Dataset Information

Contrasts in active transport behaviour across four countries: how do they translate into public health benefits?

ABSTRACT:

Objective

Countries and regions vary substantially in transport related physical activity that people gain from walking and cycling and in how this varies by age and gender. This study aims to quantify the population health impacts of differences between four settings.

Method

The Integrated Transport and Health Model (ITHIM) was used to estimate health impacts from changes to physical activity that would arise if adults in urban areas in England and Wales adopted travel patterns of Switzerland, the Netherlands, and California. The model was parameterised with data from travel surveys from each setting and estimated using Monte Carlo simulation. Two types of scenarios were created, one in which the total travel time budget was assumed to be fixed and one where total travel times varied.

Results

Substantial population health benefits would accrue if people in England and Wales gained as much transport related physical activity as people in Switzerland or the Netherlands, whilst smaller but still considerable harms would occur if active travel fell to the level seen in California. The benefits from achieving the travel patterns of the high cycling Netherlands or high walking Switzerland were similar.

Conclusion

Differences between high income countries in how people travel have important implications for population health.

SUBMITTER: Gotschi T

PROVIDER: S-EPMC4456468 | biostudies-literature | 2015 May

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Contrasts in active transport behaviour across four countries: how do they translate into public health benefits?

Götschi Thomas T Tainio Marko M Maizlish Neil N Schwanen Tim T Goodman Anna A Woodcock James J

Preventive medicine 20150224

<h4>Objective</h4>Countries and regions vary substantially in transport related physical activity that people gain from walking and cycling and in how this varies by age and gender. This study aims to quantify the population health impacts of differences between four settings.<h4>Method</h4>The Integrated Transport and Health Model (ITHIM) was used to estimate health impacts from changes to physical activity that would arise if adults in urban areas in England and Wales adopted travel patterns o ...[more]

PMID: 25724106

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Project description:ObjectiveBased on regulatory focus theory, it was predicted that there would be a relationship between regulatory focus, health-related perceived risk of using public transport during COVID-19, and choice of public transport mode.MethodThe study focused on choice between demand responsive transport (DRT), and more traditional modes of public transport, buses and private taxis. Participants completed online questionnaires to measure chronic regulatory focus, perception of health-related risk of using public transport, and choice of public transport mode (choice between buses and DRT, and separately, between taxis and DRT).ResultsThe choice between buses and DRT is explained by moderation. The relationship between promotion focus and choice is moderated by risk perception whereas the relationship between prevention focus and choice is moderated by age. Specifically, the probability of choosing DRT is smaller for those saying DRT is riskier (relative to bus is riskier), and the effect gets stronger with increasing strength of promotion focus. Furthermore, the probability of choosing DRT increases with increasing strength of prevention focus for individuals older in age, but decreases with increasing strength of prevention focus for those younger in age. The choice between taxis and DRT is explained by mediated-moderation. The relationship between promotion focus and choice is moderated by age and mediated by risk perception. Specifically, the probability of saying that DRT is riskier than taxis decreases with increasing strength of promotion focus for individuals older in age. As a result, the probability of choosing DRT increases with increasing strength of promotion focus for older people. Moreover, the probability of saying that DRT is riskier than taxis increases with increasing strength of promotion focus for individuals younger in age. As a result, the probability of choosing DRT decreases with increasing strength of promotion focus for younger people. Implications for transport and health are discussed.

Project description:PurposeTo strengthen our understanding of the impact of baseline variability in mode choice on the likelihood of travel behaviour change.MethodsQuasi-experimental analyses in a cohort study of 450 commuters exposed to a new guided busway with a path for walking and cycling in Cambridge, UK. Exposure to the intervention was defined using the shortest network distance from each participant's home to the busway. Variability in commuter travel behaviour at baseline was defined using the Herfindahl-Hirschman Index, the number of different modes of transport used over a week, and the proportion of trips made by the main (combination of) mode(s). The outcomes were changes in the share of commute trips (i) involving any active travel, (ii) involving any public transport, and (iii) made entirely by car. Variability and change data were derived from a self-reported seven-day record collected before (2009) and after (2012) the intervention. Separate multinomial regression models were estimated to assess the influence of baseline variability on behaviour change, both independently and as an interaction effect with exposure to the intervention.ResultsAll three measures of variability predicted changes in mode share in most models. The effect size for the intervention was slightly strengthened after including variability. Commuters with higher baseline variability were more likely to increase their active mode share (e.g. for HHI: relative risk ratio [RRR] for interaction 3.34, 95% CI 1.41, 7.89) and decrease their car mode share in response to the intervention (e.g. for HHI: RRR 7.50, 95% CI 2.52, 22.34).ConclusionsPeople reporting a higher level of variability in mode choice were more likely to change their travel behaviour following an intervention. Future research should consider such variability as a potential predictor and effect modifier of travel and physical activity behaviour change, and its significance for the design and targeting of interventions.

Dataset Information

Contrasts in active transport behaviour across four countries: how do they translate into public health benefits?

Objective

Method

Results

Conclusion

Publications

Contrasts in active transport behaviour across four countries: how do they translate into public health benefits?

Similar Datasets

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