Fitness facilities have potential to serve as places of 'health enhancement' for many underserved populations, particularly among people with physical/mobility disabilities where walking outdoors to meet recommendations for regular physical activity is not an option due to mobility or safety issues. To examine the accessibility and usability of fitness facilities across the U.S. from a broader framework of physical and program access. A convenience sample of 227 fitness facilities in 10 states were assessed by trained evaluators using the Accessibility Instrument Measuring Fitness and Recreation Environments (AIMFREE) tool. Non-parametric tests were performed to determine whether AIMFREE section scores were different by geographic region (urban, suburban), business type (nonprofit, for-profit), facility affiliation (fitness center/health club, park district/community center, hospital/rehabilitation facility, university/college), and facility construction date (pre/post passage of the Americans with Disabilities Act, ADA). Raw scores were converted to scaled scores with higher scores indicating better accessibility based on a criterion-referenced approach. Section scale scores (11/13) were low (<70) with differences found across facility affiliation. While facilities built after passage of the ADA had higher accessibility scores compared to pre-ADA facilities, only programs and water fountains had scaled scores ≥70 regardless of facility construction date. There exists a strong and urgent need to encourage owners and operators of fitness facilities to reach a higher level of accessibility. Until then, many people with physical/mobility disabilities will continue to have limited access to programs, equipment, and services offered at these facilities.

Background: Low levels of oxygen in tissues, seen in situations such as chronic lung disease, necrotic tumors, and high altitude exposures, initiate a signaling pathway that results in active transcription of genes possessing a hypoxia response element (HRE). The aim of this study was to investigate whether a change in miRNA expression following hypoxia could account for changes in the cellular transcriptome based on currently available miRNA target prediction tools.Methods: To identify changes induced by hypoxia, we conducted mRNA- and miRNA-array-based experiments in HT29 cells, and performed comparative analysis of the resulting data sets based on multiple target prediction algorithms. To date, few studies have investigated an environmental perturbation for effects on genome-wide miRNA levels, or their consequent influence on mRNA output.Results: Comparison of miRNAs with predicted mRNA targets indicated a lower level of concordance than expected. We did, however, find preliminary evidence of combinatorial regulation of mRNA expression by miRNA.Conclusion: Target prediction programs and expression profiling techniques do not yet adequately represent the complexity of miRNA-mediated gene repression, and new methods may be required to better elucidate these pathways. Our data suggest the physiologic impact of miRNAs on cellular transcription results from a multifaceted network of miRNA and mRNA relationships, working together in an interconnected system and in context of hundreds of RNA species. The methods described here for comparative analysis of cellular miRNA and mRNA will be useful for understanding genome wide regulatory responsiveness and refining miRNA predictive algorithms.

Journal of Medical Internet Research - International Scientific Journal for Medical Research, Information and Communication on the Internet #Preprint #PeerReviewMe: Warning: This is a unreviewed preprint. Readers are warned that the document has not been peer-reviewed by expert/patient reviewers or an academic editor, may contain misleading claims, and is likely to undergo changes before final publication, if accepted, or may have been rejected/withdrawn. Readers with interest and expertise are encouraged to sign up as peer-reviewer, if the paper is within an open peer-review period. Please cite this preprint only for review purposes or for grant applications and CVs (if you are the author). Background: People with Multiple Sclerosis (MS) face varying levels of disability and symptoms, thus requiring highly trained therapists and/or exercise trainers to design personalized exercise programs. However, for people living in geographically isolated communities, access to such trained professionals can be challenging due to a number of barriers associated with cost, access to transportation and travel distance. Generic mHealth exercise apps often fall short of what people with MS need to become physically active (i.e., exercise content that has been adapted to accommodate a wide range of functional limitations). Objective: This usability study describes the development process of the TEAMS (Tele-Exercise and Multiple Sclerosis) app, which is being used by people with MS in a large randomized controlled trial (RCT) to engage in home-based telerehabilitation. Methods: Twenty-one participants with disabilities (10 people with MS) were involved in the double iterative design, which included the simultaneous development of the app features and exercise content (exercise videos and articles). Framed within a user-centered design (UCD) approach, the development process included two stages: ground-level creation (focus group followed by early stage evaluations and developments), and proof of concept through two usability tests. Usability (effectiveness, usefulness, and satisfaction) was evaluated through a mixed methods approach. Results: Regarding app effectiveness, the second usability test resulted in an average of one problem per participant, a decrease of 53% compared to the initial usability test. Five themes were constructed from the qualitative data that related to usefulness and satisfaction: high perceived confidence for app usability, positive perceptions of exercise videos, viable exercise option at home, orientation and familiarity required for successful participation, and app issues. Participants acknowledged that the final app was ready to be delivered to the public after minor revisions. After including these revisions, the project team released the final app that is being used in the RCT. Conclusions: A multi-level user-centered development process resulted in an inclusive exercise program for people with MS operated through an easy-to-use app. The promotion of exercise through self-regulated mHealth programs requires a stakeholder-driven approach to app development. This ensures that app and content match the preferences and functional abilities of the end user (i.e., people with varying levels of MS).

Obesity is closely related to the development of insulin resistance and type 2 diabetes (T2D). The prevention of T2D has become imperative to stem the rising rates of this disease. Weight loss is highly effective in preventing T2D; however, the at-risk pool is large, and a clinically meaningful metric for risk stratification to guide interventions remains a challenge. The objective of this study is to predict T2D risk using full-information continuous analysis of nationally sampled data from white and black American adults age ≥45 years. A sample of 12,043 black (33%) and white individuals from a population-based cohort, REasons for Geographic And Racial Differences in Stroke (REGARDS) (enrolled 2003–2007), was observed through 2013–2016. The mean participant age was 63.12 ± 8.62 years, and 43.7% were male. Mean BMI was 28.55 ± 5.61 kg/m². Risk factors for T2D regularly recorded in the primary care setting were used to evaluate future T2D risk using Bayesian logistic regression. External validation was performed using 9,710 participants (19% black) from Atherosclerotic Risk in Communities (ARIC) (enrolled 1987–1989), observed through 1996–1998. The mean participant age in this cohort was 53.86 ± 5.65 years, and 44.6% were male. Mean BMI was 27.15 ± 4.92 kg/m². Predictive performance was assessed using the receiver operating characteristic (ROC) curves and area under the curve (AUC) statistics. The primary outcome was incident T2D. By 2016 in REGARDS, there were 1,602 incident cases of T2D. Risk factors used to predict T2D progression included age, sex, race, BMI, triglycerides, high-density lipoprotein, blood pressure, and blood glucose. The Bayesian logistic model (AUC = 0.79) outperformed the Framingham risk score (AUC = 0.76), the American Diabetes Association risk score (AUC = 0.64), and a cardiometabolic disease system (using Adult Treatment Panel III criteria) (AUC = 0.75). Validation in ARIC was robust (AUC = 0.85). Main limitations include the limited generalizability of the REGARDS sample to black and white, older Americans, and no time to diagnosis for T2D. Our results show that a Bayesian logistic model using full-information continuous predictors has high predictive discrimination, and can be used to quantify race- and sex-specific T2D risk, providing a new, powerful predictive tool. This tool can be used for T2D prevention efforts including weight loss therapy by allowing clinicians to target high-risk individuals in a manner that could be used to optimize outcomes.