Metabolic and Cardiovascular Responses to a Simulated Commute on an E-Bike

Short term e-bicycle riding results in favorable cardiometabolic shifts in moderately active adults

PURPOSE

Electric bikes (EB) are a form of active transportation with demonstrated health benefits. The purpose of this study was to determine the influence of riding an EB for one week on indices of cardiometabolic health in middle-aged adults.

METHODS

Adults (n = 22; age = 57.1 ± 11.3 year; BMI = 27.7 ± 4.9) participated in a 2 week study. During Week 1, participants were instructed to continue regular activities. Starting Week 2 participants were provided an EB to ride at least 3 days for a minimum of 30 min·day-1. Physical activity (PA) and glucose were measured continuously. Body composition, blood lipids, glucose, insulin, hemoglobin A1c (HbA1c), plasma endothelin-1 (ET-1), and carotid-femoral pulse wave velocity (cf-PWV) were measured on days 1 and 14.Data and Statistical analyses or Statistics. Each participant served as their own control. Paired t-tests compared dependent variables between week 1 (without EB) and week 2 (with EB).

RESULTS

When provided an EB for one week, moderate to vigorous PA increased by 6-9 min·day-1 (P < 0.05) and sedentary time decreased by ~ 77 min·day-1 (P < 0.05). Data from 24 h continuous glucose monitoring showed the percentage of time in healthy range (70-120 mg·dl-1 glucose) increased (P < 0.05) from week 1 to week 2. Compared to day 1, cf-PWV was lower at day 14 (P < 0.05) following one week of riding an EB.

CONCLUSION

Moderately-active, middleaged adults showed improved continuous glucose regulation and lower central arterial stiffness following one week of riding an EB.

Physical activity when riding an electric-assisted bicycle with and without cargo

Background

Regular physical activity provides several health benefits, and active transport is a convenient way to implement physical activity in everyday life. However, bikes' lack of possibilities to carry cargo is a limitation. E-cargo bikes can help overcome barriers to cycling and increase levels of active transport while still providing the option to carry cargo such as groceries and children. As such, E-cargo bikes have a greater potential for being a substitute for cars, but relevance is not known as no study has assessed the energy expenditure and time used using E-cargo bikes with considerable cargo.

Objectives

The aim of this study is to compare time spent riding and exercise intensity when (1) riding an electric-assisted bicycle with cargo (30 kg) and without cargo and (2) driving a car.

Method

This study has a randomised crossover design. Eleven participants (six women) were recruited through convenience sampling. The participants traversed through a 4.5 km route with three different forms of transportation: an electric-assisted bicycle (E-bike) with 30 kg cargo, an E-bike without cargo, and a car. Oxygen uptake was measured with a portable oxygen analyser (Metamax 3B), and time spent cycling was measured on site by the test leader using a stopwatch.

Results

Riding an E-bike with cargo was slightly slower than riding an E-bike without cargo (11.8 vs. 11.1 min, p = 0.017) and driving a car (8.8 min, p = 0.002). There was no significant difference in exercise intensity between E-bikes with and without cargo but riding an E-bike with cargo entailed significantly higher exercise intensity compared to driving a car [4.9 metabolic equivalents of task (METs) vs. 1.4 METs, p ≤ 0.001].

Conclusions

E-biking with cargo was rather similar in time spent and exercise intensity to E-biking without cargo, and not much slower than driving a car. Using E-cargo bikes, therefore, appears a good alternative to driving a car when in need of carrying things such as grocery bags and children, resulting in increasing physical activity and, at the same time, decreasing greenhouse gas emissions.

Public Health-Led Insights on Electric Micro-mobility Adoption and Use: a Scoping Review

The advent of electric micro-mobility (EMM) has transformed the urban mobility landscape, with projections indicating a 5-10% increase in its modal share in European cities by 2030. In this scoping review, we aimed to comprehensively examine the key determinants of EMM adoption and usage from a public health perspective. Sixty-seven articles were included in the analysis, primarily covering e-bikes and e-scooters. The determinants were categorised into two broad categories: (1) contextual determinants that encompass enabling and hindering factors related to legal frameworks, transportation systems and infrastructure, and technology, and (2) individual-level determinants that pertain to intrinsic motivations and deterrents of individuals. Our findings reveal that EMM vehicles are widely perceived as a cost-effective, flexible, ad hoc, and fast mode of transportation within urban areas, augmenting accessibility and connectivity. Additionally, the lightweight, foldable, and transportable nature of these vehicles is highly appreciated by users. However, several barriers have also been identified, including inadequate infrastructure and end-of-trip facilities, limited capability to traverse diverse terrains and trip scenarios, acquisition and maintenance costs, limited carrying capacities, technical failures, and accident risks. Our results suggest that the interplay of contextual enablers and barriers and personal motivations and deterrents drive the emergence, adoption, and usage of EMM. Hence, a comprehensive understanding of both contextual and individual-level determinants is crucial for ensuring a sustainable and healthy uptake of EMM.

Exploring built environment factors on e-bike travel behavior in urban China: A case study of Jinan

E-bike, characterized as a low-carbon and health-beneficial active travel mode, is gradually becoming popular in China. Although built environment factors are considered to be key parameters that can facilitate or hinder active transportation, such as cycling or walking, few studies have explored the impact of built environment on e-bikes. To fill this gap, this study was the first to explore the relationship between e-bike usage and built environment factors based on population level travel survey in central Jinan, China. Both macro and micro levels of built environment were measured using multi-source data. We employed ordinary least squares (OLS) and geographically weighted regression (GWR) models to explore the aggregation patterns of e-bike trips. Besides, the local Moran's I was employed to classify the aggregation patterns of e-bike trips into four types. The results from OLS model showed that eye-level greenery, building floor area, road density and public service POI were positive significantly related to e-bike trips, while open sky index and NDVI had negative association with e-bike trips. The usage of GWR model provided more subtle results, which revealed significant spatial heterogeneity on the impacts of different built environment parameters. Road density and public service POI posed positive effects on e-bike travel while NDVI and open sky index were found mainly pose negative impacts on e-bike travel. Moreover, we found similar coefficient distribution patterns of eye-level greenery, building floor area and distance to bus stop. Therefore, tailored planning interventions and policies can be developed to facilitate e-bike travel and promote individual's health level.

Systematic review and meta-analysis evaluating the effects electric bikes have on physiological parameters

BACKGROUND

There is a universal need to increase the number of adults meeting physical activity (PA) recommendations to help improve health. In recent years, electrically assisted bicycles (e-bikes) have emerged as a promising method for supporting people to initiate and maintain physical activity levels. To the best of our knowledge, there have been no meta-analyses conducted to quantify the difference in physiological responses between e-cycling with electrical assistance, e-cycling without assistance, conventional cycling, and walking.

METHODS

A systematic review and meta-analysis was conducted following PRISMA guidelines. We identified short-term e-bike studies, which utilized a crossover design comparing physiological outcomes when e-cycling with electrical assistance, e-cycling without electrical assistance, conventional cycling, or walking. Energy expenditure (EE), heart rate (HR), oxygen consumption (VO₂ ), power output (PO), and metabolic equivalents (METs) outcomes were included within the meta-analysis.

RESULTS

Fourteen studies met our inclusion criteria (N = 239). E-cycling with electrical assistance resulted in a lower energy expenditure (EE) [SMD = -0.46 (-0.98, 0.06), p = 0.08], heart rate (HR) [MD = -11.41 (-17.15, -5.68), p < 0.000, beats per minute], oxygen uptake (VO₂ ) [SMD = -0.57 (-0.96, -0.17), p = 0.005], power output (PO) [MD = -31.19 (-47.19 to -15.18), p = 0.000, Watts], and metabolic equivalent (MET) response [MD = -0.83 (-1.52, -0.14), p = 0.02, METs], compared with conventional cycling. E-cycling with moderate electrical assistance resulted in a greater HR response [MD 10.38 (-1.48, 22.23) p = 0.09, beats per minute], and VO₂ response [SMD 0.34 (-0.14, 0.82) p = 0.16] compared with walking.

CONCLUSIONS

E-cycling was associated with increased physiological responses that can confer health benefits.

Smart Electrically Assisted Bicycles as Health Monitoring Systems: A Review

This paper aims to provide a review of the electrically assisted bicycles (also known as e-bikes) used for recovery of the rider's physical and physiological information, monitoring of their health state, and adjusting the "medical" assistance accordingly. E-bikes have proven to be an excellent way to do physical activity while commuting, thus improving the user's health and reducing air pollutant emissions. Such devices can also be seen as the first step to help unhealthy sedentary people to start exercising with reduced strain. Based on this analysis, the need to have e-bikes with artificial intelligence (AI) systems that recover and processe a large amount of data is discussed in depth. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines were used to complete the relevant papers' search and selection in this systematic review.

The 2019 Conference on Health and Active Transportation: Research Needs and Opportunities

Active transportation (AT) is widely viewed as an important target for increasing participation in aerobic physical activity and improving health, while simultaneously addressing pollution and climate change through reductions in motor vehicular emissions. In recent years, progress in increasing AT has stalled in some countries and, furthermore, the coronavirus (COVID-19) pandemic has created new AT opportunities while also exposing the barriers and health inequities related to AT for some populations. This paper describes the results of the December 2019 Conference on Health and Active Transportation (CHAT) which brought together leaders from the transportation and health disciplines. Attendees charted a course for the future around three themes: Reflecting on Innovative Practices, Building Strategic Institutional Relationships, and Identifying Research Needs and Opportunities. This paper focuses on conclusions of the Research Needs and Opportunities theme. We present a conceptual model derived from the conference sessions that considers how economic and systems analysis, evaluation of emerging technologies and policies, efforts to address inclusivity, disparities and equity along with renewed attention to messaging and communication could contribute to overcoming barriers to development and use of AT infrastructure. Specific research gaps concerning these themes are presented. We further discuss the relevance of these themes considering the pandemic. Renewed efforts at research, dissemination and implementation are needed to achieve the potential health and environmental benefits of AT and to preserve positive changes associated with the pandemic while mitigating negative ones.