Integrated health impact assessment of travel behaviour: Model exploration and application to a fuel price increase

Abstract

Transportation policy measures often aim to change travel behaviour towards more efficient transport. While these policy measures do not necessarily target health, these could have an indirect health effect. We evaluate the health impact of a policy resulting in an increase of car fuel prices by 20% on active travel, outdoor air pollution and risk of road traffic injury. An integrated modelling chain is proposed to evaluate the health impact of this policy measure. An activity-based transport model estimated movements of people, providing whereabouts and travelled kilometres. An emission- and dispersion model provided air quality levels (elemental carbon) and a road safety model provided the number of fatal and non-fatal traffic victims. We used kilometres travelled while walking or cycling to estimate the time in active travel. Differences in health effects between the current and fuel price scenario were expressed in Disability Adjusted Life Years (DALY). A 20% fuel price increase leads to an overall gain of 1650 (1010-2330) DALY. Prevented deaths lead to a total of 1450 (890-2040) Years Life Gained (YLG), with better air quality accounting for 530 (180-880) YLG, fewer road traffic injuries for 750 (590-910) YLG and active travel for 170 (120-250) YLG. Concerning morbidity, mostly road safety led to 200 (120-290) fewer Years Lived with Disability (YLD), while air quality improvement only had a minor effect on cardiovascular hospital admissions. Air quality improvement and increased active travel mainly had an impact at older age, while traffic safety mainly affected younger and middle-aged people. This modelling approach illustrates the feasibility of a comprehensive health impact assessment of changes in travel behaviour. Our results suggest that more is needed than a policy rising car fuel prices by 20% to achieve substantial health gains. While the activity-based model gives an answer on what the effect of a proposed policy is, the focus on health may make policy integration more tangible. The model can therefore add to identifying win-win situations for both transport and health.

Air pollution as a risk factor in health impact assessments of a travel mode shift towards cycling

“…Rojas-Rueda et al [38] and Woodcock et al [39] evaluated the current benefit of increased cycling due to a public bicycle-sharing program. Dhondt et al [40] simulated the travel activity patterns before and after an increase in fuel prices, while Macmillan et al [41] simulated the effects of policy changes employing the System Dynamics Modelling.…”

“…Thirteen studies used a comparative risk assessment approach for quantification of health risks or benefits of a change from motorized transport to cycling [22,34–40,42–46]. The economic impacts of transport interventions were estimated in four studies using a cost benefit analysis approach [41,47–49], while a benefit analysis without focusing on risks or costs was conducted in one study [50].…”

“…Important health endpoints that were evaluated in the studies were (a) mortality, including cause-specific mortality, all-cause mortality, and fatalities; (b) morbidity, including cardiovascular diseases, respiratory diseases, diabetes type 2, cancer, dementia, depression, and injuries; and (c) burden of disease (BoD), including both morbidity and mortality in the form of years of life lost (YLL) and years lost due to disability (YLD). Some studies also included individual health events such as disease-specific hospital admission, activity restriction days, and emergency room visits [40,48,50]. Buekers et al [47] and Rabl et al [49] expressed the impacts using the equivalent monetary benefits approach of Value of a Life Year (VOLY) [51].…”

“…The health impacts of increased physical activity resulting from increased cycling were evaluated in all studies. Physical activity was mainly reported as distance or time spent in active travel, except in seven studies – Dhondt et al [40], Maizlish et al [34], Woodcock et al [35,36,39], Buekers et al [47] and Rojas-Rueda et al [43] – where it was expressed as metabolic equivalent of task (MET) hours per week. All except two studies – Holm et al [42] and Xia et al [46] – measured physical activity as a continuous variable and employed published risk estimates to evaluate the health impacts of increased cycling.…”

“…Nine studies examined the air pollution impact on the general population [34–37,40,41,46,48,50], four estimated impacts on active commuters [38,39,42,43], and five included impacts on both the general population and active commuters [22,44,45,47,49]. The included studies modeled both particulate and gaseous pollutants such as particulate matter (PM) less than 2.5 µm and less than 10 µm (PM2.5 and PM10), sulfur dioxide, nitrogen dioxide (NO 2) and nitrogen oxides (NOx), carbon monoxide, ammonia, etc.…”