Employee wellness, health risk assessment, modifiable health risk, PEN-3 model, worksite culture, worksite envirmonent

This study used an online Health Risk Appraisal (HRA) to assess individual employee health and eight additional statements to assess the worksite health culture of Eastern Michigan University. It was hypothesized there will be a relationship between EMU employees’ levels of self-reported health risk and their perceptions of supportiveness of the worksite environment and health culture. The results indicated the relationship between health risks of participants and perception of supportiveness of the worksite culture was not significant (p \u3e.05). Of the employees that participated, the top three risk factors identified were body weight (20%), stress (14%), and blood pressure (10%). The tenets of the PEN-3 model were used to identify points of entry for possible future health promotion programming. It was found that 54% of participants were willing to participate in programs to enhance overall health. Further assessment using a larger sample size is needed to enhance understanding of the relationshi

The perimeter of uniform and geometric words: a probabilistic analysis

Let a word be a sequence of $n$ i.i.d. integer random variables. The perimeter $P$ of the word is the number of edges of the word, seen as a polyomino. In this paper, we present a probabilistic approach to the computation of the moments of $P$. This is applied to uniform and geometric random variables. We also show that, asymptotically, the distribution of $P$ is Gaussian and, seen as a stochastic process, the perimeter converges in distribution to a Brownian motionComment: 13 pages, 7 figure

A Review of Orofacial Clefting and Current Genetic Mouse Models

The prevalence of orofacial clefts (OFCs) is nearly 10.2 per 10,000 births in the United States and 9.9 per 10,000 births worldwide. OFCs occur as a result of a break (nonfusion) of orofacial structures during development. This can occur due to a variety of reasons;prenatal exposure to many drugs and environmental factors as well as genetic factors which are implicated in the development of OFCs. While approximately 15 types of clefts have been identified, there are at least four distinct classifications of OFCs. These include complete cleft palate with cleft lip; cleft of the anterior palate, which may/may not involve cleft lip; cleft of the posterior palate; and submucosal cleft. A number of candidate genes have been identified, including transforming growth factor beta (TGFβ) and homeobox genes (e.g., MSX1), among many others. What follows is a review of mouse models currently used in research and the classification of their overall contribution to known OFCs

A Liouville theorem for some Bessel generalized operators

In this paper we establish a Liouville theorem in $\mathcal{H'}_{\mu}$ for a wider class of operators in $(0,\infty)^{n}$ that generalizes the $n$-dimensional Bessel operator. We will present two different proofs, based in two representation theorems for certain distributions "supported in zero"

Training Toys ... Bells, Ropes, and Balls - Oh My!

Participation in regular moderate-to-vigorous physical activity often decreases with increasing age (16), and among people who do exercise, long-term adherence often is a challenge because of various factors including lack of enjoyment, intrinsic motivation, or social support; poor environment; inconvenience; fear of injury; and health-related issues. During the past decade, general fitness professionals and personal trainers have incorporated numerous adjunct modalities (‘‘toys’’) to ‘‘break up’’ the rigors of fitness training and as a means to introduce some diversion and goal-specific activities. Three popular modalities are kettlebells, battling ropes, and medicine balls. This article briefly reviews each device and presents some applications for their use in the fitness setting

Predicting diabetes mellitus using SMOTE and ensemble machine learning approach: The Henry Ford ExercIse Testing (FIT) project

Machine learning is becoming a popular and important approach in the field of medical research. In this study, we investigate the relative performance of various machine learning methods such as Decision Tree, Naïve Bayes, Logistic Regression, Logistic Model Tree and Random Forests for predicting incident diabetes using medical records of cardiorespiratory fitness. In addition, we apply different techniques to uncover potential predictors of diabetes. This FIT project study used data of 32,555 patients who are free of any known coronary artery disease or heart failure who underwent clinician-referred exercise treadmill stress testing at Henry Ford Health Systems between 1991 and 2009 and had a complete 5-year follow-up. At the completion of the fifth year, 5,099 of those patients have developed diabetes. The dataset contained 62 attributes classified into four categories: demographic characteristics, disease history, medication use history, and stress test vital signs. We developed an Ensembling-based predictive model using 13 attributes that were selected based on their clinical importance, Multiple Linear Regression, and Information Gain Ranking methods. The negative effect of the imbalance class of the constructed model was handled by Synthetic Minority Oversampling Technique (SMOTE). The overall performance of the predictive model classifier was improved by the Ensemble machine learning approach using the Vote method with three Decision Trees (Naïve Bayes Tree, Random Forest, and Logistic Model Tree) and achieved high accuracy of prediction (AUC = 0.92). The study shows the potential of ensembling and SMOTE approaches for predicting incident diabetes using cardiorespiratory fitness data

Relation of a Maximal Exercise Test to Change in Exercise Tolerance During Cardiac Rehabilitation

The purpose of this study was to test the hypothesis that an individualized exercise training target heart rate (HR) based on a maximal graded exercise test (GXT) is associated with greater improvements in exercise tolerance during cardiac rehabilitation (CR) compared with no GXT. In this retrospective study, we identified patients who completed 9 to 36 visits of CR between 2001 and 2016, with a length of stay ≤18 weeks and a visit frequency of 1 to 3 days per week. Patients were grouped based on whether their exercise was guided by a target HR determined from a GXT. To assess the relation between GXT and change in exercise training metabolic equivalents of task (METs), we used generalized linear models adjusted for age, gender, race, referral reason, CR visits, CR frequency, METs at start, CR location, and year of participation. Out of 4,455 patients (37% female, 48% White, median age = 62 years), 53% were prescribed a target HR based on a GXT. Compared with no GXT, a GXT was associated with a significantly greater increase in covariate-adjusted METs during CR and percentage change from start (+0.44 METs [95% confidence interval [CI] 0.38 to 0.51] and +17% [95% CI 14% to 19%], respectively). In a sensitivity analysis limited to patients with 24 to 36 visits at ≥2 days per week (n = 1,319), a GXT was associated with a significantly greater increase in covariate-adjusted exercise training METs (+0.51 [95% CI 0.36 to 0.66]; +19% [95% CI 13% to 24%]). In conclusion, to maximize the potential increase in exercise capacity during CR, patients should undergo a GXT to determine an individualized exercise training target HR

Statins and Exercise Training Response in Heart Failure Patients: Insights From HF-ACTION.

OBJECTIVES: The aim of this study was to assess for a treatment interaction between statin use and exercise training (ET) response. BACKGROUND: Recent data suggest that statins may attenuate ET response, but limited data exist in patients with heart failure (HF). METHODS: HF-ACTION (Heart Failure: A Controlled Trial Investigating Outcomes of Exercise Training) was a randomized trial of 2,331 patients with chronic HF with ejection fraction ≤35% who were randomized to usual care with or without ET. We evaluated whether there was a treatment interaction between statins and ET response for the change in quality of life and aerobic capacity (peak oxygen consumption and 6-min walk distance) from baseline to 3 months. We also assessed for a treatment interaction among atorvastatin, simvastatin, and pravastatin and change in these endpoints with ET. Multiple linear regression analyses were performed for each endpoint, adjusting for baseline covariates. RESULTS: Of 2,331 patients in the HF-ACTION trial, 1,353 (58%) were prescribed statins at baseline. Patients treated with statins were more likely to be older men with ischemic HF etiology but had similar use of renin angiotensin system blockers and beta-blockers. There was no evidence of a treatment interaction between statin use and ET on changes in quality of life or exercise capacity, nor was there evidence of differential association between statin type and ET response for these endpoints (all p values \u3e0.05). CONCLUSIONS: In a large chronic HF cohort, there was no evidence of a treatment interaction between statin use and short-term change in aerobic capacity and quality of life with ET. These findings contrast with recent reports of an attenuation in ET response with statins in a different population, highlighting the need for future prospective studies. (Exercise Training Program to Improve Clinical Outcomes in Individuals With Congestive Heart Failure; NCT00047437)