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Approved research

Patterns and correlates of active commuting in adults with type 2 diabetes; cross-sectional evidence from UK Biobank.

Principal Investigator: Dr Catherine Falconer
Approved Research ID: 19307
Approval date: June 13th 2016

Lay summary

Type 2 diabetes is one of the most common chronic health conditions in the UK and in the first instance treatment is focussed on improving lifestyle through increasing physical activity improving diet. Active commuting can increase physical activity and research has also shown it to be associated with lower levels of obesity and better cardiovascular health. However, little is known about the active commuting patterns of adults with type 2 diabetes. This project aims to understand more about the active commuting behaviour of adults with type 2 diabetes, how it relates to physical activity and what may predict participation. Type 2 diabetes affects over 3.5 million people in the UK and with prevalence rates rapidly increasing contributes a huge burden to NHS costs. Slowing disease progression is the predominant focus of first-line treatment and there is substantial evidence that increasing physical activity and reducing sedentary time are key components of this. However, it is very difficult to get people to increase and maintain their physical activity by sufficient amounts for health benefits to be seen. Therefore, alternative strategies such as active commuting, which focus on more behaviourally sustainable approaches are required. This analysis will be cross-sectional. We will initially use descriptive statistics to explore the commuting patterns of adults with type 2 diabetes and how they vary by age, sex and various socio-economic indicators for example education. A series of linear regression models will then be built with physical activity and sedentary behaviour (minutes) entered as the dependent variables and commuting mode (e.g car, walk, cycle) entered as the independent variables. Models will be adjusted for a number of confounding factors. Further regression modelling will be used to identify potential socio-demographic and environmental determinants of commuting mode. Of the 500,00 enrolled in UK Biobank, we know from prior research that 264,341 of these engage in regular commuting behaviour. We also know there is an approximate diabetes prevalence of 5.2% within the sample. Therefore, we anticipate there may be up to 14,000 with diabetes who commute. This is likely to be an over-estimate as type 2 diabetes is associated with increased age and therefore there may be a smaller proportion who commute.