There is strong evidence that health benefits comprise the majority of the benefits accrued from engagement in active travel. The effect is most pronounced at an individual level (Rabl & de Nazelle, 2012), but results in benefits to society through the associated savings to the NHS. The negative impact of insufficient physical activity on both physical and psychological health has been conclusively established. Evidence is strongest for the heightened risk of several chronic health conditions, including: cardiovascular disease (CVD), stroke, obesity, colon and breast cancer, type II diabetes, osteoporosis, depression and anxiety (TRL, 2018; Davis, 2014). In older adults, it has also been linked to reduced levels of functional ability (World Health Organisation, 2017).
Research demonstrates that active travel can contribute to meeting the recommended minimum levels of physical activity across all age groups provided that it be sufficiently frequent and intensive (Rissel, et al., 2012; Flint, et al., 2014; Petrunoff, et al., 2016). It has been suggested that integrating active travel into a commute is a sustainable way of engaging in exercise which is important as maintaining consistent levels of physical activity is crucial to accruing the associated health benefits.
Men and members of ethnic minorities are estimated to benefit more from active travel than the general population. Additionally, adults over the age 45 are estimated to benefit more overall from a mode shift to active travel than younger people (Mueller, et al., 2015), due to older adults being at increased risk of developing chronic health conditions. Unfortunately, the research suggests that this age group is less likely to participate in active travel (Department for Transport, 2016). However Halfords (2018) reports that 62% of e-bikes in the UK are sold to people aged 55 years and above, with 79% of those sales made by new customers to the cycling range. As research suggests that e-bikes can contribute to meeting some of recommended levels of physical activity, this could have promising implication for widening access of the health benefits of active travel to individuals with reduced mobility or physical ability (TRL, 2018).
Meeting the recommended levels of physical activity is associated with a reduction in all-cause mortality (Shaw, et al., 2020). A number of studies use the World Health Organisation’s (WHO) HEAT tool when calculating the reduction in all-cause mortality as a result of active travel. Compared to a non-walker or cyclist’s relative risk of all-cause death of 1.0, an individual walking 168 minutes a week (52 weeks/year) at an average of 4.8 km/hour yields a relative risk of death of 0.88 (World Health Organisation, 2017). The relative risk for cycling is 0.90, based on a scenario of 100 minutes/week (52 weeks/year) at an average speed of 14 km/hour (World Health Organisation, 2017).
The HEAT tool assumes a linear association between physical activity and health outcomes, however health benefits are subject to a dose-response relationship. As such higher levels of physical activity result in a larger percentage of risk reduction in all-cause mortality and the stated causes of morbidity. Additionally, while any amount of physical activity is beneficial, with substantial health gains at lower levels of activity, improved health outcomes are not immediate but require maintained levels of physical activity over time to accrue (Kyu, et al., 2016). Based on the latest available evidence, a five-year period of sustained levels of physical activity is generally considered to be necessary to reap the maximum health benefits. Finally, the evidence suggests that the decrease in risk reduction for both morbidity and mortality is minimal at very high levels of physical activity (3000-4000 metabolic MET minutes/week) (Kyu, et al., 2016). Consequently, WHO (2017) caps the percentage risk reduction in all-cause mortality after five years at 30% for walking (scenario assumes 460 minutes/week) and 45% for cycling (447 minutes/week).
Meeting the recommended levels of physical activity is also associated with a reduction in the incidence or severity of several health conditions including: CVD, type II diabetes, obesity, colon and breast cancer, and stroke (Mueller, et al., 2015). In older adults it is additionally linked to reductions in hypertension, falls (which includes resulting fractures), hospitalisation for CVD events, and improved muscular and strength function (LaCroix, et al., 1996; Vogel, et al., 2009). Kyu et al. (2016) recently conducted a meta-analysis on existing research in order to quantify the dose response association between total physical activity and the risk of five of the most prevalent chronic diseases: breast and colon cancer, diabetes, ischemic heart disease and ischemic stroke. The results indicate that the effect physical activity has a strong association with decreased risk of contracting diabetes and that substantial risk-reduction can be obtained at lower levels of physical activity (see Table 4).
Table 4. Risk of contracting five chronic diseases by level of physical activity.
Source: (Kyu, et al., 2016)
||low active (600-3999 MET minutes/week)
||moderately active (4000-7999 MET minutes/week)
||highly active (≥8000 MET minutes/week)
|Breast cancer (women only)
|Ischemic heart disease
Celis-Morales, et al. (2017) monitored 263540 adult commuters aged between 40-69 across 22 sites in the UK over a median follow up period of five years. They found that cycling is associated with higher levels of risk-reduction in all-cause mortality, and both CVD and cancer incidence than walking, though significant reductions are found for both (see Table 5).
Table 5. Average risk reduction by mode of travel (blank cells denote no significant associations found)
Source: (Celis-Morales, et al., 2017)
|Causes of Mortality
||Mixed including walking
||Mixed including cycling
It is important to note that the impact from active travel on health outcomes will vary depending on an individual’s baseline levels of physical activity. This is often not taken into account in studies such as Celis-Morales et al.’s (2017) which only looks at the amount of physical activity undertaking through active travelling (Department for Transport, 2016). This may result in inflating the impact of active travel on mortality and morbidity percentage risk reduction estimates. In addition, studies don’t systematically consider whether active travel may be replacing other forms of physical activity and therefore whether it constitutes an increase in total physical activity levels of instead a substitution. Substitution could result in a net reduction in the amount of time spent physically active and thus a reduction in the dose proportional health benefits. For example, replacing a walked commute with a cycled one produces less benefits per mileage travelled as the intensity and duration of an actively travelled trip is key to accruing increased health benefits.
Despite these limitations to existing research, these is a consensus that a mode shift to active travel results in substantial health benefits at an individual level, irrespective of baseline activity levels, geographical context or the varying assumptions on health pathways adopted within models (Humphreys, et al., 2013; Mueller, et al., 2015; Department for Transport, 2016).
The evidence for the impact of physical activity and active travel on mental health and wellbeing is less clear. In older adults it has been associated with reduced incidence of dementia (Vogel, et al., 2009). Large and sustained amounts of walking appears to reduce loss of grey matter in older age with possible corollary benefits in terms of lowering levels of cognitive decline and dementia (Erickson, et al., 2010).
Active commuters also self-report increased levels of psychological wellbeing (Martin, et al., 2014), and physical exercise has been found to be beneficial to the management and treatment of anxiety and depression (Fox, 1999; Paluska & Schwenk, 2000). The impact on academic performance is also contested as while there is stronger evidence that physical activity has beneficial effects on maths performance, the impact on overall academic performance is inconclusive (Davis, 2014; Singh, et al., 2019).
Increased exposure to pollutants is cited as an impact of a modal switch to active travel (Rojas-Rueda, et al., 2013), the extent of which is context-dependent (Rabl & de Nazelle, 2012; MacNaughton, et al., 2014). However literature indicates that individual generally do not factor this into their decision making when taking up active travel and, more importantly, that the overall health benefits accrued outweigh this negative impact (Rabl & de Nazelle, 2012).
There is conflicting evidence regarding the impact of a mode shift to active travel on individual levels of risk exposure. Walking and cycling are considered high risk modes and increases in active travel are generally estimated to result in an increase in traffic fatalities or injuries. However a majority of research agrees that this can only be evaluated on a case-by-case basis due to the estimations of risk being highly context-dependent (Mueller, et al., 2015; Department for Transport, 2016).
Some evidence suggests that risk for cycling casualties may decline in communities where cycling is a higher mode share. This relationship between number of walkers or cyclists on the road and the likelihood of being involved in an incident with a motorist is known as the “safety in numbers effect” (Jacobsen, 2003). While this effect has been found irrespective of geographical context and time periods, there is no consensus on how or indeed at what number of active travellers it occurs (Mueller, et al., 2015). In addition, the results may be affected by under-reported cases of minor injuries.
Once again however, the overall health benefits are widely considered to outweigh any changes in the levels of risk at an individual level (Rabl & de Nazelle, 2012; Mueller, et al., 2015; Department for Transport, 2016)
While health benefits are widely considered to account for between half and two thirds of the monetised benefits of active travel schemes and interventions, meta-analysis and reviews tend to refrain from venturing a monetary estimate of health care savings (Department for Transport, 2016). This is a result of a number of factors: the variation in health conditions and health pathways considered; the variation in levels and forms of activity included in the study sample; a large number of case-study evidence relying on small sample sizes; and a variation in the sample demographics. Furthermore, the resulting predicted savings are often based on an assumed substantial increase in active travel numbers or are too specific to be representative at a national level.