(1) Background: The novel coronavirus disease 2019 (COVID-19) is a global public health emergency that has caused worldwide concern. Vast resources have been allocated to control the pandemic and treat patients. However, little attention has been paid to the adverse impact on mental health or effective mitigation strategies to improve mental health. (2) Purpose: The aim of this study was to assess the adverse impact of the COVID-19 outbreak on Chinese college students’ mental health, understand the underlying mechanisms, and explore feasible mitigation strategies. (3) Methods: During the peak time of the COVID-19 outbreak in China, we conducted longitudinal surveys of sixty-six college students. Structured questionnaires collected information on demographics, physical activity, negative emotions, sleep quality, and aggressiveness level. A mixed-effect model was used to evaluate associations between variables, and the mediating effect of sleep quality was further explored. A generalized additive model was used to determine the dose-response relationships between the COVID-19 death count, physical activity, and negative emotions. (4) Results: The COVID-19 death count showed a direct negative impact on general sleep quality (β = 1.37, 95% confidence interval [95% CI]: 0.55, 2.19) and reduced aggressiveness (β = −6.57, 95% CI: −12.78, −0.36). In contrast, the COVID-19 death count imposed not a direct but an indirect impact on general negative emotions (indirect effect (IE) = 0.81, p = 0.012), stress (IE = 0.40, p < 0.001), and anxiety (IE = 0.27, p = 0.004) with sleep quality as a mediator. Moreover, physical activity directly alleviated general negative emotions (β = −0.12, 95% CI: −0.22, −0.01), and the maximal mitigation effect occurred when weekly physical activity was about 2500 METs. (5) Conclusions: (a) The severity of the COVID-19 outbreak has an indirect effect on negative emotions by affecting sleep quality. (b) A possible mitigation strategy for improving mental health includes taking suitable amounts of daily physical activity and sleeping well. (c) The COVID-19 outbreak has reduced people’s aggressiveness, probably by making people realize the fragility and preciousness of life.

Background: Two related lifestyle behaviors associated with sleep disturbance are sedentary behavior and physical exercise participation. We aimed to use a population-based study to disentangle the relationships between sedentary behavior, exercise, and sleep disturbance based on blood-cell-based inflammatory biomarkers.Methods: A total of 22,599 participants from the National Health and Nutrition Examination Survey (NHANES) were included in the analyses. Sleep disturbance was assessed according to the NHANES questionnaire. Exercise participation ansd sedentary behavior were evaluated by the global physical activity questionnaire. The inflammatory biomarkers in the examination were white blood cell (WBC) count, neutrophil count (NEU), neutrophil-to-lymphocyte ratio (NLR), and systemic immune inflammation index (SII). A complex multistage sampling design and weighted multivariable logistic regression were applied for further analysis. Mediation models were constructed to figure out the mediating role of inflammatory biomarkers.Results: The weighted prevalence of sleep disturbance was 24.17%. Sedentary behavior and exercise were associated with sleep disturbance after full adjustment [for sedentary behavior, OR (95% CI): 1.261 (1.154, 1.377); for exercise, OR (95% CI): 0.849 (0.757, 0.953)]. In severe sedentary behavior groups, the mitigation effect of exercise on sleep disturbance was observed [OR (95% CI): 0.687 (0.551, 0.857)]. For the mechanism, strong associations were detected between inflammatory biomarkers and sleep disturbance. Mediation analysis showed that WBC, NEU, NLR, and SII mediated the statistical association between sedentary behavior and sleep disturbance with proportions (%) of 2.09, 2.27, 1.76, and 0.82, respectively.Conclusions: Our data suggested that sedentary behavior was a risk factor for sleep disturbance. Blood-cell-based inflammatory biomarkers were an easily accessible and cost-effective strategy for identifying sleep disturbance and also significantly mediated the association between sedentary behavior and sleep disturbance. Exercise was proved to be effective in severe sedentary behavior groups to improve sleep disturbance symptoms, while the internal mechanism needed further exploration.

Background: High-intensity interval training (HIIT) is an emerging exercise strategy and is considered to be a recipe for health promotion. This study aimed to systematically identify collaboration networks, track research trends, highlight current hotspots, and predict future frontiers in HIIT and its applications in health promotion since the start of the new century.Methods: Relevant original publications were obtained from the Science Citation Index Expanded of the Web of Science Core Collection (WoSCC) database between 2001 and 2020. CiteSpace and VOSviewer software were used to perform bibliometric visualization and comparative analysis of involved indexes that included countries, institutions, journals, authors, references, and keywords.Results: A total of 572 papers were included, and the trend of annual publications showed a remarkable growth. The United States and the University of Exeter were the most productive country and institutions, respectively, with 107 and 18 publications, respectively. European Journal of Applied Physiology took the lead in the number of published articles, and Medicine and Science in Sports and Exercise ranked first in the cocitation counts. Barker AR and Gibala MJ were considered as the most productive and the most highly-cited authors.Conclusions: “Health risks,” “adolescent,” and “aging” are the three noteworthy topics during the evolution of HIIT-health promotion (HIIT-HP) research. The current research hotspots of HIIT and its practices in the health promotion domain lies in “metabolic diseases,” “cardiovascular diseases,” “neurological diseases,” and “musculoskeletal diseases.” The authors summarize that “prevention and rehabilitation,” “micro and molecular level,” and “cognition and mental health” are becoming frontiers and focus on the health topics related to HIIT in the upcoming years, which are worthy of further exploration.

Background: The equilibrium between gut microbiota (GM) and the host plays a pivotal role in maintaining overall health, influencing various physiological and metabolic functions. Emerging research suggests that exercise modulates the abundance and functionality of gut bacteria, yet the comprehensive effects on GM diversity remain to be synthesized. Objectives and Design: The study aims to quantitatively examine the effect of exercise on the diversity of gut microbiota of adults using a systemic review and meta-analysis approach. Methods: PubMed, Ebsco, Embase, Web of Science, Cochrane Central Register of Controlled Trials, the China National Knowledge Infrastructure, and Wanfang Data were searched from their inception to September 2023. Exercise intervention studies with a control group that describe and compare the composition of GM in adults, using 16S rRNA gene sequencing, were included in this meta-analysis. Results: A total of 25 studies were included in this meta-analysis with a total of 1044 participants. Based on a fixed-effects model [Chi² = 29.40, df = 20 (p = 0.08); I² = 32%], the pooled analysis showed that compared with the control group, exercise intervention can significantly increase the alpha diversity of adult GM, using the Shannon index as an example [WMD = 0.05, 95% CI (0.00, 0.09); Z = 1.99 (p = 0.05)]. In addition, exercise interventions were found to significantly alter GM, notably decreasing Bacteroidetes and increasing Firmicutes, indicating a shift in the Firmicutes/Bacteroidetes ratio. The subgroup analysis indicates that females and older adults appear to exhibit more significant changes in the Shannon Index and observed OTUs. Conclusions: Exercise may be a promising way to improve GM in adults. In particular, the Shannon index was significantly increased after exercise. Distinct responses in GM diversity to exercise interventions based on gender and age implicated that more research was needed.

Sleep is a modifiable behavior that can be targeted in interventions aimed at promoting healthy aging. This study aims to (i) identify the sleep duration trend in US adults; (ii) investigate the relationship between sleep duration and phenotypic age; and (iii) explore the role of exercise in this relationship. Phenotypic age as a novel index was calculated according to biomarkers collected from US adults based on the National Health and Nutrition Examination Survey (NHANES). Sleep information was self-reported by participants and discerned through individual interviews. The principal analytical method employed was weighted multivariable linear regression modeling, which accommodated for the complex multi-stage sampling design. The potential non-linear relationship was explored using a restricted cubic spline (RCS) model. Furthermore, subgroup analyses evaluated the potential effects of sociodemographic and lifestyle factors on the primary study outcomes. A total of 13,569 participants were finally included in, thereby resulting in a weighted population of 78,880,615. An examination of the temporal trends in sleep duration revealed a declining proportion of individuals with insufficient and markedly deficient sleep time since the 2015–2016 cycle. Taken normal sleep group as a reference, participants with extreme short sleep [β (95% CI) 0.582 (0.018, 1.146), p = 0.044] and long sleep [β (95% CI) 0.694 (0.186, 1.203), p = 0.010] were both positively associated with phenotypic age using the fully adjusted model. According to the dose–response relationship between sleep duration and phenotypic age, long sleep duration can benefit from regular exercise activity, whereas short sleep duration with more exercise tended to have higher phenotypic age. There is an inverted U-shaped relationship between short and long sleep durations and phenotypic age. This study represents an important step forward in our understanding of the complex relationship between sleep and healthy aging. By shedding light on this topic and providing practical exercise recommendations for promoting healthy sleep habits, researchers can help individuals live longer, healthier, and more fulfilling lives.

Aims: The molecular mechanism of short‐sleep conditions on cognition remains largely unknown. This research aimed to investigate associations between short sleep, inflammatory biomarkers and cognitive function in the US population (NHANES data 2011–2014) and explore cellular mechanisms in mice.Methods: Systemic immune‐inflammation index (SII) was calculated using blood‐cell based biomarkers. Further, we employed integrated bioinformatics and single‐cell transcriptomics (GSE137665) to examine how short sleep exposure influenced the molecular pathways associated with inflammation in the brain. To explore the signaling pathways and biological processes of sleep deprivation, we carried out enrichment analyses utilizing the GO and KEGG databases.Results: Population results showed that, compared with normal sleep group, severe short sleep was associated with lower cognitive ability in all the four tests. Moreover, a higher SII level was correlated with lower scores of cognitive tests. In mice study, elevated activation of the inflammatory pathway was observed in cell subgroups of neurons within the sleep deprivation and recovery sleep cohorts. Additionally, heightened expression of oxidative stress and integrated stress response pathways was noted in GABAergic neurons during sleep deprivation.Conclusion: This study contributed to the understanding of the influence of short sleep on cognitive function and its cellular mechanisms.