TikTok, the most popular social media, brings various benefits to nowadays living. However, the problematic use of TikTok has also elicited a range of health problems, such as sleep problems. Physical activity (PA) appears to play a protective role in the problematic use of TikTok and its health consequences, but the pathways between PA and sleep health are understudied. Therefore, we aimed to propose a framework to check whether PA can benefit the sleep health of TikTok users by reducing bedtime delays for TikTok. Stress and mental health issues were also considered as they are potential mediators between PA and sleep health and may also influence the problematic use of smartphones. A cross-sectional investigation that involved 660 Chinese TikTok users was conducted in April 2021. The volume of PA, perceived stress (PSS-10), depression (PHQ-9), anxiety (GAD-7), bedtime delay for TikTok use, and sleep quality (PSQI) were investigated through an online questionnaire survey. Structural equation modeling was employed to examine pathways from PA to sleep quality through stress, mental health issues (depression and anxiety), and bedtime delay for TikTok. We found that PA exerted a significant effect on sleep quality through indirect pathways (β = −0.056, p = 0.001). Stress was a critical mediator of all indirect pathways, and the pathway mediated by stress and mental health issues made a major contribution to the total effect (β = −0.048, p = 0.002). The identified pathways mediated by bedtime delay for TikTok were relatively weak but significant. PA showed a distinct effect on bedtime delay for TikTok through stress and mental health issues (β = −0.043, p = 0.001). In conclusion, our framework highlights some pathways to understanding the benefits of PA on TikTok users’ sleep quality. Future research is warranted to explore extra indirect pathways and re-examine the causal relationships between variables.

Velocity-based training (VBT) is a rising auto-regulation method that dynamically regulates training loads to promote resistance training. However, the role of VBT in improving various athletic performances is still unclear. Hence, the presented study aimed to examine the role of VBT in improving lower limbs’ maximum strength, strength endurance, jump, and sprint performance among trained individuals. A systematic literature search was performed to identify studies on VBT for lower limb strength training via databases, including PubMed, Web of Science, Embase, EBSCO, Cochrane, CNKI (in Chinese), and Wanfang Database (in Chinese). Controlled trials that deployed VBT only without extra training content were considered. Eventually, nine studies with a total of 253 trained males (at least one year of training experience) were included in the meta-analysis. The pooled results suggest that VBT may effectively enhance lower limbs’ maximum strength (SMD = 0.76; p < 0.001; I2 = 0%), strength endurance (SMD = 1.19; p < 0.001; I2 = 2%), countermovement jump (SMD = 0.53; p < 0.001; I2 = 0%), and sprint ability (SMD of sprint time = −0.40; p < 0.001; I2 = 0%). These findings indicate the positive role of VBT in serving athletic training. Future research is warranted to focus on the effect of velocity loss of VBT on athletic performance.

People with high levels of intelligence are more aware of risk factors, therefore choosing a healthier lifestyle. This assumption seems reasonable, but is it true? Previous studies appear to agree and disagree. To cope with the uncertainty, we designed a mendelian randomization (MR) study to examine the causal effects of genetically proxied intelligence on alcohol-, smoking-, and physical activity (PA)-related behaviors. We obtained genome-wide association study (GWAS) datasets concerning these variables from separate studies or biobanks and used inverse-variance weighted (IVW) or MR-Egger estimator to evaluate the causal effects according to an MR protocol. The MR-Egger intercept test, MR-PRESSO, and funnel plots were employed for horizontal pleiotropy diagnosis. The Steiger test (with reliability test), Cochran’s Q test, MR-PRESSO, and leave-one-out method were employed for sensitivity analysis. We found significant or potential effects of intelligence on alcohol dependence (OR = 0.749, p = 0.003), mental and behavioral disorders due to alcohol (OR = 0.814, p = 0.009), smoking (OR = 0.585, p = 0.005), and smoking cessation (OR = 1.334, p = 0.001). Meanwhile, we found significant or potential effects on walking duration (B = −0.066, p < 0.001), walking frequency (B = −0.055, p = 0.031), moderate PA frequency (B = −0.131, p < 0.001), and vigorous PA frequency (B = −0.070, p = 0.001), but all in a negative direction. In conclusion, our findings reinforce some existing knowledge, indicate the complexity of the health impacts of human intelligence, and underline the value of smoking and alcohol prevention in less intelligent populations. Given the existing limitations in this study, particularly the potential reverse causality in some estimations, re-examinations are warranted in future research.

The protection of physical activity (PA) against COVID-19 is a rising research interest. However, the role of physical activity intensity on this topic is yet unclear. To bridge the gap, we performed a Mendelian randomization (MR) study to verify the causal influence of light and moderate-to-vigorous PA on COVID-19 susceptibility, hospitalization, and severity. The Genome-Wide Association Study (GWAS) dataset of PA (n = 88,411) was obtained from the UK biobank and the datasets of COVID-19 susceptibility (n = 1,683,768), hospitalization (n = 1,887,658), and severity (n = 1,161,073) were extracted from the COVID-19 Host Genetics Initiative. A random-effect inverse variance weighted (IVW) model was carried out to estimate the potential causal effects. A Bonferroni correction was used for counteracting. The problem of multiple comparisons. MR-Egger test, MR-PRESSO test, Cochran’s Q statistic, and Leave-One-Out (LOO) were used as sensitive analysis tools. Eventually, we found that light PA significantly reduced the risk of COVID-19 infection (OR = 0.644, 95% CI: 0.480–0.864, p = 0.003). Suggestive evidence indicated that light PA reduced the risks of COVID-19 hospitalization (OR = 0.446, 95% CI: 0.227 to 0.879, p = 0.020) and severe complications (OR = 0.406, 95% CI: 0.167–0.446, p = 0.046). By comparison, the effects of moderate-to-vigorous PA on the three COVID-19 outcomes were all non-significant. Generally, our findings may offer evidence for prescribing personalized prevention and treatment programs. Limited by the available datasets and the quality of evidence, further research is warranted to re-examine the effects of light PA on COVID-19 when new GWAS datasets emerge.

Bedtime smartphone use is an emerging issue that threatens the sleep health of children and young adults. Physical activity can have numerous health benefits, including reducing problematic or addictive behavior. However, the role of daily physical activity in reducing bedtime smartphone use is understudied. Hence, we conducted a one-day cross-sectional on the weekend (21–22 May 2021) to investigate the associations between daytime physical activity, bedtime smartphone use, and sleep quality. A total of 828 college students were recruited in two colleges. Their daytime physical activity indices were captured, including self-reported physical activity duration, intensity, volume, and smartphone-monitored walking steps. The participants reported whether they used smartphone while lying in bed (before sleep) and whether they delayed sleep due to smartphone use. Their while-in-bed screen time (duration) and subsequent sleep quality were also measured with self-report and a numeric rating scale, respectively. The results suggested that daytime physical activity duration was associated with lower chances of while-in-bed smartphone use (OR = 0.907, p = 0.019) and smartphone-related sleep delay (OR = 0.932, p = 0.014). However, no significant association was found between physical activity indices and while-in-bed screen time or sleep quality. These findings may contribute to understanding the reciprocal relationship between physical activity and smartphone use and highlighting the potential of controlling problematic bedtime smartphone use through daily physical activity. Future research is warranted to examine the associations with extra objective measures.