Associations of sleep time, quality of life, and obesity indicators on physical literacy components: a structural equation model.

AIM: To verify the association between ideal sleep time and physical literacy components while also considering multiple mediators, such as quality of life and obesity, using a sample of adolescents. METHODS: This cross-sectional study consisted of 470 adolescents aged 11-17 years from southern Brazil. Sleep time, health-related quality of life, and physical literacy components (i.e., physical education enjoyment, sports participation, sedentary behavior, moderate to vigorous physical activity, sex, and age) were evaluated through self-reported questionnaires. In addition, body mass index (BMI), and waist circumference were determined. The theoretical/statistical support of the structural equation model was evaluated according to fit parameters and strength of association. RESULTS: A direct association was observed between more sleep time and lower levels of obesity. The obesity indicators also had a negative association with HqOL, and HqOL had a positive association with physical literacy. The indirect associations indicated that the ideal sleep time was positively associated with HqOL and physical literacy components, considering the negative mediation effect of obesity. The model explains physical literacy in 31% of the variance (R = 0.31). CONCLUSION: There was an indirect association between ideal sleep duration and quality of life and between both variables with physical literacy. These relationships occur even considering the negative influence of obesity. Therefore, a child who sleeps adequately has a higher likelihood of being physically active, regardless of obesity, potentially enhancing overall quality of life across various domains.

Effects of a physical education intervention on children's physical activity and fitness: the PROFIT pilot study.

BACKGROUND: Physical education classes are widely accepted as one of the most effective settings for promoting physical activity and health and have often been used to implement physical activity interventions. The aim of this pilot study was to test a physical education intervention program on physical activity levels and physical fitness in a sample of school-age children. METHODS: Participants were a convenience sample of 50 children (34 experimental group and 16 in the comparative group) aged between 6 and 11 years old (Mean = 8.28 years). A 21-week intervention was implemented, consisting of high-intensity and physical fitness-focused exercises, in addition to a once-a-month extra class nutritional education. The following variables were evaluated before and post-intervention: physical fitness, sedentary behavior (SB), light physical activity (LPA), moderate physical activity (MVA), and vigorous physical activity (VPA). Propensity score analyses calculated the average treatment effect on the treated (ATET) within a quasi-experimental framework. RESULTS: Physical fitness variables showed improvements after the intervention, specifically for agility (ATET = -0.67 s; p < 0.001), cardiorespiratory fitness (ATET = 89.27 m; p = 0.045), lower limbs power (ATET = 4.47 centimeters; p = 0.025), and speed (ATET = -1.06 s; p < 0.001). For physical activity and SB levels, there were no improvements after intervention implementation. CONCLUSION: The intervention program showed preliminary effectiveness to improve physical fitness of children, but not SB nor physical activity.

Associations of Anxiety, Insomnia, and Physical Activity during the COVID-19 Pandemic.

PURPOSE: Anxiety, insomnia, and physical activity (PA) are interrelated, but the bi-directional relationships between these three variables are not well understood. Less is known of these relationships in settings of disrupted daily activities and acute stress. This study aimed to characterize and examine relationships between insomnia, anxiety, and PA throughout the first year of the COVID-19 pandemic, when many lifestyle behaviors were disrupted. METHODS: Participants comprised a convenience sample of 204 adults (55.4% female; 43.85 ± 15.85 years old) who completed the Generalized Anxiety Disorder Questionnaire (GAD-7), Insomnia Severity Index (ISI), and the International Physical Activity Questionnaire (IPAQ) at three time points through the first year of the COVID-19 pandemic. A cross-lagged panel model was used to evaluate these variables' concurrent, autoregressive, and cross-lagged relationships across time. Follow-up dynamic panel modeling using maximum likelihood and structural equation modeling was employed. RESULTS: Approximately 64% of participants reported their work/occupation as affected by the pandemic. At baseline, associations between anxiety and insomnia were observed (ß-coefficient: 15.87; p < 0.001). Insomnia was a positive future predictor of anxiety (ISI time point 2: 7.9 ± 5.6 points; GAD-7 at time point 3: 4.1 ± 4.2 points; ß-coefficient: 0.16; p < 0.01). No associations were observed between PA and anxiety or insomnia (all p > 0.05). CONCLUSIONS: Insomnia and anxiety were interrelated, and effects were cross-lagged. These data can inform future work focused on improving anxiety in settings of acute stress and disruptions to daily life, such as changes in occupational structure and stability. Specifically, targeting sleep parameters may be of interest to elicit downstream positive health behaviors.

A Retrospective Chart Review Suggests That Coordinated, Multidisciplinary Treatment for Patients with Anorexia Nervosa Improves Odds of Weight Restoration.

Purpose: The objective of this study was to conduct a secondary data analysis of clinical information documented in the electronic medical record to assess the clinical outcomes of patients who received three different treatment approaches on clinical outcomes for treatment of patients with anorexia nervosa (AN). Patients and methods: Historical electronic medical record (EMR) data on patients aged 6 to 80 years diagnosed with AN seen in a healthcare system between 2007 and 2017 were stratified, according to services received, into three groups: Group A (n = 48) received hospital-based services; Group B (n = 290) saw one or two provider types; Group C (n = 26) received outpatient coordinated multidisciplinary care from three provider types. Clinical outcomes [body mass index for adults (BMI), body mass index percentile (BMI%ile) for pediatric patients] defined AN severity and weight restoration. EMR data were analyzed using a generalized mixed-effects model and a Markov Transition model to examine the odds of weight restoration and the change in odds of weight restoration across the number of provider visits, respectively. Results: Patients receiving coordinated multidisciplinary care had significantly higher odds of weight restoration compared with patients receiving hospital-based services only (OR = 3.76, 95% CI [1.04, 13.54], p = 0.042). In addition, patients receiving care from 1 to 2 providers (OR = 1.006, 95% CI [1.003, 1.010], p = 0.001) or receiving coordinated multidisciplinary care (OR = 1.005, 95% CI [1.001, 1.011], p = 0.021) had significantly higher odds of weight restoration per provider visit day compared with patients receiving hospital-based services only. Conclusion: This retrospective chart review supports the coordinated, multidisciplinary care model for the weight restoration in patients with AN in an outpatient setting.

A regionally tailored epidemiological forecast and monitoring program to guide a healthcare system in the COVID-19 pandemic.

BACKGROUND: During the COVID-19 pandemic, analytics and predictive models built on regional data provided timely, accurate monitoring of epidemiological behavior, informing critical planning and decision-making for health system leaders. At Atrium Health, a large, integrated healthcare system in the southeastern United States, a team of statisticians and physicians created a comprehensive forecast and monitoring program that leveraged an array of statistical methods. METHODS: The program utilized the following methodological approaches: (i) exploratory graphics, including time plots of epidemiological metrics with smoothers; (ii) infection prevalence forecasting using a Bayesian epidemiological model with time-varying infection rate; (iii) doubling and halving times computed using changepoints in local linear trend; (iv) death monitoring using combination forecasting with an ensemble of models; (v) effective reproduction number estimation with a Bayesian approach; (vi) COVID-19 patients hospital census monitored via time series models; and (vii) quantified forecast performance. RESULTS: A consolidated forecast and monitoring report was produced weekly and proved to be an effective, vital source of information and guidance as the healthcare system navigated the inherent uncertainty of the pandemic. Forecasts provided accurate and precise information that informed critical decisions on resource planning, bed capacity and staffing management, and infection prevention strategies. CONCLUSIONS: In this paper, we have presented the framework used in our epidemiological forecast and monitoring program at Atrium Health, as well as provided recommendations for implementation by other healthcare systems and institutions to facilitate use in future pandemics.

Radical surgical resection with molecular margins is associated with improved survival in IDH wildtype GBM.

BACKGROUND: Survival is variable in patients with glioblastoma IDH wild-type (GBM), even after comparable surgical resection of radiographically-detectable disease, highlighting the limitations of radiographic assessment of infiltrative tumor anatomy. The majority of post-surgical progressive events are failures within 2cm of the resection margin, motivating supramaximal resection strategies to improve local control. However, which patients benefit from such radical resections remains unknown. METHODS: We developed a predictive model to identify which IDH wild-type GBM are amenable to radiographic gross total resection (GTR). We then investigated whether GBM survival heterogeneity following GTR is correlated with microscopic tumor burden a by analyzing tumor cell content at the surgical margin with a rapid qPCR-based method for detection of TERT promoter mutation. RESULTS: Our predictive model for achievable GTR, developed on retrospective radiographic and molecular data of GBM patients undergoing resection, had an AUC of 0.83, sensitivity of 62%, and specificity of 90%. Prospective analysis of this model in 44 patients found 89% of patients were correctly predicted to achieve a RV<4.9cc. Of the 44 prospective patients undergoing rapid qPCR TERT promoter mutation analysis at the surgical margin, 7 had undetectable TERT mutation, of which 5 also had a gross total resection (RV<1cc). In these 5 patients at 30 months follow up, 75% showed no progression, compared to 0% in the group with TERT mutations detected at the surgical margin (p=0.02). CONCLUSIONS: These findings identify a subset of patients with GBM that may derive local control benefit from radical resection to undetectable molecular margins.