ObjectiveThe purpose of this study was to evaluate the effects of high-intensity interval training (HIIT) and moderate-intensity continuous training (MICT) on cardiovascular disease (CVD) risk factors in adults with overweight and obesity.MethodsTwenty-two articles were included by searching six databases, the total number of subjects was 620 in these articles. Outcomes were synthesised using a random-effects meta-analysis of the Standardized mean difference (SMD) in CVD risk factors.ResultsHIIT and MICT resulted in statistically significant reductions in Weight, BMI, fat%, total cholesterol(TC), and improvement in VO2max. Compared with MICT, subgroup of durations of HIIT training interval ≥2 min can significantly increase VO2max (SMD = 0.444, 95% CI:0.037~0.851,P = 0.032), subgroup of energy expenditure of HIIT equal to MICT can significantly increase VO2max (SMD = 0.399, 95% CI:0.106~0.692,P = 0.008).ConclusionsHIIT appears to provide similar benefits to MICT for improving body composition, VO2maxand TC, but HIIT spent less time than MICT by 9.7 min on one session. HIIT is superior to MICT in improving cardiopulmonary fitness when durations of HIIT training interval ≥2 min or energy expenditure of HIIT same as MICT. PROSPERO ID: CRD42016045835.

Background Exercise modes can be divided into open skill exercise (OSE) and closed skill exercise (CSE). While research has shown that these two exercise modes may have different effects on cognitive function, this possibility has not been systematically reviewed. Objective The purpose of the present review was to objectively evaluate the research literature regarding the effects of OSE versus CSE on cognitive function. Methods Six electronic databases (Web of Science, EMBASE, Google Scholar, PubMed, PsycINFO, and SPORTDiscus) were searched from inception dates to December 2018 for studies examining the associations of OSE and CSE with cognitive function. The literature searches were conducted using the combinations of two groups of relevant search items related to exercise modes (i.e., OSE and CSE) and cognitive function. Articles were limited to human studies in all age groups. Both intervention and observational studies with full text published in English-language peer-reviewed journals were considered eligible. The search process, study selection, data extraction, and study quality assessment were carried out independently by two researchers. Results A total of 1,573 articles were identified. Fourteen observational and five intervention studies met the inclusion criteria. Twelve of the 14 observational studies found that OSE benefits cognitive function, and seven of these 14 observational studies supported superior effects of OSE compared with CSE for enhancing cognitive function. Three of the five intervention studies found that OSE (versus CSE) led to greater improvements in cognitive function in both children and older adults. Conclusion Although the majority of studies in this review were observational cross-sectional designs, the review tends to support that OSE is more effective for improving some aspects of cognitive function compared with CSE. More rigorous randomized control trials with long-term follow-ups are needed in order to confirm these differential cognitive effects of the two exercise modes.

Enhancing cardiorespiratory fitness (CRF) can lead to substantial health benefits. Comparisons between high-intensity interval training (HIIT) and moderate-intensity continuous training (MICT) on CRF for children and adolescents are inconsistent and inconclusive. The objective of this study was to perform a meta-analysis to compare the effects between HIIT and MICT on CRF in children and adolescents. We searched MEDLINE, PubMed, Web of Science, and Google Scholar to identify relevant articles. The standardized mean differences (SMD) and 95% confidence intervals (95% CI) were calculated to determine the pooled effect size of HIIT and MICT on CRF. A total of 563 subjects from 17 studies (18 effects) were identified. The pooled effect size was 0.51 (95% CI = 0.33–0.69) comparing HIIT to MICT. Moreover, intervention duration, exercise modality, work and rest ratio, and total bouts did not significantly modify the effect of HIIT on CRF. It is concluded that compared with endurance training, HIIT has greater improvements on cardiorespiratory fitness among children and adolescents.

Background About 70% of children and adolescents worldwide do not meet the recommended level of physical activity (PA), which is closely associated with physical, psychological, and cognitive well-being. Nowadays, the use of technologies to change PA is of interest due to the need for novel, more effective intervention approaches. The previous meta-analyses have examined smartphone-based interventions and their impact on PA in adults, but evidence in children and adolescents still needs further research. Objective This systematic review and meta-analysis aimed to determine the effectiveness of smartphone-based interventions for improving PA in children and adolescents. Methods Five electronic databases (PubMed, Web of Science, OVID, Scopus, and the China National Knowledge Infrastructure) were searched up to June 29, 2020. Randomized controlled trials with a control group that examine the effect of smartphone interventions on PA among children and adolescents were included. Bias risks were assessed using the Cochrane collaboration tool. Meta-analysis was performed to assess the pooled effect on PA using a random effects model. Subgroup analyses were conducted to examine the potential modifying effects of different factors (eg, types of intervention, intervention duration, age, measurement, study quality). Results A total of 9 studies were included in this review, including 4 mobile app interventions, 3 SMS text messaging interventions, and 2 app + SMS text messaging interventions. In general, the risk of bias of included studies was low. Compared with the control group, the use of smartphone intervention significantly improved PA (standardized mean difference [SMD] 0.44, 95% CI 0.11-0.77, P=.009), especially for total PA (TPA; weighted mean difference [WMD] 32.35, 95% CI 10.36-54.33, P=.004) and daily steps (WMD 1185, 95% CI 303-2068, P=.008), but not for moderate-to-vigorous PA (WMD 3.91, 95% CI –1.99 to 9.81, P=.19). High statistical heterogeneity was detected (I2=73.9%, P<.001) for PA. Meta-regression showed that duration (β=–.08, 95% CI –0.15 to –0.01, n=16) was a potential factor for high heterogeneity. The results of subgroup analyses indicated that app intervention (SMD 0.76, 95% CI 0.23-1.30, P=.005), children (SMD 0.64, 95% CI 0.10-1.18, P=.02), “≤8 weeks” (SMD 0.76, 95% CI 0.23-1.30, P=.005), objective measurement (SMD 0.50, 95% CI 0.09-0.91, P=.02), and low risk of bias (SMD 0.96, 95% CI 0.38-1.54, P=.001) can significantly improve PA. Conclusions The evidence of meta-analysis shows that smartphone-based intervention may be a promising strategy to increase TPA and steps in children and adolescents. Currently, app intervention may be a more effective strategy among smartphone intervention technologies. To extend the promise of smartphone intervention, the future needs to design comparative trials among different smartphone technologies. Trial Registration PROSPERO CRD42019148261; https://tinyurl.com/y5modsrd

Background: Data on the longitudinal association of walking pace with the risk of cognitive decline and dementia are inconsistent and inconclusive. Therefore, researchers conducted a meta-analysis of prospective cohort studies to quantitatively assess the association of walking pace with the risk of cognitive decline and dementia among elderly populations. Methods: Eligible studies were searched in PubMed and EMBASE through April 22, 2016. Additional information was retrieved through Google Scholar or hand review of the reference lists from the relevant studies. Prospective cohort studies were included if they reported relative risk (RR) and the corresponding 95% confidence interval (CI) of cognitive decline or dementia in relation to walking pace. Results: Seventeen studies were identified, including 10 studies reporting the RR of cognitive decline (9,949 participants and 2,547 events) and 10 presenting the RR of dementia (14,140 participants and 1,903 events). Comparing the lowest to the highest category of walking pace, the pooled RR was 1.89 (95% CI = 1.54-2.31) for cognitive decline and 1.66 (95% CI = 1.43-1.92) for dementia. With every 1 dm/s (360 m/h) decrement in walking pace, the risk of dementia was increased by 13% (RR = 1.13; 95% CI = 1.08-1.18). Conclusions: This meta-analysis provides accumulated evidence supporting that slow or decreased walking pace is significantly associated with elevated risk of cognitive decline and dementia in elderly populations.