferred all of the variables from the
individual, pair-blended, and combined group diagrams into Vensim , (which is a software
package for building a variety of simulation models, including causal loop diagrams) and
created the initial HE2 causal loop diagram (CLD). The core team reviewed the workshop notes
and the mind maps, checking that all of the connections identified in the workshop were
captured in the CLD. Groupings of variables were identified and organized according to emergent
themes (sub-systems) by members of the core team. Any changes made to the variable names
or connections generated in the first workshop were noted for discussion with the experts at
the second planned workshop.
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The same group of experts were invited to reconvene at a second workshop in Canberra in
November 2015. At this workshop, participants were reminded of the mind maps that they
created in the first workshop in May. The purpose of this workshop was to review the CLD,
check that the discussions from the first workshop were properly captured in the CLD and fill
in any gaps. The core research team explained the process they had used to create the initial
CLD derived from workshop 1, which was then presented to the group. The experts were
asked to review the CLD, add any other variables or connections to the diagram, and correct
any mistakes or misrepresentations in the way individual and pair blended maps were
reflected. They were also asked to check that the polarity of each relationship was described
correctlyÐas either positive or negative (i.e. a positive polarity refers to one where variables
change in the same direction and a negative polarity where they change in opposite directions).
Following the second workshop, the core team further refined the CLD. Variable names,
direction of linkages and polarity were discussed, and the variable groupings into emerging
sub-systems were modified to reflect the perspectives of the expert group.
The group of experts identified multiple determinants of inequities in healthy eating. These
were at multiple levels and interconnected. For example, the group identified people's food
preferences, factors in the food environment such as food price, issues of housing type, and a
range of other policy issues, including social welfare and planning. Pictures of the mind maps
as they were emerging during the first workshop are shown in Fig 1.
The HE2 causal loop diagram
After much clarification of variables, relationships between variables and direction of
connections, via email and telephone following the first workshop, and after review at the second
workshop, the final CLD was completed. The CLD (Fig 2) is referred to as the `HE2 diagram.
The HE2 diagram sets out a representation of the determinants of the social distribution of
healthy eating according to the knowledge and experience of the expert group.
The decisions about which variables are included and excluded from a causal loop or other
depiction of a system amount to the boundaries of the system [
]. The boundaries of the HE2
system were set by the expert group as they chose variables for inclusion (and implicitly,
exclusion) in the workshops and any subsequent online discussions. According to the research
team's goal of identifying public policy relevant determinants of inequities in healthy eating,
the desired focus of the causal loop diagram was to identify policy relevant factors and their
dynamic interactions. Based on this, the group opted to be inclusive of many determinants
Fig 1. An example of a policy actor mind map of the determinants of inequities in healthy eating.
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Fig 2. HE2 causal loop diagram of the determinants of inequities in healthy eating. The HE2 diagram is structured according to accepted principles of
system dynamics [
]. The arrows indicate the direction and polarity of influence. The solid lines indicate positive polarity and the dashed lines indicate
negative polarity. Positive polarity means that the initiating variable influences the receiving variable in the same direction of change (e.g. as the `distance
between households and food retailers' goes up, so does the `time spent travelling to food retailers'). Negative polarity means that the initiating variable
influences the receiving variable in the opposite direction (e.g. when the `level of misinformation about unhealthy foods' falls, an individual's `ability to sort
through conflicting health related messages' rises). Polarities do not indicate the rate of influence, and it is important to note that change may occur at uneven
rates within the diagram.
and the feedback loops that propel them, rather than to depict fewer determinants in finer
detail. The selection of included variables was based on the groups' expert knowledge in the
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Fig 3. Core mechanism of the HE2 diagram.
fields of food security, public health nutrition, health economics and the social determinants
of health, informed by a substantial body of work that has been carried out in recent years with
respect to the food system and the food environment, and also other policy areas that have
been identified as important for achieving equity in healthy eating [
5, 46, 47
When constructing the diagrams, members of the expert group began to identify reinforcing
feedback loops. Feedback is a circular chain of influence that can act to perpetuate or reinforce
the state of the system variables. A change in one variable can trigger a string of connections
that result in either amplifying or reducing the original variable. The change `feeds back' into
itself. Most variables within the HE2 diagram are part of at least 50 feedback loops. The HE2
diagram depicts a highly interconnected system, demonstrating that experts within the field are
acutely aware of the connections between factors that influence inequities in healthy eating.
The system core
At the core of the HE2 diagram is the central stock and flow section (depicted separately in Fig
3), in which the two stocks are the degree of `inequitable distribution of healthy eating' and the
degree of `equitable distribution of healthy eating' across a population. The terms `stock and
flow' refers to the accumulation of a variable over time (stock) and the rate of change between
variables (flow). The arrow between these indicates the rate of change, and the variables that
influence this rate of change are the acceptability, affordability, accessibility and availability of
healthy food (which are in turn influenced by all of the variables captured in the wider causal
loop diagram). This central structure allows the dynamic shift from an inequitable distribution
in healthy eating towards a more equitable distribution to be captured in the diagram. A draft
stock and flow system core was developed by the expert modeller prior to the first workshop.
This was amended throughout the two workshops while making the CLD (i.e. both the CLD
and system core were developed using an iterative process). While stocks and flows are often
quantified, the expert group and the resulting HE2 CLD focused on first articulating the
systems structure of equity/inequity in healthy eating, and the unnumbered stocks are adequate
for this purpose. The a priori hypothesis that gave rise to the system core is that for the level of
equity in healthy eating to rise there needs to be greater consumption of a healthy diet by all
Australians and also a proportionally greater percentage increase among socially
8 / 18
The HE2 diagram comprises 67 variables and 129 connecting arrows, highlighting the
perception among the expert group of a high degree of complexity, interconnectedness and feedback
Fig 4. CLD for determinants of inequities in healthy eating, showing sub-systems. The arrows indicate the direction and polarity of influence. Solid lines
indicate positive polarity and dashed lines indicate negative polarity. Positive polarity means that the initiating variable influences the receiving variable in the
same direction of change (e.g. as the `distance between households and food retailers' goes up, so does the `time spent travelling to food retailers'). Negative
polarity means that the initiating variable influences the receiving variable in the opposite direction (e.g. when the `level of misinformation about unhealthy
foods' falls, an individual's `ability to sort through conflicting health related messages' rises). Polarities do not indicate the rate of influence, and it is important
to note that change may occur at uneven rates within the diagram.
9 / 18
between variables in the system. Most variables within the HE2 diagram are part of at least 50
feedback loops. Various groupings of variables±sub-systems±emerged through the workshops.
As shown in Fig 4, each variable was allocated into a sub-system relevant to macro-level policy
domains such as `transport' and `social protection', and also more meso/micro level factors
such as `health literacy' and `food preferences'. There were one or two factors raised during the
workshop that did not warrant sub-systems of their own and did not quite fit into the other
sub-systems. Trade and investment liberalization was the main one, and was recognised by the
group as influencing the availability, affordability and acceptability of different foodstuffs, as
well as affecting labour markets and employment conditions, with the attendant effects on
healthy eating as described in those particular sub-systems.
The breakdown of the diagram into seven sub-systems also serves to enhance
communication of the diagram and the ways in which the variables related to inequity in healthy eating
span sectoral boundariesÐof the 129 connecting arrows, 48 illustrate connection between the
sub-systems. The goal of the study was to take a `high level' look at the whole system. It is
therefore impractical to describe each linkage and variable in the HE2 diagram. Instead, the
following discussion highlights the key variables identified within the main sub-systems by the
Food supply and environment. Much of the discussion at the workshops focused on
issues to do with food supply and the food environments. This is depicted as the Food Supply
and Environment sub-system, which illustrates the movement of nutrition quality, access and
price through each stage of the food environment from production to processing,
manufacturing, and ultimately availability in the retail and food service environments. Members of the
expert group spoke about the various opportunities and barriers to improving equity in
healthy eating through policy and actions in the food supply and environment that would
improve levels of availability, accessibility, affordability and acceptability of healthy foods
relative to unhealthy foods. An observed feedback loop in this sub-system is between food
labelling±including the influence of advocacy and industry groups on implementation of
mandatory or voluntary arrangements, respectively±and the impact labelling has on reformulation
and marketing of food.
Housing and the built environment sub-system. The Housing and Built Environment
sub-system represents the physical conditions through which people must access food, and the
ways in which the conditions of the built environment, including housing, affect that access.
Significant variables identified by the expert group included the degree of rurality or
remoteness of an area. Rurality and remoteness, which affect the distance between wholesaler and
retailer, were considered to be significant factors in the current social distribution of healthy
eating in AustraliaÐthe challenges in providing fresh food to remote communities are well
]. The participants also identified the distance between homes and
workplaces to healthy food outlets and retailers as being important to the accessibility of healthy
food relative to unhealthy food. The built environment was also noted to influence market
conditions, such as the attractiveness of a location to food retailers and outlets, and the
prominence of convenience food outlets. Housing was another variable discussed by the group. With
access to affordable and quality housing being a key factor for health in general, and healthy
eating in particular±access to facilities for cooking and storing food, were considered essential
conditions for maintaining a healthy diet. Affordable housing and housing quality are major
issues among lower socioeconomic groups and improving them would significantly help to
reduce health and dietary inequities.
Transport sub-system. The transport sub-system captures the way that the dynamics
between distance, work and time affect inequities in healthy eating. Access to affordable
transport among lower socioeconomic groups, either public or private, was noted by the expert
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group as influencing the time spent commuting and time spent traveling to work and other
regular places of attendance. These factors were believed to go on to determine the time
available to prepare healthy meals and engage in a healthy diet, and the time spent improving health
Employment sub-system. The group identified that work matters for inequities in healthy
eating due to the affordability of a healthy diet being determined not just by the price of food,
but also by the disposable income of individuals and households. Participants spoke about
families or households who are unemployed or in low paid jobs finding it difficult to afford a
healthy diet. Precarious employment conditions such as shift work, variable, non-standard or
inflexible work hours, working overtime and multiple jobs, lack of job security, low pay, and
low status jobs were all identified as being associated with fewer family meals prepared or
eaten at home, poorer nutritional quality of meals, and less healthy diets. Working conditions
can also shape food choices indirectly through their influence on time stress and time available
for meal planning, food shopping, and preparation and their contribution to stress, fatigue
and dissatisfaction. The variable `distance between home and work' was placed into the
employment sub-system to highlight the power that some employers have to enable work
from home options for their employees, and thus reduce commuting time pressures.
Social protection sub-system. The Social Protection sub-system represents the formal
and informal social conditions that were identified as shaping people's opportunities to eat
healthily, and were noted by the group as being strongly connected to the Employment
subsystem. Important social protection factors identified include level of educational attainment,
regulatory controls over the labour market, the adequacy of the welfare system and the
minimum wage, which influence levels of household income and the affordability of healthy food.
According to the HE2 Diagram, a key factor affecting the adequacy of the welfare system and
of the minimum wage is the consideration of the real cost of healthy eating in the design of
these social protection mechanisms. The group also acknowledged the informal supports that
can help improve equity in healthy eating, including factors such as kinship and community
groups, which provide financial or meals based support to people in need.
Health literacy sub-system. The group also identified a number of individual level
variables, notably in the health literacy and food preference sub-systems. The Health Literacy
subsystem represents consumers' ability to make sense of different health messages, their degree
of comprehension of nutrition information (nutrition knowledge) and the willingness and
time available to improve health literacy. Nutrition knowledge was noted by the group as
being a key equity concern, whereby people from low socioeconomic groups typically report
lower levels of nutrition knowledge. Nutrition knowledge can act as an antecedent to healthy
food choices, however many other intersecting factors often influence health literacy, as
illustrated in the Health Literacy sub-system.
Food preferences sub-system. Food preferences were noted by participants as being
important individual level factors that affect food choices. Preferences and levels of acceptance
for new foods can be altered via repeat exposures to disliked or unfamiliar foods. Within the
current obesogenic food environment, the group felt that it is often difficult for communities
to avoid the heavily marketed highly palatable foods that are often high in fat, salt, and sugar.
Dynamics of the HE2 system as a whole
Fig 5 is a structural level depiction of the HE2 diagram that shows the feedback between
different sub-systems as they relate to inequity in healthy eating. The arrows are indicative of the
high level connections between the sub-systems, illustrating the ways in which policy domains
interact to give rise to equity/inequity in healthy eating. The direction of the arrows connecting
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Fig 5. Feedback between sub-systems and the social distribution of healthy eating.
each sub-system are derived from the direction of the arrows in the full HE2 CLD (Fig 2). The
structural level diagram gives insight into the feedback between policy sub-systems at a
structural level. From this diagram it can be observed that the distribution of healthy eating is
influenced by all sub-systems. Further, this diagram indicates that the state of variables within a
certain sub-system, for example Housing, influence the distribution of healthy eating directly,
but also go on to influence the state of variables in other sub-systems, such as Transport,
Employment and, Food Supply and Environment. The state of variables in these sub-systems
can then go on to influence variables in the Housing sub-system, and so on. Such feedback
based interactions between sub-systems add to the complexity of the HE2 system overall.
In this paper we present the results of research conducted with an expert group of policy actors
(policy makers, practitioners and researchers). A systems approach, using group model
building of a causal loop diagram, has made it possible to organise and analyse complex information
with an emphasis on the whole picture. While the healthy eating literature has paid a lot of
attention to food systems, this project expands the thinking in two ways: it brings an equity
lens to healthy eating, and it considers a much wider system that is inclusive of societal and
individual level factors that cross multiple sectorsÐthe food supply and environment; housing
and the built environment; transport; employment; social protection; health literacy, and food
preferences. This articulation of the interconnections within the wider system highlights the
need, within policy development and implementation, to consider the ways in which actions
in one sector can reinforce or undermine actions in other sectors. Members of the policy actor
group were able to identify multiple level determinants of inequities in healthy eating and
capture the interactions between the different factors. They were also able to identify feedback
loops within the system that drive inequities in healthy eating. Through participating in the
workshops and constructing the CLD, the policy actors were able to discuss deeply the whole
system and begin to identify key points in the system in which there are opportunities to
intervene to address inequities in healthy eating.
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Strengths of the study
A new way of thinking. This study framed the emergence of inequity in healthy eating as
arising from a complex adaptive system and successfully used an expert group collaborative
modelling process to build a causal loop diagram for understanding drivers, major feedback
loops, and the system structure of inequity in healthy eating. This has not been done as far as
we are aware. Previous nutrition related systems research has focussed on the food
environment rather than to draw together all of the relevant drivers of diet and nutrition as a complex
adaptive system, and has not included an equity focus [
Participatory processes. By using a collaborative group model building method in the
development of the causal loop diagram, the study demonstrated that such a systematic
approach was a useful way of engaging key policy actors in developing a broad understanding
of systems that affect inequities in healthy eating and ultimately inequities in NCDs. The study
was very participatory, and enabled a diverse group of stakeholders to share knowledge and
insights about a whole variety of issues relating to healthy eating, in a way that was informative
and respectful of differences in views and knowledge. The involvement of senior government
officials, key non-government agencies and prominent academics has the potential to enhance
the leadership and workforce readiness to push for a comprehensive policy and practice
response to inequities in healthy eating. This participatory approach of involving key
stakeholders in the process of developing the CLD has been observed by others to help create
ownership of the issues raised and help move towards action and solutions [
11, 15, 53
Crossing sectors. Almost none of the participants had used systems science approaches
previously, and in a relatively short period of time, using the CCM method, deepened their
understanding of the wide range of determinants of inequities in healthy eating, and started to
think about policies and interventions that they might otherwise not have. Indeed, the
complexity of the HE2 diagram demonstrates that bringing together the range of experts in the
field of healthy eating enabled the identification of many connections between many factors
that influence equity in healthy eating. As a group, the experts identified seven sub-systems
that are important to address inequities in healthy eating: food supply and environment;
housing and the built environment; transport; employment; social protection; health literacy, and
food preferences. The HE2 CLD provides a useful tool for engaging actors from less
`traditional' sectors (e.g. Housing, Social Protection, Employment), which is a critical first step in
tackling this complex systems-wide issue of inequities in healthy eating.
A model for complex problems. Using a systems approach to understand the drivers of
inequities in healthy eating has enabled us to produce a new conceptual model of HE2. This
visual product, plus the method used to develop it, is likely to be of value to others concerned
with complex health and social issues. Not only does the CLD help visualise the different
drivers of complex problems, in this case inequities in healthy eating, it also demonstrates the
interconnections and feedback loops, which ultimately can help the users identify key points
in the system in which to intervene.
Weaknesses of the study
As with other studies that have used systems science to investigate health issues [
resulting CLD is complex, messy and potentially overwhelming. However, visualising the
complexity helped the expert group `see themselves' in the potential solutions to inequities in healthy
eating and how their actions were connected to many other parts of the system that they
would otherwise not have known.
As is the case for all causal loop diagrams [
], the HE2 diagram cannot visually represent
the distributional effects of the different variables on healthy eating. The HE2 diagram
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represents important variables that impact on inequities in health eating, the structure of these
variables, and their relationships, but not the specific degree that these affect an individual or
group. However, the diagram can be used in an interpretive manner, noting that while the
depicted policy areas and determinants matter for all people, different groups are affected to
different degrees. For example, access to affordable public transport is relevant for accessing
food for all people, however the degree to which different individuals or groups experience
transport as a barrier to healthy eating varies.
Another limitation of the study is the positioning of the boundaries around the system. The
boundaries were determined by the interests and knowledge of the expert group and may have
differed if the composition of the group was less health prevention focussed and more inclusive
of a business perspective or directly involved community organizations engaged in promoting
or preserving healthy eating alternatives. The CLD may therefore not be generalizable to other
policy actor groups and communities. However, the purpose of this study was to provide a
way by which policy actors could begin to engage with, and apply, systems thinking.
While study participants were encouraged to think in an analytical manner about a
complex system, the study must be considered descriptive in nature rather than analytical. As a
descriptive study, the results are however valuable as a first step in understanding and
appreciating the processes that were undertaken to address the research question and provide a
platform from which to continue such a body of work.
The method used in this study relies on the knowledge of an assembled group of experts.
This brings with it some potential biases and knowledge gaps. Complementing this method
could be meta-narrative synthesis mapping exercises, which characterise the literature in
complex issues (e.g. inequities in healthy eating) in order to identify areas where published
evidence exists or where gaps can be ascertained. For example, Weiler et al  undertook such
an exercise to examine literature exploring the relationships between food sovereignty, food
security, and health equity. Iteration between experts and literature would help overcome
knowledge gaps and group biases.
Implications of the study
This conceptualisation of the drivers of inequities in healthy eating helps demonstrate to a
range of policy actors the importance of policy action that tackles the systemic drivers of the
availability, affordability, accessibility and acceptability of healthy food compared to unhealthy
foods, and that these actions are not confined to the food system or food environment. The
identification of seven broad policy domains that affect inequity in healthy eating suggests that
whole of government action is needed.
Further work is needed to elicit different stakeholder perspectives, including food industry,
social policy and consumer groups, on the issues that affect healthy eating. The group model
building methods used in this study provide a relatively straightforward technique that could
be used by policy actors to engage communities. This would go some way to helping ensure
policy actions respond to people's needs.
A quantitative system dynamics model based on the HE2 diagram could generate further
insight into the utility of the model, and enable policy makers to identify the relative impact of
different policy actions at various intervention points in the model. Similar work has been
done in modelling diabetes [
] and obesity more broadly [
], which could provide examples
of data driven models that could be adapted to the social distribution of healthy eating.
In conclusion, this study aimed to organise, from a complex systems perspective, current
understandings of how individual and societal level factors interact to create inequities in
healthy eating as part of a larger body of work asking the question: `What kind of insight can
14 / 18
policy actors gain about the causes and potential solutions to inequity in healthy eating using
systems science methods?' The application of the collaborative conceptual modelling systems
approach helped answer this through identifying the complexity of the causes of inequities in
healthy eating; visually illustrating the system and its structures, and by beginning to identify
leverage points for change within the system.
This research was supported by The Australian Prevention Partnership Centre through the
NHMRC partnership centre grant scheme (Grant ID: GNT9100001) with the Australian
Government Department of Health, New South Wales Ministry of Health, Australian Capital
Territory Health, HCF, and the HCF Research Foundation.
Conceptualization: Sharon Friel, Melanie Pescud, Eleanor Malbon, Amanda Lee, Robert
Data curation: Sharon Friel, Melanie Pescud, Eleanor Malbon.
Formal analysis: Sharon Friel, Melanie Pescud, Eleanor Malbon.
Funding acquisition: Sharon Friel.
Investigation: Sharon Friel, Melanie Pescud, Eleanor Malbon, Amanda Lee, Robert Carter,
Joanne Greenfield, Megan Cobcroft, Jane Potter, Lucie Rychetnik, Beth Meertens.
Methodology: Sharon Friel, Eleanor Malbon.
Project administration: Sharon Friel, Melanie Pescud, Eleanor Malbon, Joanne Greenfield.
Resources: Sharon Friel, Melanie Pescud, Eleanor Malbon, Amanda Lee, Robert Carter,
Joanne Greenfield, Megan Cobcroft, Jane Potter, Lucie Rychetnik.
Software: Melanie Pescud, Eleanor Malbon.
Supervision: Sharon Friel, Melanie Pescud.
Validation: Sharon Friel, Melanie Pescud.
Visualization: Sharon Friel, Melanie Pescud, Eleanor Malbon.
Writing ± original draft: Sharon Friel, Melanie Pescud, Eleanor Malbon, Amanda Lee, Robert
Carter, Joanne Greenfield, Megan Cobcroft, Jane Potter, Lucie Rychetnik, Beth Meertens.
Writing ± review & editing: Sharon Friel, Melanie Pescud, Eleanor Malbon, Amanda Lee,
Robert Carter, Joanne Greenfield, Megan Cobcroft, Jane Potter, Lucie Rychetnik, Beth
15 / 18
16 / 18
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