Filtering by
- All Subjects: Exercise
- All Subjects: Diabetes
- Creators: College of Health Solutions
Methods— Data were extracted and filtered from electronic databases PubMed (MEDLINE), CINAHL, Embase, PsycINFO, and Scopus. Intervention effects were represented by Hedges’ g and combined into pooled effect sizes using random effects models. Heterogeneity was evaluated using the Chi-squared (Q) and I-squared statistics.
Results— Five studies met inclusion criteria, representing data from 182 participants. The primary analysis produced a positive overall effect of aerobic exercise on cognitive performance (Hedges’ g [95% confidence interval]= 0.42 [0.007–0.77]). Effects were significantly different from zero for aerobic interventions combined with other physical activity interventions (Hedges’ g [CI] =0.59 [0.26 to 0.92]), but not for aerobic interventions alone (P= 0.40). In specific subdomains, positive moderate effects were found for global cognitive function (Hedges’ g [CI] =0.79 [0.31 to 1.26]) but not for attention and processing speed (P=0.08), executive function (P= 0.84), and working memory (P=0.92).
Conclusions— We determined that aerobic exercise combined with other modes of training produced a significant positive effect on cognition in adults after stroke in the subacute and chronic phases. Our analysis supports the use of combined training as a treatment option to enhance long-term cognitive function in adults after stroke. Further research is needed to determine the efficacy of aerobic training alone.
Chronic diseases place a financial burden on the United States and claim the lives of nearly 2 million Americans every year. Among the chronic diseases that plague American people, type 2 diabetes is particularly prevalent and injurious. Thus, action is warranted to improve prevention and management of this disease. Nutrition plays a significant role in prevention and management of type 2 diabetes and other chronic diseases. Registered dietitians, as nutrition experts, are qualified to use medical nutrition therapy as a method of prevention and treatment for chronic diseases using a nutritional approach. However, there is no consensus as to which eating pattern is the most efficacious. The aim of this review of research was to examine how plant-based eating patterns impact chronic disease conditions, with an emphasis on type 2 diabetes mellitus, as compared to omnivorous eating patterns. A literature search was conducted through the ASU Library, PubMed, and CINAHL using terms related to plant-based diets and chronic diseases, such as type 2 diabetes. The results revealed that a plant-based eating pattern may be beneficial in the prevention and treatment of certain chronic diseases, such as type 2 diabetes. Specifically, adults who have type 2 diabetes and consume a plant-based diet may exhibit enhanced glycemic control as evidenced by less insulin resistance, increased incretin and insulin secretion, greater insulin sensitivity, and improved HbA1c levels. There is sufficient evidence for registered dietitians to recommend a plant-based approach to patients with type 2 diabetes who would like to achieve enhanced glycemic control.
The purpose of this study was to examine the validity of a modified Assisted Cycling Therapy bicycle for improving depression in children with Down Syndrome (DS). Seven participants completed 2x/week for 8 weeks, 30 minutes at a time of ACT, in which participants’ voluntary pedaling rates were augmented via the bicycle motor, ensuring that they were pedaling at a rate greater than their self-paced rate. Depression was measured using a modified version of the Children’s Depressive Inventory, called the CDI-2. Our study demonstrated that the scores from the CDI-2 decreased, demonstrating less depressive symptomatology after the conclusion of the 8 week intervention. Our results were interpreted via our model of the mechanisms involved in influencing the success of ACT. Future research would include a greater sample size, a more relevant measure of depressive scores, and a consistent data collection environment. However our initial pilot study showed promising results for improving mental health in children with DS.
Objective: There were three main objectives of the study. One objective was to elucidate potential new relationships via linear regression. Another objective was to determine which factors were indicative of Type 2 DM in the population. Finally, the last objective was to compare the incidence of Type 2 DM in the dataset to trends seen elsewhere.
Methods: The dataset was uploaded from an open source site with citation onto Python. The dataset, created in 1990, was composed of 768 female patients across 9 different attributes (Number of Pregnancies, Plasma Glucose Levels, Systolic Blood Pressure, Triceps Skin Thickness, Insulin Levels, BMI, Diabetes Pedigree Function, Age and Diabetes Presence (0 or 1)). The dataset was then cleaned using mean or median imputation. Post cleaning, linear regression was done to assess the relationships between certain factors in the population and assessed via the probability statistic for significance, with the exclusion of the Diabetes Pedigree Function and Diabetes Presence. Reverse stepwise logistic regression was used to determine the most pertinent factors for Type 2 DM via the Akaike Information Criterion and through the statistical significance in the model. Finally, data from the Center of Disease Control (CDC) Diabetes Surveillance was assessed for relationships with Female DM Percenatge in Pinal County through Obesity or through Physical Inactivity via simple logistic regression for statistical significance.
Results: The majority of the relationships found were statistically significant with each other. The most pertinent factors of Type 2 DM in the dataset were the number of pregnancies, the plasma glucose levels as well as the Blood Pressure. Via the USDS Data from the CDC, the relationships between Female DM Percentage and the obesity and inactivity percentages were statistically significant.
Conclusion: The trends found in the study matched the trends found in the literature. Per the results, recommendations for better diabetes control include more medical education as well as better blood sugar monitoring.With more analysis, there can be more done for checking other factors such as genetic factors and epidemiological analysis. In conclusion, the study accomplished its main objectives.