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Publications - ISI Article

Health effects of active mobility and their economic value: Unit
benefit factor estimates for Italy

Publications - ISI Article

Health effects of active mobility and their economic value: Unit
benefit factor estimates for Italy

This study quantifies, in economic terms, the health benefits associated with the shift from passive to active mobility (walking, biking, and e-biking) in some Italian cities to identify unit benefit factors to be used for developing mobility policies. The impacts are estimated by measuring the change in expected mortality, considering both positive effects (increased physical activity) and negative ones (increased inhalation of air pollutants and risk of accidents) associated with change in mode. The quantification takes into account the demographic structure and specific mortality rates of each city and age group, as well as previous physical activity levels. The positive effects of active mobility outweigh the negative ones for all means considered, although with significant differences between the means and cities considered. Walking generates far more benefits than biking or e-biking, and in particularly polluted cities, the overall benefit may be null in the case of e-bikes.

The study quantifies the economic benefits for health generated by the transition from passive modes of transport (cars and motorcycles) to active modes in Italy, aiming to define benefit factors to be used in the development of mobility policies.

 

The active transport modes considered are walking, biking, and e-biking.

 

Methodology: The quantification is carried out through the development of a ten-year scenario for several Italian cities. The switch from passive to active mobility has beneficial health effects due to increased physical activity but also passive effects due to greater exposure to air pollutants and a higher risk of road accidents. Health impacts are measured through changes in expected mortality, considering mortality rates and demographic structures specific to each city. The level of previous physical activity is also considered by age group. The change in the mortality rate due to the change in the mode of transport is converted into economic terms using the value of a life year (VOLY) and the value of a statistical life (VSL). The unit benefit factors are expressed in euros/km, based on the total distances traveled over the scenario period.

 

Results: The health benefit guaranteed by increased physical activity is greater than the damage caused by increased exposure to pollutants and a higher risk of injuries. However, there are significant differences between the modes considered: the average benefit is 0.32 euros/km for walking and much lower in the case of biking and e-biking (0.06 and 0.02 euros/km) due to different levels of physical exertion, duration of activity, and lung ventilation. In cities with high concentrations of background air pollutants, the health benefit may be null in the case of e-bikes.

 

Conclusions: This is the first work that uses VOLY for assigning economic value to health benefits and evaluates the health effects of e-bike use. It also considers the demographic structure and previous physical activity levels of the population. The main limitation is that the calculated impacts are based only on changes in mortality and do not consider morbidity.

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