Dataset Information

Longitudinal associations between built environment characteristics and changes in active commuting.

ABSTRACT:

Background

Few studies have assessed the predictors of changes in commuting. This study investigated the associations between physical environmental characteristics and changes in active commuting.

Methods

Adults from the population-based European Prospective Investigation into Cancer (EPIC)-Norfolk cohort self-reported commuting patterns in 2000 and 2007. Active commuters were defined as those who reported 'always' or 'usually' walking or cycling to work. Environmental attributes around the home and route were assessed using Geographical Information Systems. Associations between potential environmental predictors and uptake and maintenance of active commuting were modelled using logistic regression, adjusting for age, sex and BMI.

Results

Of the 2757 participants (62% female, median baseline age: 52, IQR: 50-56 years), most were passive commuters at baseline (76%, n = 2099) and did not change their usual commute mode over 7 years (82%, n = 2277). In multivariable regression models, participants living further from work were less likely to take up active commuting and those living in neighbourhoods with more streetlights were more likely to take up active commuting (both p < 0.05). Findings for maintenance were similar: participants living further from work (over 10 km, OR: 0.06; 95% CI: 0.25 to 0.13) and had a main or secondary road on route were more likely to maintain their active commuting (OR: 0.52; 95% CI: 0.28 to 0.98). Those living in neighbourhoods with greater density of employment locations were more likely to maintain their active commuting.

Conclusions

Co-locating residential and employment centres as well as redesigning urban areas to improve safety for pedestrians and cyclists may encourage active commuting. Future evaluative studies should seek to assess the effects of redesigning the built environment on active commuting and physical activity.

SUBMITTER: Yang L

PROVIDER: S-EPMC5527401 | biostudies-literature | 2017 May

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Longitudinal associations between built environment characteristics and changes in active commuting.

Yang Lin L Griffin Simon S Khaw Kay-Tee KT Wareham Nick N Panter Jenna J

BMC public health 20170517 1

<h4>Background</h4>Few studies have assessed the predictors of changes in commuting. This study investigated the associations between physical environmental characteristics and changes in active commuting.<h4>Methods</h4>Adults from the population-based European Prospective Investigation into Cancer (EPIC)-Norfolk cohort self-reported commuting patterns in 2000 and 2007. Active commuters were defined as those who reported 'always' or 'usually' walking or cycling to work. Environmental attributes ...[more]

PMID: 28693547

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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.

Project description:In the current call for a greater human health and well-being as a sustainable development goal, to encourage active commuting to and from school (ACS) seems to be a key factor. Research focusing on the analysis of the association between environmental factors and ACS in children and adolescents has reported limited and inconclusive evidence, so more knowledge is needed about it. The main aim of this study is to examine the association between different built environmental factors of both school neighbourhood and home-school route with ACS of children and adolescents belonging to urban areas. The ACS level was evaluated using a self-reported questionnaire. Built environment variables (i.e., density of residents, street connectivity and mixed land use) within a school catchment area and home-school route characteristics (i.e., distance and pedestrian route directness-PRD) were measured using a geographic information system (GIS) and examined together with ACS levels. Subsequently, the association between environmental factors and ACS was analysed by binary logistic regression. Several cut-off points of the route measures were explored using receiver operating characteristic (ROC) curves. In addition, the PRD was further studied regarding different thresholds. The results showed that 70.5% of the participants were active and there were significant associations between most environmental factors and ACS. Most participants walked to school when routes were short (distance variable in children: OR = 0.980; p = 0.038; and adolescents: OR = 0.866; p < 0.001) and partially direct (PRD variable in children: OR = 11.334; p < 0.001; and adolescents: OR = 3.513; p < 0.001), the latter specially for children. Mixed land uses (OR = 2.037; p < 0.001) and a high density of street intersections (OR = 1.640; p < 0.001) clearly encouraged adolescents walking and slightly discouraged children walking (OR = 0.657, p = 0.010; and OR = 0.692, p = 0.025, respectively). The assessment of ACS together with the environmental factors using GIS separately for children and adolescents can inform future friendly and sustainable communities.

Dataset Information

Longitudinal associations between built environment characteristics and changes in active commuting.

Background

Methods

Results

Conclusions

Publications

Longitudinal associations between built environment characteristics and changes in active commuting.

Similar Datasets

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