THEO MURPHY (AUSTRALIA) HIGH FLYERS THINK TANK

Preventative health: Science and technology in the prevention and early detection of disease

University of Sydney (Eastern Avenue Complex), Thursday 6 November 2008

GROUP C: Metabolic syndrome
Rapporteur: Dr Alex Brown
Head, Centre for Indigenous Vascular and Diabetes Research, Baker IDI Heart and Diabetes Institute

Alex Brown is an indigenous doctor, who has been working in Aboriginal health and health policy, communicable disease control, service delivery and public health, epidemiology, cardiovascular research and research ethics for the last nine years. Alex is currently the head of the Centre for Indigenous Vascular and Diabetes Research, for the Baker IDI Heart and Diabetes Institute, based in Alice Springs.

Alex’s research interests focus on indigenous cardiovascular disease disparity and its determinants, clinical and epidemiological cardiovascular research, chronic disease policy development, Aboriginal chronic disease health services research, indigenous male health, and unpacking the psychosocial determinants of indigenous health. His current projects include:

• the Men, Hearts and Minds Study, exploring the measurement of psychosocial stress, depression and socioeconomic inequalities in Aboriginal men in Central Australia and their association with cardiovascular and metabolic risk;
• the Kanyini Vascular Collaboration Health Services Research program (in conjunction with The George Institute), focusing on understanding and addressing barriers to care for Aboriginal people with or at risk of vascular diseases (diabetes, cardiovascular and renal disease); and
• the Heart of the Heart Program, determining the burden of cardiovascular risk and heart failure in 500 Aboriginal people in Central Australia and piloting a novel nurse-led family-based outreach management and education program to reduce preventable death.

Thank you very much for the chance to be involved in today's festivities. I too would like to acknowledge the traditional owners of the land on which we meet today. They were hit by the first wave of colonisation of this country and our mob just down on the south coast was hit by the second. Thankfully, they bore the brunt in a way that helped others to survive the onslaught.

Getting an hour to solve the riddle of the Sphinx with a paperclip and a piece of paper is not the easiest of jobs, so I will present a bit of background here and then move on to the discussions we had as a group.

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To utilise the metabolic syndrome (MS) as an exemplar condition for progressing a national preventative health agenda faces many challenges of practical, scientific, clinical and social importance. Kerin [O'Dea] touched on many of these earlier this morning. As is evident within the literature, and within the practice of clinical medicine, there are enormous definitional challenges around what constitutes or is classified as metabolic syndrome, and this has not been helped by definitive basic science to date. Unfortunately we haven't really spent a lot of time on that today. Similarly, there are additional challenges in understanding insulin resistance and how it plays out across the body and across multiple tissues as target organs. This heterogeneity presents an enormous challenge, not only in the way science approaches a broader understanding through animal models but also how these translate to human models of cardio-metabolic risk.

The heterogeneity of insulin's activity and the impact of insulin resistance across tissues is incredibly important. You may be insulin resistant in one tissue bed and not in another. How does that play out in terms of a person's future risk and problems with handling glucose, fat and subsequent disease?

Similarly, as a group, we touched on issues around life course perspectives. How do you understand the trajectories people go upon and what critical intervention points are there along that life course on which we can intervene from a preventative perspective? I think Ian [Hickie] touched on that earlier in terms of mental health, but the questions are the same in terms of cardio-metabolic risk over the life course. Similarly, there is the escalating burden of metabolic syndrome, which was touched on earlier this morning by Paul [Zimmet] and Kerin.

One of the critical challenges rests with trying to unpack the complexity of the biological, psychological and social, and the molecular contributors to MS and related conditions. I realise that it is very complicated, but that's about all I know.

In addition, we must remain vigilant in ensuring that we refrain from medicalising what are largely social phenomena. I think the broader discussion – although we won't get to it today – really has to be on our agenda. Clearly, there is no pill that cures poverty. If poverty causes a range of conditions, do we give it a medical name and, therefore, somehow find a medical solution? I am not so sure.

Similarly, treatment has to focus on those sorts of considerations as well, spanning from biological treatments to focusing on risk factors, to the clustering of risk factors and then to understanding the whole person. I think these are challenges for us as a scientific, social and medical community.

There also was quite a lot of discussion about widening the gaps. If we intervene from a preventative health perspective, we usually make it better for those who are best equipped to deal with the insults of the world. Unfortunately, we make it tougher for those who are doing it the toughest and, therefore, widen the gaps. Clearly, the example of indigenous Australians is important here, but there are other communities at risk as well.

Similarly, our biggest gains in terms of prevention are likely to come from outside of the health sector. Yet how do we engage them? It would need a whole bunch of scientific investigations of the mind-sets of bureaucrats and politicians – a study that I'll never get funded for and probably do not want to do anyway.

Lastly, we are challenged by our ability to translate our cross disciplinary understandings of MS: can we express our understanding from the cell in a manner that is understood by the community in a way that engages and enacts preventative action across society?

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However, from every great challenge come opportunities. What can we learn from the way in which metabolic syndrome has been defined and utilised to understand risk of disease? We need to take those opportunities. Similarly, utilising the story of MS may be a way of us dragging our sorry bums, for want of a better expression, into adolescence rather than at risk in adults and in maybe using things like clustering of risk factors and early markers as our opportunity to intervene long before the pathway to disease has been set in stone.

Similarly, there is an opportunity to map trajectories across the life course and to understand the most critical intervention points. Unfortunately we remain a long way from doing that. What metabolic syndrome has offered is an opportunity to understand the endocrine function of multiple tissues. In addition, there is an opportunity to link the data that we have already to answer the big questions – and I think we do it very badly. Many of our discussions this afternoon were focused on that.

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I was thinking that we would have quite a lot of discussion about enabling technologies but these are not without their own difficulties. Epigenomics; well, where do you start; genomics, the promise unfulfilled thus far; and proteomics, targets or fishing trips? No offence to molecular biologists here but as a public health physician looking in from the outside, it is very hard to get a handle as yet on the population benefits that are likely to be delivered through these technologies. I think these sorts of discussions, across disciplines are really important.

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If we are to think about enabling technologies, then we also need to be thinking about enabling methodologies. Do we have the mathematics to unpack complicated integrative biological processes, particularly around disease risk across multiple systems? Do we have the statistics that match? Do we have the animal models that will answer the tough questions? Also, do we have enough clinical samples to enable us to look at this in humans? These are the questions that we need to be thinking of.

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So more specifically, what did our group talk about? It touched on quite a few of those things that I have presented. But, really, we need to look at whether we can track the trends in risk and disease on a routine basis, in a standardised fashion and over the longer term in Australia so that we can map trends over time. The issue of data linkage is critical and it was very strongly discussed in our group, really focusing on linking clinical data, population-level data and educational and socioeconomic data. The ABS [Australian Bureau of Statistics] collects a whole range of information, but you can't link it down to the individual level. Certainly, people's interactions with health systems are important data that already exist across multiple jurisdictions in multiple datasets, but we just can't get them together.

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The other understanding offered from the example of the MS is that we run the risk of trying to focus on therapies alone; as management or curative strategies rather than prevention. What is the best way? We still don't know. Should we remain obsessed with managing individual risk factors, in the absence of better targets within the insulin resistance paradigm? Or are sneakers [exercise] the best therapy and prevention? The group tended to focus on preventative strategies, and I will talk to those more specifically than to therapeutic options.

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The process and consequences of MS also raise important questions as to our ability, across disciplines, to find (if it exists), the unifying framework of metabolic syndrome. Is it allostatic load? Is it allostatis, the biology of stress? Is inflammation the centre of the universe? Alternatively, is it all about insulin in terms of a whole-body regulator? As with most complex biological processes, it's probably a bit of everything.

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What did we talk about in terms of bioinformatics to fill the matrix that people are keen for us to fill? There was a brief but very important discussion that we did not really conclude on the use of imaging to understand the deposition of adipose tissue around the body, and how we can better understand and clinically phenotype participants, patients or clinical groups to improve our knowledge of what is going on.

The data and data linkages, as I mentioned remain enormous opportunities that are unfulfilled at this stage. Governments, particularly jurisdictional health departments – I was encouraged to be very strong on this point – are the major barriers to linking data at this stage.

A large discussion in this issue is around privacy, the concern that patients will not want their data identified or linked in any way, shape or form. Some of the most vulnerable populations in the country, from our experience in dealing with them, do not understand why we don't link data: 'You've got that data. I just told that doctor. Why the hell are you asking me for? I already told somebody.'

There are also issues around holding data, collating data and the governance of that system, which are inconsistent across jurisdictions. There was a strong discussion about the need for a single unifying and unique identifier for individuals, based on the example given by New Zealand participants in the room. They said, 'We've got that. It's working great. It's de-identified. We can do a whole bunch of stuff with it.' It just seems ridiculous that we can't be moving towards the same sort of system.

There was strong discussion of a national cohort to track, as I mentioned before, lifestyle, diet, vascular and metabolic risk over time, looking at a number of factors within that and making sure that, when we are going to link data, it includes a range of critical information – not just hospitalisations but also Medicare data, community data, ABS information and primary care data elements.

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We did not talk a great deal about genes and the environment. Nutrigenomics was mentioned as an example of a key potential to identify simple solutions with the help of complex methods; that is, it would seem fairly reasonable to find the improved diets that can improve the cardio-metabolic profile of populations. Unfortunately, time was against us in further exploring the likely gene-environment interactions.

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Around screening and early diagnosis, there was a strong push for making sure that we had standardisation of key diagnostic assays across the country – you would think in this day and age that's not too much to ask, in particular, haemoglobin A1c [glycosylated haemoglobin] over which there is great controversy internationally. If we cannot get it right in a small country like Australia there must be something wrong.

There was strong discussion of making sure that we could link screening data, wherever it is performed, across a range of information systems. So, if five million people were having an adult health screening check across the country, that information would be available, would be standardised and could be linked to national e-health records.

We also had a small discussion about utilising non-fasting methodology for assessing risk. Clearly, there is a need to validate such methods. We talked about the fact that one size doesn't fit all. We need to consider that there is significant heterogeneity across population groups and clinical population groups and also within individual groups.

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Where were people thinking in terms of protection or prevention to fill the matrix? We have to implement what we know. We used the Lord of the Rings criteria, which basically is: 'One guideline to rule them all'.

We also need to utilise electronic decision support tools, assessment tools – whatever there is that makes it easier to get the job done in a standardised fashion – and to ensure that, when that information is collated, it is put on to a system that lots of people can access.

There was discussion about realigning acute hospital approaches to cardio-metabolic disease; and using things like rationalisation and incentives to drive new approaches to focusing on chronic diseases within acute sectors in a broader brush stroke; rather than focusing on renal services, diabetes services and cardiology services, to look at vascular and metabolic services and integrate them across the system. We discussed making sure that we had a systematic approach to managing risk across all levels of our system, particularly our health system.

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Looking at life course trajectories, there was certainly strong discussion about starting early in childhood and focusing on nutrition and education about healthy lifestyle right from the start. But there was a strong focus on our making sure that we create the environments that support healthy choices in encouraging people to understand the choices they make.

We need to take the opportunities that exist around the Rudd agenda on prevention and more proactive services and climate change, as a way of perhaps getting people off their bums. We need to learn the lessons from abroad. There was particular discussion about labelling; using the market, if we can; understanding that the economics of food choice are important drivers; making sure that we consider things like the health impact statements of major public health policy or public policy (as they do with environmental health impact statements) to make sure that people think about the health implications of the stuff that they do – and I thought that was a pretty good idea. So we might leave it there.

Discussion

Comment – Marissa Lassere, University of NSW. I think one of the key consensus statements that came out of the group was about a top-down approach from government to legislate certain changes – taking an example from the tobacco industry – because they can then push a sort of traffic-light approach, such as the one with food labelling that someone mentioned. Once that legislation takes place, the market will follow. The industry will put up a fight right to the end in terms of any legislative changes that are put out. But then, if they are put through, industry will make certain changes. An example was given of the labelling of the salt content in certain food and so forth.