Population and Age-Based Cardiorespiratory Fitness Level Investigation and Automatic Prediction

Maximal oxygen consumption (VO2max) reflects aerobic capacity and is crucial for assessing cardiorespiratory fitness and physical activity level. The purpose of this study was to classify and predict the population-based cardiorespiratory fitness based on anthropometric parameters, workload, and steady-state heart rate (HR) of the submaximal exercise test. Five hundred and seventeen participants were recruited into this study. This study initially classified aerobic capacity followed by VO2max predicted using an ordinary least squares regression model with measured VO2max from a submaximal cycle test as ground truth. Furthermore, we predicted VO2max in the age ranges 21–40 and above 40. For the support vector classification model, the test accuracy was 75%. The ordinary least squares regression model showed the coefficient of determination (R2) between measured and predicted VO2max was 0.83, mean absolute error (MAE) and root mean square error (RMSE) were 3.12 and 4.24 ml/kg/min, respectively. R2 in the age 21–40 and above 40 groups were 0.85 and 0.75, respectively. In conclusion, this study provides a practical protocol for estimating cardiorespiratory fitness of an individual in large populations. An applicable submaximal test for population-based cohorts could evaluate physical activity levels and provide exercise recommendations.

PASIG RIVER WATER QUALITY ESTIMATION USING AN EMPIRICAL ORDINARY LEAST SQUARES REGRESSION MODEL OF SENTINEL-2 SATELLITE IMAGES

This study entails generation of empirical ordinary least squares regression models to estimate water parameters. It uses remote sensing for environmental monitoring of Pasig River located in the Philippines. This uses measurements of primary water quality (WQ) parameters defined on Department of Environment and Natural Resources Administrative Order 2016-08 recorded on the Pasig River Unified Monitoring Stations (PRUMS) report from January to June of 2019. Sentinel-2 images are utilized to estimate biological oxygen demand (BOD), Chloride, Color, Dissolved Oxygen (DO), Fecal Coliform, Nitrate, pH, Phosphate, Temperature, and Total suspended solids (TSS). Feature generation involved calculation of different band reflectances from the satellite image. Exhaustive feature selection through application of a Pearson Correlation threshold was applied to limit number of independent variables. The box-cox transformations of water quality parameters (except for Temperature) were used as dependent variables and the selected features are used as dependent variables for the ordinary least squares regression model. The root mean square error (RMSE) values for the models which are computed using the k-fold cross validation technique showed outliers, especially for the TSS model (>547000 mg/L), which made its average negative RMSE so large. Tests for multicollinearity, autocorrelation, and homoscedasticity indicated problems in models created. However, normality of residuals indicates that models allow us to roughly estimate water quality for the river as a whole with the advantages of remote sensing, enabling a better perspective for its spatial distribution.

Using Inverse Probability Weighting to Address Post-Outcome Collider Bias

We consider the problem of bias arising from conditioning on a post-outcome collider. We illustrate this with reference to Elwert and Winship (2014) but we go beyond their study to investigate the extent to which inverse probability weighting might offer solutions. We use linear models to derive expressions for the bias arising in different kinds of post-outcome confounding, and we show the specific situations in which inverse probability weighting will allow us to obtain estimates that are consistent or, if not consistent, less biased than those obtained via ordinary least squares regression.

Factors Affecting the Cases and Deaths of COVID-19 Victims

This paper attempts to find the factors that affect the number of cases and deaths of coronavirus disease 2019 (COVID-19) patients a year after the first outbreak in Wuhan, China. There were 141 countries affected with COVID-19 involved in the study. Countries were grouped based on population. Using ordinary least squares regression, it was found that the total number of cases and deaths were significantly related with the levels of population of the different countries. On the overall, median age of the country, and average temperature are positively related with the number of deaths from the virus. On the other hand, population density is positively related with the deaths due to COVID for low populated countries. The result of this preliminary study can be used as a benchmark for authorities in the formulation of policies with regards to treating COVID-19 related issues.

Characterization of a high-resolution breath acetone meter for ketosis monitoring

Background The ketone bodies beta-hydroxybutyrate (BHB) and acetone are endogenous products of fatty acid metabolism. Although ketone levels can be monitored by measuring either blood BHB or breath acetone, determining the precise correlation between these two measurement methods has been challenging. The purpose of this study is to characterize the performance of a novel portable breath acetone meter (PBAM) developed by Readout, Inc., to compare single versus multiple daily ketone measurements, and to compare breath acetone (BrAce) and blood BHB measurements. Methods We conducted a 14-day prospective observational cohort study of 21 subjects attempting to follow either a low-carbohydrate/ketogenic or a standard diet. Subjects were asked to concurrently measure both blood BHB and BrAce five times per day and report the results using an online data entry system. We evaluated the utility of multiple daily measurements by calculating the coefficient of variation (CV) for each daily group of measurements. We calculated the correlation between coincident BrAce and blood BHB measurements using linear ordinary least squares regression analysis. We assessed the ability of the BrAce measurement to accurately predict blood BHB states using receiver operating characteristic (ROC) analysis. Finally, we calculated a daily ketone exposure (DKE) using the area under the curve (AUC) of a ketone concentration versus time graph and compared the DKE of BrAce and blood BHB using linear ordinary least squares regression. Results BrAce and blood BHB varied throughout the day by an average of 44% and 46%, respectively. The BrAce measurement accurately predicted whether blood BHB was greater than or less than the following thresholds: 0.3 mM (AUC = 0.898), 0.5 mM (AUC = 0.854), 1.0 mM (AUC = 0.887), and 1.5 mM (AUC = 0.935). Coincident BrAce and blood BHB measurements were moderately correlated with R2 = 0.57 (P < 0.0001), similar to literature reported values. However, daily ketone exposures, or areas under the curve, for BrAce and blood BHB were highly correlated with R2 = 0.80 (P < 0.0001). Conclusions The results validated the performance of the PBAM. The BrAce/BHB correlation was similar to literature values where BrAce was measured using highly accurate lab instruments. Additionally, BrAce measurements using the PBAM can be used to predict blood BHB states. The relatively high daily variability of ketone levels indicate that single blood or breath ketone measurements are often not sufficient to assess daily ketone exposure for most users. Finally, although single coincident blood and breath ketone measurements show only a moderate correlation, possibly due to the temporal lag between BrAce and blood BHB, daily ketone exposures for blood and breath are highly correlated.

Estimating the Relationship Between Perceived Stigma and Victimization of People With Mental Illness

Over the past two decades, we have substantially increased our understanding of violence committed by individuals with mental illness, while comparatively less is known about the victimization experiences of this population. What has been established in the literature is that individuals with mental illness are more likely to experience victimization than the general public, and certain risk factors influence the likelihood of victimization. What remains unexplored is the possibility that a person with mental illness’ perception that mental illness is stigmatized may be significantly associated with victimization experiences. Thus, the purpose of the current study is to examine whether stigma and victimization are associated, and in what direction. In other words, does perceived stigma lead to victimization? Or does victimization lead to perceived stigma? To assess these research questions, data from the Community Outcomes of Assisted Outpatient Treatment study are used, which is a longitudinal study of individuals with serious mental illness ( n = 184). A variety of methods are employed to assess the association between victimization and perceived stigma including logistic and ordinary least squares regression models. Results from the logistic regression model indicate that perceived stigma is associated with an increase in the odds that a person with mental illness will experience victimization at later follow-ups. Results from the ordinary least squares regression analysis, however, show that victimization at baseline does not predict perceived stigma at later times. Implications regarding future research and clinical practice are discussed.

Characterization of a high-resolution breath acetone meter for ketosis monitoring

ABSTRACTBackgroundThe ketone bodies beta-hydroxybutyrate (BHB) and acetone are endogenous products of fatty acid metabolism. Although ketone levels can be monitored by measuring either blood BHB or breath acetone, determining the precise correlation between these two measurement methods has been challenging. The purpose of this study is to characterize the performance of a novel portable breath acetone meter (PBAM) developed by Readout, Inc., to compare single versus multiple daily ketone measurements, and to compare breath acetone (BrAce) and blood BHB measurements.MethodsWe conducted a 14-day prospective observational cohort study of 21 subjects attempting to follow either a low-carbohydrate/ketogenic or a standard diet. Subjects were asked to concurrently measure both blood BHB and BrAce five times per day and report the results using an online data entry system. We evaluated the utility of multiple daily measurements by calculating the coefficient of variation (CV) for each daily group of measurements. We calculated the correlation between coincident BrAce and blood BHB measurements using linear ordinary least squares regression analysis. We assessed the ability of the BrAce measurement to accurately predict blood BHB states using receiver operating characteristic (ROC) analysis. Finally, we calculated a daily ketone exposure (DKE) using the area under the curve (AUC) of a ketone concentration versus time graph and compared the DKE of BrAce and blood BHB using linear ordinary least squares regression.ResultsBrAce and blood BHB varied throughout the day by an average of 44% and 46%, respectively. The BrAce measurement accurately predicted whether blood BHB was greater than or less than the following thresholds: 0.3 mM (AUC = 0.898), 0.5 mM (AUC = 0.854), 1.0 mM (AUC = 0.887), and 1.5 mM (AUC = 0.935). Coincident BrAce and blood BHB measurements were moderately correlated with R2 = 0.57 (P < 0.0001), similar to literature reported values. However, daily ketone exposures, or areas under the curve, for BrAce and blood BHB were highly correlated with R2 = 0.83 (P < 0.0001).ConclusionsThe results validated the performance of the PBAM. The BrAce/BHB correlation was similar to literature values where BrAce was measured using highly accurate lab instruments. Additionally, BrAce measurements using the PBAM can be used to predict blood BHB states. The relatively high daily variability of ketone levels indicate that single blood or breath ketone measurements are often not sufficient to assess daily ketone exposure for most users. Finally, although single coincident blood and breath ketone measurements show only a moderate correlation, possibly due to the temporal lag between BrAce and blood BHB, daily ketone exposures for blood and breath are highly correlated.

Projecting a High-School Quarterback’s Performance at the Collegiate Level

We examine recruiting ratings for high-school quarterbacks over the period 2006-2012 from Rivals, 247 Sports, and ESPN. Using Lee & Preacher’s (2013) test of the difference between two dependent correlations with one variable in common and ordinary least squares regression, we determine that the Rivals ratings have the strongest correlation with quarterback performance over the time-period examined. The 247 Sports ratings follow closely behind the Rivals ratings; however, the ESPN ratings correlate more weakly with a quarterback’s career performance in college.