COVID-19 hotspot detection in a university setting.

The onset of the COVID-19 pandemic commenced an era of widespread disruptions in the academic world, including shut downs, periodic shifts to online learning, and disengagement from students. In an effort to transition back to in-person learning, many universities and schools tried to implement policy that balanced student learning with community health. While academic administrators have little control over some aspects of COVID-19 spread, they often choose to use temporary shutdowns of in-person teaching based on perceived hotspots of COVID-19. Specifically, if administrators have substantial evidence of within-group transmission for a class or other academic unit (a "hotspot"), the activities of that class or division of the university might be temporarily moved online. In this article, we describe an approach used to make these types of decisions. Using demographic information and weekly COVID-19 testing outcomes for university students, we use an XGBoost model that produces an estimated probability of testing positive for each student. We discuss variables engineered from the demographic information that increased model fit. As part of our approach, we simulate semesters under the null hypothesis of no in-class transmission, and compare the distribution of simulated outcomes to the observed group positivity rates to find an initial p-value for each group (e.g., section, housing area, or major). Using a simulation-based modification of a standard false discovery rate procedure, we identify possible hot spots-classes or groups whose COVID-19 rates exceed the levels expected for the demographic mix of students in each group of interest. We use simulation experiments and an anonymized example from Fall 2020 to illustrate the performance of our approach. While our example is based on hotspot detection in a university setting, the approach can be used for monitoring the spread of infectious disease within any interconnected organization or population.

State Legislation Related to School Nutrition: Predictors of Bill Passage From 2010-2019.

OBJECTIVE: This study aimed to discover the prevalence of school nutrition state legislation and to identify the correlates of enactment. DESIGN, SETTING, AND PARTICIPANTS: An online legislative database, Legiscan, was used to collect bills related to school nutrition from the US from 2010 to 2019. Bills were coded and compiled into a study database with state-level dietary variables (obesity prevalence, fruit, and vegetable intake, sugar-sweetened beverage consumption), community variables (percent White, poverty), and bill-characteristic variables (party affiliation in legislature, strength of language, party of governor, school gardens, vegetable intake, and other salient variables). Multivariable models were built to examine predictors of bill enactment. RESULTS: Of the 462 bills introduced, 38.7% (n = 156) were enacted. In a multivariable model, the strength of bill language, political party affiliation, implementation of school gardens, and vegetable intake were the variables associated with bill passage. Bills with strong language were less likely to be enacted (P <0.001). Bills introduced by Democrats were more likely to be enacted (P = 0.01). CONCLUSION AND IMPLICATION: This study showed a better understanding of legislative support for child nutrition via policy surveillance of bills and their correlates of enactment. This information can be used to prioritize advocacy efforts and identify ways research can better inform policy.

The Effects of Potato Presentation on Vegetable Intake in School-Aged Children: A Cross-Over Study.

Vegetables are an essential component of a healthy dietary pattern in children; however, their consumption is often insufficient due to lack of preference. To address this, the influence of combining vegetables (mixed peas and carrots-MPACs) with potatoes, a generally liked food, on overall vegetable consumption among children aged 7-13 years was explored. The research involved a cross-over study design with 65 participants who completed five lunchtime meal conditions, each with different combinations of MPACs and potatoes versus a control (MPACs with a wheat roll). The meals were provided in a cafeteria setting, and plate waste was used to measure vegetable consumption. Anthropometric data and other variables were also measured. Notably, self-reported hunger did not significantly differ between conditions. Meal condition was a significant predictor of MPACs (F = 5.20; p = 0.0005), with MPAC consumption highest when combined with shaped potato faces in the same bowl (+8.77 g compared to serving MPACs and shaped potato faces in separate bowls) and lowest when combined with diced potatoes in the same bowl (-2.85 g compared to serving MPACs and diced potatoes in separate bowls). The overall model for MPAC consumption was influenced by age, height z-score, body fat percentage z-score, and condition (likelihood ratio = 49.1; p < 0.0001). Age had the strongest correlation with vegetable consumption (r = 0.38), followed by male gender, height z-score (r = 0.30), and body fat z-score (r = -0.15). The results highlight the positive impact of combining potatoes with vegetables in school meals, particularly when using shaped potato faces. These findings emphasize the potential of potatoes as a valuable vegetable option in promoting healthier eating habits among children. Additionally, future research could explore the impact of different potato combinations and investigate other factors influencing meal consumption in school settings.

Distributional Validation of Precipitation Data Products with Spatially Varying Mixture Models.

The high mountain regions of Asia contain more glacial ice than anywhere on the planet outside of the polar regions. Because of the large population living in the Indus watershed region who are reliant on melt from these glaciers for fresh water, understanding the factors that affect glacial melt along with the impacts of climate change on the region is important for managing these natural resources. While there are multiple climate data products (e.g., reanalysis and global climate models) available to study the impact of climate change on this region, each product will have a different amount of skill in projecting a given climate variable, such as precipitation. In this research, we develop a spatially varying mixture model to compare the distribution of precipitation in the High Mountain Asia region as produced by climate models with the corresponding distribution from in situ observations from the Asian Precipitation-Highly Resolved Observational Data Integration Towards Evaluation (APHRODITE) data product. Parameter estimation is carried out via a computationally efficient Markov chain Monte Carlo algorithm. Each of the estimated climate distributions from each climate data product is then validated against APHRODITE using a spatially varying Kullback-Leibler divergence measure. Supplementary materials accompanying this paper appear online. Supplementary materials for this article are available at 10.1007/s13253-022-00515-0.

Body shape perception in men and women without obesity during caloric restriction: a secondary analysis from the CALERIE study.

OBJECTIVE: To examine body shape perception in 218 adults without obesity or history of eating disorders during caloric restriction (CR). METHODS: Comprehensive Assessment of Long-term Effects of Reducing Intake of Energy (CALERIE) is a 2-year, randomized clinical trial using a 2:1 assignment (CR, 25% reduction in calories; Control, typical diet). For this secondary analysis, we examined perceived body shape using the Body Shape Questionnaire (BSQ). Analyses of BSQ scores are reported by group, over time, by sex, and by BMI. Data for body fat percentage, symptoms of depression, food cravings, maximal oxygen consumption, and stress were analyzed for their association with BSQ scores. RESULTS: Compared to control, CR reduced BSQ scores. Women tended to have greater concern with body shape than men across all measurement times. There was no difference in change in BSQ scores at 12 or 24 months between those with a BMI < 25 kg/m2 or ≥ 25 kg/m2. Change in body fat percentage was most correlated with change in BSQ score from 0 to 12 (r = 0.39) and 0-24 months (r = 0.38). For change in BSQ score, Akaike/ Bayesian information criterion (AIC/BIC) found that the model of best fit included the following three change predictors: change in body fat percentage, depression symptoms, and food cravings. For 0-12 months, AIC/BIC = 1482.0/1505.6 and for 0-24 months AIC/BIC = 1364.8/1386.5. CONCLUSIONS: CR is associated with reduced concern for body shape in men and women without obesity and with no history of eating disorders. Body shape perception among this sample was complex and influenced by multiple factors. LEVEL OF EVIDENCE: Level I, randomized controlled trial.

Falls in Senior Adults: Demographics, Cost, Risk Stratification, and Evaluation.

Falls occur at staggering rates across the country, with 25% of Americans over 65 reporting annual falls. The fall rate in Missourian older adults is 27.3%. Eighty-six percent of fall-related deaths happen over the age of 65. There are many intrinsic and extrinsic factors that contribute to falls, with some factors that can be targeted and optimized by physicians. There are nuances to the history and physical that can help physicians identify these risk factors.

Assessing Dimensionality in Dichotomous Items When Many Subjects Have All-Zero Responses: An Example From Psychiatry and a Solution Using Mixture Models.

Common methods for determining the number of latent dimensions underlying an item set include eigenvalue analysis and examination of fit statistics for factor analysis models with varying number of factors. Given a set of dichotomous items, the authors demonstrate that these empirical assessments of dimensionality often incorrectly estimate the number of dimensions when there is a preponderance of individuals in the sample with all-zeros as their responses, for example, not endorsing any symptoms on a health battery. Simulated data experiments are conducted to demonstrate when each of several common diagnostics of dimensionality can be expected to under- or over-estimate the true dimensionality of the underlying latent variable. An example is shown from psychiatry assessing the dimensionality of a social anxiety disorder battery where 1, 2, 3, or more factors are identified, depending on the method of dimensionality assessment. An all-zero inflated exploratory factor analysis model (AZ-EFA) is introduced for assessing the dimensionality of the underlying subgroup corresponding to those possessing the measurable trait. The AZ-EFA approach is demonstrated using simulation experiments and an example measuring social anxiety disorder from a large nationally representative survey. Implications of the findings are discussed, in particular, regarding the potential for different findings in community versus patient populations.

Accurate Prediction of Knee Angles during Open-Chain Rehabilitation Exercises Using a Wearable Array of Nanocomposite Stretch Sensors.

In this work, a knee sleeve is presented for application in physical therapy applications relating to knee rehabilitation. The device is instrumented with sixteen piezoresistive sensors to measure knee angles during exercise, and can support at-home rehabilitation methods. The development of the device is presented. Testing was performed on eighteen subjects, and knee angles were predicted using a machine learning regressor. Subject-specific and device-specific models are analyzed and presented. Subject-specific models average root mean square errors of 7.6 and 1.8 degrees for flexion/extension and internal/external rotation, respectively. Device-specific models average root mean square errors of 12.6 and 3.5 degrees for flexion/extension and internal/external rotation, respectively. The device presented in this work proved to be a repeatable, reusable, low-cost device that can adequately model the knee's flexion/extension and internal/external rotation angles for rehabilitation purposes.

The impact of exercise intensity on neurophysiological indices of food-related inhibitory control and cognitive control: A randomized crossover event-related potential (ERP) study.

Food-related inhibitory control, the ability to withhold a dominant response towards highly palatable foods, influences dietary decisions. Food-related inhibitory control abilities may increase following a bout of aerobic exercise; however, the impact of exercise intensity on both food-related inhibitory control and broader cognitive control processes is currently unclear. We used a high-powered, within-subjects, crossover design to test how relative intensity of aerobic exercise influenced behavioral (response time, accuracy) and neural (N2 and P3 components of the scalp-recorded event-related potential [ERP]) measures of food-related inhibitory and cognitive control. Two hundred and ten participants completed three separate conditions separated by approximately one week in randomized order: two exercise conditions (35% VO2max or 70% VO2max) and seated rest. Directly following exercise or rest, participants completed a food-based go/no-go task and a flanker task while electroencephalogram data were recorded. Linear mixed models showed generally faster response times (RT) and improved accuracy following 70% VO2max exercise compared to rest, but not 35% VO2max; RTs and accuracy did not differ between 35% VO2max exercise and rest conditions. N2 and P3 amplitudes were larger following 70% VO2max exercise for the food-based go/no-go task compared to rest and 35% VO2max exercise. There were no differences between exercise conditions for N2 amplitude during the flanker task; however, P3 amplitude was more positive following 70% VO2max compared to rest, but not 35% VO2max exercise. Biological sex did not moderate exercise outcomes. Results suggest improved and more efficient food-related recruitment of later inhibitory control and cognitive control processes following 70% VO2max exercise.

To play or not to play? The relationship between active video game play and electrophysiological indices of food-related inhibitory control in adolescents.

Sedentary behaviors, such as computer use and sedentary video games, are barriers to physical activity, contribute to overweight and obesity among adolescents, and can adversely affect eating behaviors. Active video games may increase daily physical activity levels among adolescents and improve food-related inhibitory control. We compared the effects of acute bouts of active and sedentary video gaming on event-related potential (ERP) indices of food-related inhibitory control, energy expenditure, and ad libitum eating. In a within-subjects design, 59 adolescent participants (49% female, Mage  = 13.29 ± 1.15) completed two separate counterbalanced, 60-min long video gaming sessions separated by seven days. Immediately after, participants completed two go/no-go tasks with high- and low-calorie images and N2 and P3 ERP amplitudes were measured. Participants also completed a Stroop task and were given high- and low-calorie snacks to consume ad libitum. Results indicated that active relative to sedentary video games significantly increased energy expenditure on multiple measures (e.g., METs, heart rate, kcals burned) and participants consumed more calories after the active compared to the sedentary video game session. N2 amplitudes were larger when participants inhibited to high- compared to low-calorie foods, suggesting that high-calorie foods necessitate increased the recruitment of inhibitory control resources; however, there were non-significant differences for the N2 or P3 amplitudes, accuracy or response times, and Stroop performance between active versus sedentary video game sessions. Overall, sixty minutes of active video gaming increased energy expenditure and food consumption but did not significantly alter neural or behavioral measures of inhibitory control to food stimuli.

Evaluating Relationships Between Sleep and Next-Day Physical Activity in Young Women.

BACKGROUND: To evaluate the relationship between sleep and next-day physical activity (PA) under free-living conditions in women. METHODS: Sleep and PA were measured objectively for 7 consecutive days by accelerometry in 330 young adult women (aged 17-25 y). A structural equation model was used to evaluate the relationship between the driving factor of sleep (total sleep or morning wake time) and the amount of nonsleep sedentary (SED) and moderate to vigorous physical activity (MVPA) each day. RESULTS: With sleep duration as the driving factor, the estimates of ßSED and ßMVPA were -0.415 and -0.093, respectively (P ≤ .05). For every hour slept, a 24.9-minute reduction in SED time and a 5.58-minute reduction in MVPA were observed. With wake time as the driving factor, the estimates of ßSED and ßMVPA were -0.636 and -0.149, respectively. For every wake time that was 1 hour later, a 38.2-minute decrease in SED and a 8.9-minute decrease in MVPA (P ≤ .05) were observed. CONCLUSIONS: Women who wake later or who sleep longer tend to get less MVPA throughout the day. Getting up earlier and going to bed earlier may support behaviors that improve PA and lifestyle.

A case study exploring associations between popular media attention of scientific research and scientific citations.

The association between mention of scientific research in popular media (e.g., the mainstream media or social media platforms) and scientific impact (e.g., citations) has yet to be fully explored. The purpose of this study was to clarify this relationship, while accounting for some other factors that likely influence scientific impact (e.g., the reputations of the scientists conducting the research and academic journal in which the research was published). To accomplish this purpose, approximately 800 peer-reviewed articles describing original research were evaluated for scientific impact, popular media attention, and reputations of the scientists/authors and publication venue. A structural equation model was produced describing the relationship between non-scientific impact (popular media) and scientific impact (citations), while accounting for author/scientist and journal reputation. The resulting model revealed a strong association between the amount of popular media attention given to a scientific research project and corresponding publication and the number of times that publication is cited in peer-reviewed scientific literature. These results indicate that (1) peer-reviewed scientific publications receiving more attention in non-scientific media are more likely to be cited than scientific publications receiving less popular media attention, and (2) the non-scientific media is associated with the scientific agenda. These results may inform scientists who increasingly use popular media to inform the general public and scientists concerning their scientific work. These results might also inform administrators of higher education and research funding mechanisms, who base decisions partly on scientific impact.

Predicting vertical ground reaction force during running using novel piezoresponsive sensors and accelerometry.

Running is a common exercise with numerous health benefits. Vertical ground reaction force (vGRF) influences running injury risk and running performance. Measurement of vGRF during running is now primarily constrained to a laboratory setting. The purpose of this study was to evaluate a new approach to measuring vGRF during running. This approach can be used outside of the laboratory and involves running shoes instrumented with novel piezoresponsive sensors and a standard accelerometer. Thirty-one individuals ran at three different speeds on a force-instrumented treadmill while wearing the instrumented running shoes. vGRF was predicted using data collected from the instrumented shoes, and predicted vGRF were compared to vGRF measured via the treadmill. Per cent error of the resulting predictions varied depending upon the predicted vGRF characteristic. Per cent error was relatively low for predicted vGRF impulse (2-7%), active peak vGRF (3-7%), and ground contact time (3-6%), but relatively high for predicted vGRF load rates (22-29%). These errors should decrease with future iterations of the instrumented shoes and collection of additional data from a more diverse sample. The novel technology described herein might become a feasible way to collect large amounts of vGRF data outside of the traditional biomechanics laboratory.

Functional Data Analyses of Gait Data Measured Using In-Shoe Sensors.

In studies of gait, continuous measurement of force exerted by the ground on a body, or ground reaction force (GRF), provides valuable insights into biomechanics, locomotion, and the possible presence of pathology. However, gold-standard measurement of GRF requires a costly in-lab observation obtained with sophisticated equipment and computer systems. Recently, in-shoe sensors have been pursued as a relatively inexpensive alternative to in-lab measurement. In this study, we explore the properties of continuous in-shoe sensor recordings using a functional data analysis approach. Our case study is based on measurements of three healthy subjects, with more than 300 stances (defined as the period between the foot striking and lifting from the ground) per subject. The sensor data show both phase and amplitude variabilities; we separate these sources via curve registration. We examine the correlation of phase shifts across sensors within a stance to evaluate the pattern of phase variability shared across sensors. Using the registered curves, we explore possible associations between in-shoe sensor recordings and GRF measurements to evaluate the in-shoe sensor recordings as a possible surrogate for in-lab GRF measurements.

Nano-Composite Foam Sensor System in Football Helmets.

American football has both the highest rate of concussion incidences as well as the highest number of concussions of all contact sports due to both the number of athletes and nature of the sport. Recent research has linked concussions with long term health complications such as chronic traumatic encephalopathy and early onset Alzheimer's. Understanding the mechanical characteristics of concussive impacts is critical to help protect athletes from these debilitating diseases and is now possible using helmet-based sensor systems. To date, real time on-field measurement of head impacts has been almost exclusively measured by devices that rely on accelerometers or gyroscopes attached to the player's helmet, or embedded in a mouth guard. These systems monitor motion of the head or helmet, but do not directly measure impact energy. This paper evaluates the accuracy of a novel, multifunctional foam-based sensor that replaces a portion of the helmet foam to measure impact. All modified helmets were tested using a National Operating Committee Standards for Athletic Equipment-style drop tower with a total of 24 drop tests (4 locations with 6 impact energies). The impacts were evaluated using a headform, instrumented with a tri-axial accelerometer, mounted to a Hybrid III neck assembly. The resultant accelerations were evaluated for both the peak acceleration and the severity indices. These data were then compared to the voltage response from multiple Nano Composite Foam sensors located throughout the helmet. The foam sensor system proved to be accurate in measuring both the HIC and Gadd severity index, as well as peak acceleration while also providing additional details that were previously difficult to obtain, such as impact energy.

Estimation of 3D Ground Reaction Force Using Nanocomposite Piezo-Responsive Foam Sensors During Walking.

This paper describes a method for the estimation of the 3D ground reaction force (GRF) during human walking using novel nanocomposite piezo-responsive foam (NCPF) sensors. Nine subjects (5 male, 4 female) walked on a force-instrumented treadmill at 1.34 m/s for 120 s each while wearing a shoe that was instrumented with four NCPF sensors. GRF data, measured via the treadmill, and sensor data, measured via the NCPF inserts, were used in a tenfold cross validation process to calibrate a separate model for each individual. The calibration model estimated average anterior-posterior, mediolateral and vertical GRF with mean average errors (MAE) of 6.52 N (2.14%), 4.79 N (6.34%), and 15.4 N (2.15%), respectively. Two additional models were created using the sensor data from all subjects and subject demographics. A tenfold cross validation process for this combined data set resulted in models that estimated average anterior-posterior, mediolateral and vertical GRF with less than 8.16 N (2.41%), 6.63 N (7.37%), and 19.4 N (2.31%) errors, respectively. Intra-subject estimates based on the model had a higher accuracy than inter-subject estimates, likely due to the relatively small subject cohort used in creating the model. The novel NCPF sensors demonstrate the ability to accurately estimate 3D GRF during human movement outside of the traditional biomechanics laboratory setting.

Disparity in neural and subjective responses to food images in women with obesity and normal-weight women.

OBJECTIVE: Self-reports tend to differ from objective measurements of food intake, particularly in adults with obesity; however, no studies have examined how neural responses to food (an objective measure) and subjective ratings of food differ by BMI status. This study tested normal-weight women (NWW) and women with obesity (OBW) for group differences in neural indices of attention towards food pictures, subjective ratings of these pictures, and the disparity between objective and subjective measurements. METHODS: Twenty-two NWW (21.8 ± 1.7 kg/m2 ) and 22 OBW (37.0 ± 5.7 kg/m2 ) viewed food and flower pictures while late positive potential amplitude, an event-related potential, was recorded. Participants rated pictures for arousal and valence. RESULTS: Late positive potential amplitude was larger toward food than flower pictures. OBW self-reported flower pictures as more pleasant than food; NWW showed no difference for pleasantness. There were no significant main effects or interactions for arousal. Standardized scores showed that only on subjective, but not objective, measures did OBW compared with NWW disproportionately indicate food pictures as less pleasant than flowers. CONCLUSIONS: Compared with NWW, OBW showed larger discrepancies between neural and subjective reports of attention towards food. Inaccurate self-reports of attention towards food may reduce the efficiency of health interventions.

Risk factors for recurrence after surgery in non-metastatic RCC with thrombus: a contemporary multicentre analysis.

OBJECTIVE: To determine the predictors of post-surgical recurrence for patients with non-metastatic renal cell carcinoma (RCC) and venous thrombus. METHODS: Records from consecutive patients with non-metastatic RCC with tumour thrombus, treated surgically between 2000 and 2012 at one of three centres, were reviewed. Univariable and multivariable analysis were used to evaluate the association of risk factors for post-surgical recurrence. RESULTS: A total of 465 patients with non-metastatic RCC were identified, including patients with thrombus present in the renal vein (257 patients, 55.3%), infrahepatic inferior vena cava (IVC; 144 patients, 31.0%) and suprahepatic IVC (64 patients, 13.8%). The median (interquartile range) follow-up was 28.3 (12.2-56.4) months, with metastatic RCC developing in 188 patients (40.5%). Independent predictors of recurrence included: body mass index ≤20 kg/m(2) (hazard ratio [HR] 2.66; 95% confidence interval [CI] 1.29-5.49), low preoperative haemoglobin (HR 1.54; 95% CI 1.07-2.20), perinephric fat invasion (HR 1.51; 95% CI 1.09-2.10), IVC thrombus height (HR 2.64; 95% CI 1.47-4.74), tumour diameter (HR 1.04 95% CI 1.00-1.09), nuclear grade (HR 1.56 95% CI 1.12-2.15) and non-clear-cell histology (HR 2.13; 95% CI 1.30-3.50). Independently predictive variables were used to create a recurrence model for three risk groups based on 0, 1-2, or >2 risk factors, respectively. The 5-year recurrence-free survival rate was significantly different in patients with favourable-risk (79.1%) compared with intermediate- (55.1%) or high-risk (22.1%) disease (P < 0.001). CONCLUSIONS: Seven risk factors for recurrence were identified for patients with non-metastatic RCC with thrombus, which can be used to select patients who may benefit from increased surveillance or adjuvant therapy clinical trials.

Highest risk of symptomatic venous thromboembolic events after radical cystectomy occurs in patients with obesity or nonurothelial cancers.

CONTEXT: Venous thromboembolism (VTE) is a common cause of postoperative morbidity and mortality in cystectomy patients. AIMS: The aim of this study is to identify variables associated with risk of developing deep venous thrombosis (DVT) or pulmonary embolism (PE) within 90 days after radical cystectomy (RC). SETTING AND DESIGN: Retrospective chart review of patients undergoing RC from 2004 to 2011 at the University of Wisconsin. SUBJECTS AND METHODS: Clinical variables collected for all RC patients. All patients received mechanical prophylaxis, and routine heparin prophylaxis began in 2010. STATISTICAL ANALYSIS USED: Univariate and multivariate analyses were used to evaluate VTE association with known risk factors. RESULTS: A total of 241 patients were identified with median age of 67.1 (interquartile range: 57.8-74.3) years. Body mass index (BMI) was ≥30 in 36.8% of patients. Median blood loss was 950 (600-1500) mL and 157/241 (65.2%) patients received a blood transfusion. CONCLUSIONS: Patients with BMI ≥30 or nonurothelial cancer are at highest risk for postoperative VTE and should be considered for extended heparin prophylaxis.