Riiser Amund, Bere Elling, Andersen Lars Bo, Nordengen Solveig
Department of Sport, Food and Natural Sciences, Faculty of Education, Arts and Sports, Western Norway University of Applied Sciences, Sogndal, Norway.
Department of Sport Science and Physical Education, University of Agder, Kristiansand, Norway.
Front Sports Act Living. 2022 Oct 19;4:1031004. doi: 10.3389/fspor.2022.1031004. eCollection 2022.
The objective of the present study is to review and meta-analyze the effect of E-cycling on health outcomes. We included longitudinal experimental and cohort studies investigating the effect of E-cycling on health outcomes. The studies were identified from the seven electronic databases: Web of Science, Scopus, Medline, Embase, PsycINFO, Cinahl and SportDiscus and risk of bias was assessed with the revised Cochrane Collaboration Risk of Bias Tool (RoB2). We performed meta-analysis with random effects models on outcomes presented in more than one study. Our study includes one randomized controlled trial, five quasi experimental trials and two longitudinal cohort studies. The trials included 214 subjects of whom 77 were included in control groups, and the cohort studies included 10,222 respondents at baseline. Maximal oxygen consumption and maximal power output were assessed in four and tree trials including 78 and 57 subjects, respectively. E-cycling increased maximal oxygen consumption and maximal power output with 0.48 SMD (95%CI 0.16-0.80) and 0.62 SMD (95%CI 0.24-0.99). One trial reported a decrease in 2-h post plasma glucoses from 5.53 ± 1.18 to 5.03 ± 0.91 mmol L and one cohort study reported that obese respondents performed 0.21 times more trips on E-bike than respondents with normal weight. All the included studies had a high risk of bias due to flaws in randomization. However, the outcomes investigated in most studies showed that E-cycling can improve health.
本研究的目的是回顾和荟萃分析电子骑行对健康结果的影响。我们纳入了调查电子骑行对健康结果影响的纵向实验和队列研究。这些研究是从七个电子数据库中识别出来的:科学网、Scopus、Medline、Embase、PsycINFO、Cinahl和SportDiscus,并使用修订后的Cochrane协作偏倚风险工具(RoB2)评估偏倚风险。对于在不止一项研究中呈现的结果,我们采用随机效应模型进行荟萃分析。我们的研究包括一项随机对照试验、五项准实验试验和两项纵向队列研究。这些试验包括214名受试者,其中77名被纳入对照组,队列研究在基线时包括10222名受访者。在四项试验中评估了最大摄氧量,其中包括78名受试者,在三项试验中评估了最大功率输出,其中包括57名受试者。电子骑行使最大摄氧量和最大功率输出分别增加了0.48标准化均数差(95%可信区间0.16 - 0.80)和0.62标准化均数差(95%可信区间0.24 - 0.99)。一项试验报告2小时后血浆葡萄糖从5.53±1.18毫摩尔/升降至5.03±0.91毫摩尔/升,一项队列研究报告肥胖受访者骑电动自行车出行的次数比体重正常的受访者多0.21倍。由于随机化存在缺陷,所有纳入的研究都有很高 的偏倚风险。然而,大多数研究调查的结果表明,电子骑行可以改善健康。