The aim of the current review was to assess the intensity of physical activity when riding an e-bike, and to examine the physiological and psychological outcomes associated with e-cycling. Where possible these outcomes were compared to traditional methods of active travel (i.e., walking and cycling). Eleven acute and six longitudinal studies were identified. There was moderate evidence that e-cycling provides moderate intensity physical activity in both physically active and inactive individuals. Furthermore, there was moderate evidence that e-cycling positively impacted cardiorespiratory fitness in physically inactive individuals. The impact of e-cycling on health outcomes beyond physical fitness was inconclusive given the sparsity of current research.
Quality of the evidence
The quality of all studies, bar one [30], was weak to moderate. These ratings should be viewed with caution as the purpose of physiological studies, such as the acute experiments reported here, is to explore a specific event in a controlled environment with less focus on obtaining representative samples. As such, many studies did not report how participants were recruited, leading to a weak rating for the selection bias component of the assessment. Study design, control of confounders and methods of assessment are often considered more crucial in these designs, all of which were strong in the acute studies reported here. Furthermore, while blinding is often unachievable in physical activity interventions, the use of objective methodology limits the impact of research bias on the outcomes.
Regarding longitudinal studies, methods of data collection were consistently strong, but with large variation in representativeness, design and reporting of withdrawals and dropouts. Confounders were considered in the context of differences between groups and were therefore rated as strong if studies used a single-group design. One pilot randomized control trial was conducted and was rated as strong [30]. Overall, there was a lack of high-quality longitudinal intervention-based research including pre-post measures examining the impact of e-cycling on physiological and psychological health outcomes.
The impact of e-cycling on physical activity intensity
To accrue health benefits, The American College of Sports Medicine recommend healthy adults engage in moderate-to-vigorous physical activity for 150-min per week [14]. Moderate intensity activity is classified as three to six metabolic equivalents (METs) and vigorous intensity activity at six METs or above. The current review suggests that e-cycling, even while using a high assistance mode, provides physical activity of at least moderate intensity on a variety of terrain, including downhill. Furthermore, e-cycling can elicit vigorous activity during uphill riding [18] and during rides with highly varied terrain [18, 26]. Interestingly, Bernsten and colleagues [22] reported that mean estimated METs were lower than mean measured METs during e-cycling. Estimated METs have been suggested to overestimate resting energy expenditure, thereby underestimating activity energy expenditure [34]. As such, the mean estimated METs reported in this review provide a conservative estimate of exercise intensity.
Relative physiological outcomes further suggest that e-cycling is performed at a moderate intensity with the percent of maximum heart rate ranging from 67.1 to 79.1 and the percent of VO2peak/max ranging from 51 to 75. These values exceed the hypothesised minimum intensity thresholds required for improvements in cardiorespiratory fitness in healthy adults [14, 35, 36].
E-cycling vs. traditional active transportation
Three studies compared e-cycling to walking [18, 23, 32] of which one compared the two modes on the same route [23]. In this study walking led to lower oxygen uptake than e-cycling across all topographies, though significant MET differences were only reported during uphill sections, with e-cycling expending more energy than walking. The few studies conducted suggest e-cycling is performed at a higher intensity than walking, however, more studies are needed to confirm these trends.
In relation to conventional cycling, this review suggests that e-cycling elicits lower physiological markers of intensity than conventional cycling, however the strength of this finding depends on the physiological assessment measure and route topography. Overall, mean percent of VO2max/peak is similar between conventional cycling and e-cycling ranging from 58 to 74% and 51 to 73% respectively. Studies examining active commuting on conventional bikes have reported similar mean percent of VO2max in healthy adults ranging from 57 to 79% [6, 37]. However, mean relative oxygen uptake is lower during e-cycling compared to conventional cycling or e-cycling without assistance. Similarly, means and medians of estimated METs are consistently higher during conventional cycling or e-cycling without assistance compared to assisted e-cycling, with values ranging from 6.1 to 8.5 and 4.9 to 8.3 respectively, though the significance of the differences varied across studies.
La Salle and colleagues [26] reported similar MET values between e-cycling and conventional cycling. However, the values reported were substantially higher than those reported in other studies, with mean estimated METs of 8.3 and 8.5 for e-cycling and conventional cycling respectively. Participant demographics may have accounted for these differences, since participants were younger and had previous cycling experience. These participants may have had higher aerobic capacity and therefore self-selected a higher intensity activity level at which to complete the conditions. This is likely given that the relative intensity of activity is similar in studies of e-cycling in physically inactive individuals [13, 18,19,20, 30, 32]. When given the choice to self-select pace and intensity individuals may select a similar physiological intensity across activities regardless of the mechanical assistance, thereby resulting in similar physiological outcomes. In support of this, when individuals were required to maintain a cycling cadence of 60 revolutions per minute throughout a condition, there were significant differences in oxygen uptake and heart rate between e-bikes and conventional bikes [18] compared to studies in which individuals were able to self-selected their intensity [21, 22, 26]. Similarly, when instructed to complete 60-meters of riding in 10-sec for a total of 30-min the reported relative VO2max was 29 ml/min/kg for e-cycling and 37 ml/min/kg for conventional cycling [25]. This suggests that performing the same amount of work requires more effort on a conventional bike than an e-bike, but that human beings reduce the amount of work conducted on a conventional bike, through choosing a slower speed, to account for the increase in expended effort.
In hilly terrain, where there is less opportunity to adjust effort levels to produce comparable intensity levels, the differences between conventional cycling and e-cycling may become more pronounced, with e-cycling requiring lower intensity activity, as found in studies comprised of routes with hilly features [18, 23]. This suggests that e-bikes are less sensitive to environmental factors such as topography. Therefore, physiological measures of intensity are lower on the e-bike than those reported on a conventional bike during uphill riding. The reduced intensity required during uphill riding when using an e-bike is one of the leading arguments for the promotion of e-bikes as an alternative mode of active transportation.
E-cycling and health
In the current review three studies provided weekly e-cycling goals for physically inactive individuals in the context of active commuting [13, 29, 30]. Two of these studies reported increases in VO2peak and maximum power output following 4-weeks of e-cycling [13, 30]. In contrast de Geus and colleagues [10] reported no changes in VO2peak following a 6-week intervention, though differences in maximum power output were seen. Differences between studies could be due to distance cycled. Specifically, both Hochsmann [30] and Peterman and colleagues [13] reported cycling distances of 70 km and 69.4 km per week respectively, compared to 54.3 km per week reported by de Geus [10]. The two studies reporting significant increases in fitness also described self-selected riding intensities of between 72.1 and 74.9% of maximum heart rate (within the moderate intensity zone [13, 30] with an average of 205 min (±43.3) of e-cycling per week [13]. This suggests that e-cycling can contribute to meeting weekly physical activity guidelines.
Without the provision of e-cycling goals, single group studies with physically inactive individuals reported increases in maximal power output of 7 to 10% over 3–8 months, despite lower average distance travelled than other studies [31, 32]. Fitness benefits were greatest in individuals classified as having low fitness [31], similar to findings with conventional cycling [6]. These results suggest that in the absence of specific goals (i.e., under free living conditions), participants engage in e-cycling and this e-cycling can contribute to improvements in fitness.
Beyond cardiorespiratory fitness, there is a lack of research examining the impact of e-cycling on physiological or psychological health outcomes, limiting our ability to draw conclusions. Peterman and colleagues [13] reported a decrease in 2-h plasma glucose during an oral glucose tolerance test after 4-weeks of e-cycling. This finding is in line with studies that have examined the impact of exercise on 2-h post exercise glucose concentrations in obese individuals [38, 39] but is novel in the context of e-cycling and conventional cycling. In the same study, no other metabolic changes were reported. Similar null effects on metabolic outcomes were reported in two systematic reviews on conventional cycling [37, 40].
E-cycling for public health?
Overall e-cycling can elicit at least moderate intensity physical activity. However, total energy expenditure when riding an e-bike is lower than when riding a conventional bike or walking over the same distance, given the reduced amount of time taken to complete a ride on an e-bike. Consequently, if e-cycling were to replace journeys made by walking or conventional cycling, individuals would have to ride for longer for comparable weekly energy expenditure. However, e-cycling is associated with lower ratings of perceived exertion than conventional cycling [23, 26], potentially enabling people to ride more frequently or for a longer duration. This possibility is supported by Hendriksen and colleagues [41], who reported that individuals in the Netherlands commuted 50% further with an e-bike than on a conventional bike.
Findings reported here suggest that e-cycling may be suitable for individuals with compromised health. Hansen and colleagues [21] showed that e-cycling elicited moderate intensity activity in older, obese individuals recovering from surgery due to coronary artery disease, while Cooper and colleagues [32] reported that e-cycling was feasible for middle-aged, overweight individuals with type 2 diabetes mellitus.
Overall, while there is a trend towards increased fitness following engagement in e-cycling interventions, more intervention research of a longer duration is required before the long-term impact of e-cycling on health can be determined. Fifty percent of the longitudinal studies in this review were approximately 1-month in length. This may not be enough time to see changes in body composition and some metabolic outcomes. Longer trials with larger samples sizes should be conducted with a focus on including a range of health outcomes in addition to cardiorespiratory fitness. These trials should utilize randomized controlled designs and clearly report their target population, recruitment process and dropouts and/or withdrawals. Interventions should also be conducted in clinical populations where physical activity is compromised. In addition, more research is needed to understand the impact of e-cycling on health based on sex or fitness level.
It is also important to consider the negative outcomes associated with e-cycling when assessing their potential utilization for health promotion. In the USA, e-bike users reported feeling safer riding their e-bike than a conventional bike, stating that the e-bike helped them to avoid crashes due to their stability, powerful brakes and the acceleration to avoid incidents and keep up with traffic. However, riders reported cycling faster on an e-bike than a conventional bike and felt that other road users misjudged their speed leading to potentially dangerous situations [42]. In the Netherlands data suggest that, after controlling for age, gender and amount of cycling, use of an e-bike was associated with an increased risk of being involved in a crash compared to conventional cycling [43]. The severity of these crashes was not significantly different from conventional cycling [43]. More context specific research is required to enable a risk-benefit assessment of engaging specifically in e-cycling. Nevertheless, e-cyclists would be well advised to be appropriately trained and use safety equipment to minimize risk.
Strengths and limitations
This is the first review to examine the physical activity intensity, cardiorespiratory, metabolic and psychological outcomes associated with e-cycling. This review used two pragmatic tools to assess the quality of studies and to provide an overall rating of the evidence. These tools provided an overall representation of the strength of research evidence related to e-cycling and health. Limitations of this review include the fact that some published studies may not have been identified. However, our systematic and broad search strategy makes this unlikely. It is more likely that we did not identify eligible unpublished studies or those published in an alternative language to English. Sample sizes used in studies were small and sample size calculations were rarely reported. Therefore, caution should be taken when interpreting the statistical significance of evidence. Given the heterogeneity in outcome measurement we were unable to quantify the effects of e-cycling on outcomes of interest using meta-analyses. In addition, focus on quality of life as a psychological outcome may have meant studies examining psychological outcomes such as depression or anxiety were excluded.