Dataset Information

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

ABSTRACT: OBJECTIVES:To describe the active commuting (AC) patterns of adults with type 2 diabetes and how these relate to physical activity and sedentary behaviour in UK Biobank. Social and environmental correlates of AC will also be explored. DESIGN:Cross-sectional analysis of a cohort study. SETTINGS:This is a population cohort of over 500?000 people recruited from 22 centres across the UK. Participants aged between 37 and 73?years were recruited between 2006 and 2010. PARTICIPANTS:6896 participants with a self-reported type 2 diabetes diagnosis who reported commuting to work and had complete covariate data were included in the analysis. EXPOSURE MEASURES:Exposure measures were AC to work, measured as usual mode of transport. OUTCOME MEASURES:Outcome measures were weekly minutes of moderate to vigorous physical activity (MVPA), hours/day of sedentary time and participation in active travel. RESULTS:AC (reporting walking or cycling to work only) was reported by 5.5% of participants, with the great majority using the car to commute (80%). AC was associated with an additional 73 (95% CI 10.8 to 134.9) and 105 (95% CI 41.7 to 167.2) weekly minutes of MVPA for men and women, respectively. AC was associated with reduced sedentary time (? -1.1, 95%?CI -1.6 to -0.7?hours/day for men; and ? -0.8, 95%?CI -1.2 to -0.3?hours/day for women). Deprivation and distance from home to work were identified as correlates of AC behaviour. CONCLUSIONS:Rates of AC are very low in adults with type 2 diabetes. However, AC offers a potentially sustainable solution to increasing physical activity and reducing sedentary behaviour. Therefore, strategies to improve the environment and encourage AC may help to increase population levels of physical activity and reduce the disease burden associated with type 2 diabetes.

SUBMITTER: Falconer CL

PROVIDER: S-EPMC5640023 | biostudies-literature | 2017 Oct

REPOSITORIES: biostudies-literature

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

Falconer Catherine L CL Cooper Ashley R AR Flint Ellen E

BMJ open 20171008 10

<h4>Objectives</h4>To describe the active commuting (AC) patterns of adults with type 2 diabetes and how these relate to physical activity and sedentary behaviour in UK Biobank. Social and environmental correlates of AC will also be explored.<h4>Design</h4>Cross-sectional analysis of a cohort study.<h4>Settings</h4>This is a population cohort of over 500 000 people recruited from 22 centres across the UK. Participants aged between 37 and 73 years were recruited between 2006 and 2010.<h4>Particip ...[more]

PMID: 28993386

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Project description:OBJECTIVES:To examine whether there are associations between active travel and markers of a healthy, low-carbon (HLC) diet (increased consumption of fruit and vegetables (FV), reduced consumption of red and processed meat (RPM)). DESIGN:Cross-sectional analysis of a cohort study. SETTINGS:Population cohort of over 500 000 people recruited from 22 centres across the UK. Participants aged between 40 and 69 years were recruited between 2006 and 2010. PARTICIPANTS:412 299 adults with complete data on travel mode use, consumption of FV and RPM, and sociodemographic covariates were included in the analysis. EXPOSURE MEASURES:Mutually exclusive mode or mode combinations of travel (car, public transport, walking, cycling) for non-work and commuting journeys. OUTCOME MEASURES:Consumption of FV measured as portions per day and RPM measured as frequency per week. RESULTS:Engaging in all types of active travel was positively associated with higher FV consumption and negatively associated with more frequent RPM consumption. Cycling exclusively or in combination with walking was most strongly associated with increased dietary consumption of FV and reduced consumption of RPM for both non-work and commuting journeys. Overall, the strongest associations were between non-work cycling and FV consumption (males: adjusted OR=2.18, 95% CI 2.06 to 2.30; females: adjusted OR=2.50, 95% CI 2.31 to 2.71) and non-work cycling and RPM consumption (males: adjusted OR=0.57, 95% CI 0.54 to 0.60; females: adjusted OR=0.54, 95% CI 0.50 to 0.59). Associations were generally similar for both commuting and non-work travel, and were robust to adjustment with sociodemographic and behavioural factors. CONCLUSIONS:There are strong associations between engaging in active travel, particularly cycling, and HLC dietary consumption, suggesting that these HLC behaviours are related. Further research is needed to better understand the drivers and dynamics between these behaviours within individuals, and whether they share common underlying causes.

Project description:BackgroundActive living approaches seek to promote physical activity and reduce sedentary time across different domains, including through active travel. However, there is little information on how movement behaviours in different domains relate to each other. We used compositional data analysis to explore associations between active commuting and patterns of movement behaviour during discretionary time.Methods and findingsWe analysed cross-sectional and longitudinal data from the UK Biobank study. At baseline (2006-2010) and follow up (2009-2013) participants reported their mode of travel to work, dichotomised as active (walking, cycling or public transport) or inactive (car). Participants also reported activities performed during discretionary time, categorised as (i) screen time; (ii) walking for pleasure; and (iii) sport and do-it-yourself (DIY) activities, summed to produce a total. We applied compositional data analysis to test for associations between active commuting and the composition and total amount of discretionary time, using linear regression models adjusted for covariates. Adverse events were not investigated in this observational analysis. The survey response rate was 5.5%. In the cross-sectional analysis (n = 182,406; mean age = 52 years; 51% female), active commuters engaged in relatively less screen time than those who used inactive modes (coefficient -0.12, 95% confidence interval [CI] -0.13 to -0.11), equating to approximately 60 minutes less screen time per week. Similarly, in the longitudinal analysis (n = 4,323; mean age = 51 years; 49% female) there were relative reductions in screen time in those who used active modes at both time points compared with those who used inactive modes at both time points (coefficient -0.15, 95% confidence interval [CI] -0.24 to -0.06), equating to a difference between these commute groups of approximately 30 minutes per week at follow up. However, as exposures and outcomes were measured concurrently, reverse causation is possible.ConclusionsActive commuting was associated with a more favourable pattern of movement behaviour during discretionary time. Active commuters accumulated 30-60 minutes less screen time per week than those using inactive modes. Though modest, this could have a cumulative effect on health over time.

Dataset Information

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

Publications

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

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