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P131 Does switching to active commuting reduce BMI in mid-life? Longitudinal, observational evidence from UK Biobank
  1. E Flint1,
  2. E Webb2,
  3. S Cummins1
  1. 1Social and Environmental Health Research, London School of Hygiene and Tropical Medicine, London, UK
  2. 2ESRC International Centre for Lifecourse Studies, University College London, London, UK

Abstract

Background Physical inactivity is a leading cause of obesity, chronic disease and premature mortality. Middle-age is a key lifestage for the development of these risks. In this study, uptake of active commuting is hypothesised to independently predict decreases in bodyweight and bodyfat.

Methods UK Biobank is a survey of individuals aged 40–69 at baseline (2006–2010; n = 502,656) selected via NHS patient registers. A subsample participated in a repeat assessment (2012–2013, n = 20,346). For this study, individuals with complete data on analytic variables at baseline and follow-up were selected (n = 4,132). BMI was calculated from objectively measured height and weight (kg/m2). Baseline BMI was subtracted from follow-up BMI to generate the outcome of interest: BMI change. Two binary exposure variables were derived from self-reported commuting mode: (i) experiencing a transition from car commuting at baseline to active/public modes at follow-up; (ii) transition from active/public modes at baseline to car commuting at follow-up (reference categories were those who had retained their baseline mode at follow-up). A range of time-varying and time-invariant socioeconomic, demographic, health and behavioural factors were identified as potential confounders. Nested multivariate linear regression models were fitted using Stata 14. All analyses were replicated using objectively measured percentage body fat change as a supplementary outcome.

Results Experiencing a transition from car commuting at baseline to a public/active modes at follow-up (n = 469) independently predicted a −0.30 kg/m2 decrease in BMI (95% CI −0.48 to −0.13), compared with stable car commuting (n = 3,545). Conversely, experiencing a transition from active/public transport commuting to car commuting (n = 405) was significantly and independently predictive of a 0.32 kg/m2 increase in BMI (95% CI 0.13 to 0.50), when compared with stable use of active or public modes (n = 1,272). Adjustment for hypothesised time-varying and time-invariant socioeconomic, demographic, health and behavioural hypothesised confounders did not attenuate the effects of commute mode transition on BMI change. results from complementary percentage body fat analyses were corroborative.

Conclusion To the authors’ knowledge, this study is the first to use UK Biobank’s nested cohort to investigate the effects of active commuting on adiposity. The findings suggest a causal relationship between active commuting and objectively measured markers for obesity in this middle-aged UK sample. Sample size constraints necessitated the combining of active and public modes, leading to probable underestimation of effects for walking and cycling. This research supports the case for interventions to promote active commuting as a population-level policy response to the prevention of obesity in mid-life.

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