Here at the Food and Mood Centre, we aim to discover the ways in which what we eat influences our brain, mood and mental health. To do so, we conduct a broad range of research activities, referred to as ‘bench to bedside’. This refers to the translation of discoveries from research laboratories through to patient treatment outcomes.

One form of research that may not evoke traditional scientific images of white lab coats and test tubes, is the use of big data. These data, as you would expect, refer to large information databases which can be mined and explored to reveal associations and patterns in health and disease over time.

There are many advantages to using big data. Whilst the impact of nutritional or dietary changes can be examined at a biological level within clinical trials and basic lab experiments, big data can be used to assess changes at a population level. Changes can be examined in relation to broader family, community, and societal level factors, which we know have complex and critical effects on mental health outcomes.

For example, through clinical trial we are currently examining the impact of different types of milk on gut health, and how this interacts with mood. Big data, such as the Australian Health Survey, may supplement the findings of this clinical trial. Through analysing dietary and mood patterns of the 20,000 individuals involved in this survey, we can identify important factors such as; those most likely to successfully respond to a dairy-based intervention, the trajectory of mood disorders in Australian communities, and how much this depends on where an individual lives, works, has supportive relationships, etc.

These opportunities are particularly important given common mental disorders are so incredibly complex, and as mentioned, are the result of many interconnected, reciprocal and sometimes conflicting factors. In fact, the first nutritional psychiatry studies to convincingly show the relationship between depression, anxiety and diet were large, population-based studies of individuals over time. It is through these big data studies that hypotheses were generated, subsequently leading to dietary interventions for mental health, including the Food and Mood Centre led SMILES trial in 2017.

As with any research methodology, there are limitations to using big data. Many datasets are based on individuals’ responses to survey questions such as ‘how many times in the last week did you eat fresh fruit or vegetables?’. An assessment of diet is only true to the extent which individuals report accurately on their own behaviour. We can all probably agree that we’d like to, and probably do, overestimate rather than underestimate our healthful behaviours.

Whilst intervention studies can tell us, for example, the physiological impact of supplement or nutraceutical treatment, big data are almost exclusively collected to understand naturally occurring changes over time. It is therefore difficult to tease out and pin point the causal associations, and therefore not possible to translate directly to patient ‘bedside’ options.

Despite limitations, big data form an important area of research in which we can identify and harness opportunities to improve dietary behaviours to support positive mental health. We are currently developing international collaborations to enhance our existing big data sources, which will further build possibilities in this research space.

Human behaviour is undoubtedly messy and complex, and it is through big data we can help untangle some relationships and ultimately find opportunities for individuals to lead happier and healthier lives.

Dr Erin Hoare is a current Australian Rotary Health Postdoctoral Fellow leading a collaborative research project between Global Obesity Centre and the Food and Mood Centre.