Peopel cycling along the Torrens river

Identifying factors which influence cancer risk, survival and survivorship

Research indicates modifiable lifestyle factors impact cancer risk, as well as quality of life and survival in people diagnosed with cancer. The overall aim of this research is to investigate the role that lifestyle factors play in the risk and management of chronic diseases, particularly cancer. Our main focus is to improve understanding of the influence of active and sedentary behaviours on cancer risk, cancer survival and cancer survivorship.

The overall aim of this research is to investigate the role that lifestyle factors play in the risk and management of chronic diseases, particularly cancer. Our main focus is to improve wider understanding of the influence of active and sedentary behaviours on cancer risk, cancer survival and cancer survivorship.

This is achieved by:

  • using accelerometers to obtain more precise and detailed measures of sedentary and active behaviours
  • utilising novel methods which take the interdependent nature of these behaviours into account
  • employing causal inference methods to provide stronger evidence for the health benefits of physical activity and/or
  • working with national and international researchers to combine datasets, thus allowing more specific research questions to be asked.

Current research projects

Cancer Survivorship

(PI: Dr Terry Boyle)

A cohort of 500 cancer survivors was established in 2013-14, and the first follow-up of these participants was completed in the second half of 2017. Baseline assessment involved collection of sleep quality and duration; sedentary time and physical activity (assessed with an accelerometer); clinical, demographic and lifestyle factors; patient-reported outcomes. Patient-reported outcome and sleep data were collected again at follow-up.

Data from this cohort is being used to prospectively examine interdependent associations between sleep, sedentary and physical activity behaviours, as well as changes in patient-reported outcomes (including health-related quality of life, fatigue, depression, anxiety and cognitive functioning) in breast cancer, colon cancer and non-Hodgkin lymphoma survivors. It will also be used to identify determinants (including socio-economic and geographic disparities) of poorer patient-reported outcomes and unmet needs in cancer survivors.

We are also working with researchers in the Netherlands, US, Canada and Australia to pool data from eight studies to identify and investigate the correlates of daily activity patterns in cancer survivors, and investigate whether these correlates differ by cancer type.

Risk of Non-Hodgkin Lymphoma

(PI: Dr Terry Boyle)

Using pooled data from 11 studies (from the US, UK, Canada, Europe and Australia) in the International Lymphoma Epidemiology Consortium, we are investigating the associations between physical activity, sedentary work and the risk of non-Hodgkin lymphoma subtypes. The overall aim of the proposed project is to investigate four specific research questions:

  1. Are there differential associations between physical activity and non-Hodgkin lymphoma risk between males & females?
  2. Are there differential associations between physical activity and different non-Hodgkin lymphoma subtypes?
  3. Does intensity influence the association between physical activity and non-Hodgkin lymphoma risk?
  4. Is sedentary work associated with the risk of non-Hodgkin lymphoma?

Mendelian Randomisation to establish causal effects on cancer

(PIs: Professor Elina Hyppönen, & Dr Terry Boyle)

While there is strong evidence indicating some modifiable exposures (such as physical activity, diet and obesity) influence cancer risk, all studies to date have been observational as it isn’t feasible to conduct randomised trials on these exposures. A different approach to investigate cancer risk factors is by using Mendelian Randomisation. New research indicates some genes are associated with modifiable exposures. Mendelian Randomisation uses individual variation in these genes as a proxy for a particular modifiable exposure to make a causal inference about the relationship between that modifiable exposure and cancer risk. We use information from the UK Biobank and other large scale studies to investigate the causal associations between specific modifiable exposures and the risk of cancer.