Elsevier

The Lancet

Volume 379, Issue 9832, 9–15 June 2012, Pages 2198-2205
The Lancet

Review
Effect of increasing active travel in urban England and Wales on costs to the National Health Service

https://doi.org/10.1016/S0140-6736(12)60766-1Get rights and content

Summary

Increased walking and cycling in urban areas and reduced use of private cars could have positive effects on many health outcomes. We estimated the potential effect of increased walking and cycling in urban England and Wales on costs to the National Health Service (NHS) for seven diseases—namely, type 2 diabetes, dementia, cerebrovascular disease, breast cancer, colorectal cancer, depression, and ischaemic heart disease—that are associated with physical inactivity. Within 20 years, reductions in the prevalences of type 2 diabetes, dementia, ischaemic heart disease, cerebrovascular disease, and cancer because of increased physical activity would lead to savings of roughly UK£17 billion (in 2010 prices) for the NHS, after adjustment for an increased risk of road traffic injuries. Further costs would be averted after 20 years. Sensitivity analyses show that results are invariably positive but sensitive to assumptions about time lag between the increase in active travel and changes in health outcomes. Increasing the amount of walking and cycling in urban settings could reduce costs to the NHS, permitting decreased government expenditure on health or releasing resources to fund additional health care.

Introduction

Increasing urban active travel (mainly walking and cycling) could yield many benefits, including improvement of public health by increasing physical activity and reducing air and noise pollution,1, 2 traffic congestion, and CO2 emissions.1, 2, 3, 4 Woodcock and colleagues5 used London and New Delhi as examples to assess the potential health effects from implementation of increased active transport strategies. For London, they estimated that doubling of average distances walked per day and an eight-fold increase in the amount of cycling could lead to substantial reductions in the burden of disease due to type 2 diabetes, dementia, depression, ischaemic heart disease, cerebrovascular disease, breast cancer, and colon cancer. The results of a sensitivity analysis showed that smaller increases in distances walked and cycled resulted in benefits to health.

We estimated the potential economic effect of increased walking and cycling in urban England and Wales on the National Health Service's (NHS) expenditure on type 2 diabetes, dementia, cerebrovascular disease, breast cancer, colorectal cancer, depression, and ischaemic heart disease. We focused on the health gains made because of increased physical activity, because in a previous study5 increases in physical activity resulted in more health gains than did reductions in air pollution. We included the effect of road traffic injuries as a potential harmful side-effect of increased walking and cycling. Reductions in long-term and geographically disparate effects of climate change were not modelled and are associated with uncertainty.

Section snippets

Active travel scenarios

Panel 1 shows the two active travel scenarios. The transport and carbon simulation visioning and backcasting for transport (VIBAT) London programme was used to design the scenarios.6 An average daily cycling distance of 3·4 km is assumed in the main active travel scenario, compared with an average distance of 3 km in Copenhagen during 2010.7, 8

We assumed that the increase in walking and cycling previously modelled for London also occurred throughout all urban areas in England and Wales. Urban

Modelling of health effects

The health benefits of increased active transport were modelled for the period 2012–31 with the WHO comparative risk assessment method, which is defined as “the systematic evaluation of the changes in population health which result from modifying the population distribution of exposure to a risk factor or a group of risk factors”.12 Seven health outcomes for which the link between physical inactivity and increased disease risk is well established were included—ie, type 2 diabetes, dementia,

Modelling of road traffic injuries

To include the effect of road traffic injuries, we used Woodcock and colleagues' data.5 Their model estimated the change in road traffic injuries that would be expected from the combined effects of less motor-vehicle traffic (because of less exposure to cars by pedestrians, cyclists, and other motor-vehicle users) and increased walking and cycling (because of more exposure of pedestrians and cyclists to motor traffic). In addition to passenger travel, heavy goods vehicles have an especially

Modelling of cost effects

We searched PubMed and disease-specific foundation reports in July 2011 with the search term “costs” and the name of the disease in question to obtain average yearly treatment costs per patient. Treatments costs were derived for the first year of diagnosis, as were yearly costs thereafter for the average duration of each disorder. The criteria for including a study were that the data had been gathered on or after Jan 1, 2001, and that the estimates were derived from a representative sample of

Sensitivity analysis

We did several sensitivity analyses to test the assumptions made in the model. In the main scenario, per-head travel distances were assumed to remain constant. However, per-head travel times are much more consistent than are per-head travel distances, so a move to typically slower modes of transit might lead to a reduction in travel distances.36 Therefore, a second (shorter distances) scenario was modelled in which we assumed that the increase in walking and cycling was only half that in the

Discussion

The money released from the NHS budget because of increased walking and cycling could result in health-care benefits if spent on other health priorities; however, to estimate these additional benefits was beyond the scope of our model. Our findings suggest that during the 20-year period as much as 1% of the yearly budget for health care in England and Wales (and possibly even more after 20 years) could be made available for reallocation by increased walking and cycling in urban areas. Aversion

Limitations

Our model does not take into account the effect of walking and cycling on environmental factors such as improved air quality because of reduced vehicle emissions, or on health-related outcomes such as a fall in the prevalences of overweight and obesity. An estimate42 of the costs of obesity to the NHS suggests that these savings could amount to £2 billion per year by 2030. Thus, even slight reductions in obesity because of increased walking and cycling could have substantial additional economic

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