Prevalence of Risk Factors for Non-Communicable Diseases for New Patients Reporting to Korle-Bu Teaching Hospital

Background: The risk factors of Noncommunicable diseases (NCDs) are not routinely monitored, especially among populace reporting to hospitals to detect and also advise on preventive measures, a key strategy to reducing the impact of NCDs on the Health Care System and population.Methods: A cross-sectional survey was carried out between the months of May and June, 2010 among a sample representative of the medical and surgical out-patients population to determine the prevalence of certain risk factors of non-communicable diseases (NCDs). Participants (n = 230) were selected by systematic random sampling. Standardised international protocols were used to measure the prevalence of smoking, alcohol consumption, physical inactivity, obesity, raised blood pressure, raised blood glucose and total cholesterol.Results: The obesity level of the study population was 40.4% with 54% being overweight. Tobacco use among the respondents was 4.8%. Alcohol consumption was 64.8%, with 54.3% of the study population being physically inactive. Almost 48%and 70.9% of the participants consumed fruits and vegetables respectively, at least three days in a week. The prevalence of hypertension was 33.6% for men and 35.2% for women. The prevalence of raised glucose and total blood cholesterol level among the study population was 6.5%. Almost 62% of the participants had a combination of three or more risk factors.Conclusion: The prevalence of the significant risk factors in this study were physical inactivity (54.3%), alcohol consumption (64.8%), overweight (54%), obesity (40.4%) and raised blood pressure (34.3%). Hospitals should therefore include NCD risk factor monitoring as part of routine services.Keywords: Non-communicable disease, obesity, blood pressure, blood sugar, blood cholesterol, physical inactivity, Korle-Bu Teaching Hospita

Understanding young adult physical activity, alcohol and tobacco use in community colleges and 4-year post-secondary institutions: A cross-sectional analysis of epidemiological surveillance data

<p>Abstract</p> <p>Background</p> <p>Young adults experience many adverse health behavior changes as they transition from adolescence into adulthood. A better understanding of the relationships between health promoting and risky health behaviors may aid in the development of health promotion interventions for various types of young adult post-secondary students. Therefore, the purpose of this study was to examine associations between alcohol and tobacco use and physical activity among 2-year and 4-year college students.</p> <p>Methods</p> <p>Cross-sectional analyses were conducted using 2007 survey data, collected as part of an on-going post-secondary health surveillance system in Minnesota. Students were randomly selected to participant from 14 Minnesota colleges and universities (six 2-year community and/or technical colleges, eight 4-year post-secondary institutions). The 2007 surveillance data included 9,931 respondents.</p> <p>Results</p> <p>The prevalence of demographic characteristics and health behaviors (e.g., physical activity, tobacco use) differed between young adults attending 2-year and 4-year post-secondary institutions; in general, those attending 2-year institutions are representative of more at-risk populations. Overall, higher levels of moderate, vigorous and strengthening physical activity were associated with higher levels of alcohol consumption and lower levels of smoking. In general, despite the disparities in the prevalence of these risk behaviors, the associations between the behaviors did not differ substantially between 2-year and 4-year post-secondary populations.</p> <p>Conclusions</p> <p>These findings illustrate links between leading risk behaviors. Interventions targeting multiple risk behaviors among young adults may warrant further consideration. Overall, future research is needed to support and inform young adult health promotion efforts that may be implemented in a wide array of post-secondary institutions.</p

Branch Mode Selection during Early Lung Development

Many organs of higher organisms, such as the vascular system, lung, kidney, pancreas, liver and glands, are heavily branched structures. The branching process during lung development has been studied in great detail and is remarkably stereotyped. The branched tree is generated by the sequential, non-random use of three geometrically simple modes of branching (domain branching, planar and orthogonal bifurcation). While many regulatory components and local interactions have been defined an integrated understanding of the regulatory network that controls the branching process is lacking. We have developed a deterministic, spatio-temporal differential-equation based model of the core signaling network that governs lung branching morphogenesis. The model focuses on the two key signaling factors that have been identified in experiments, fibroblast growth factor (FGF10) and sonic hedgehog (SHH) as well as the SHH receptor patched (Ptc). We show that the reported biochemical interactions give rise to a Schnakenberg-type Turing patterning mechanisms that allows us to reproduce experimental observations in wildtype and mutant mice. The kinetic parameters as well as the domain shape are based on experimental data where available. The developed model is robust to small absolute and large relative changes in the parameter values. At the same time there is a strong regulatory potential in that the switching between branching modes can be achieved by targeted changes in the parameter values. We note that the sequence of different branching events may also be the result of different growth speeds: fast growth triggers lateral branching while slow growth favours bifurcations in our model. We conclude that the FGF10-SHH-Ptc1 module is sufficient to generate pattern that correspond to the observed branching modesComment: Initially published at PLoS Comput Bio

Early Antenatal Prediction of Gestational Diabetes in Obese Women: Development of Prediction Tools for Targeted Intervention.

All obese women are categorised as being of equally high risk of gestational diabetes (GDM) whereas the majority do not develop the disorder. Lifestyle and pharmacological interventions in unselected obese pregnant women have been unsuccessful in preventing GDM. Our aim was to develop a prediction tool for early identification of obese women at high risk of GDM to facilitate targeted interventions in those most likely to benefit. Clinical and anthropometric data and non-fasting blood samples were obtained at 15+0-18+6 weeks' gestation in 1303 obese pregnant women from UPBEAT, a randomised controlled trial of a behavioural intervention. Twenty one candidate biomarkers associated with insulin resistance, and a targeted nuclear magnetic resonance (NMR) metabolome were measured. Prediction models were constructed using stepwise logistic regression. Twenty six percent of women (n = 337) developed GDM (International Association of Diabetes and Pregnancy Study Groups criteria). A model based on clinical and anthropometric variables (age, previous GDM, family history of type 2 diabetes, systolic blood pressure, sum of skinfold thicknesses, waist:height and neck:thigh ratios) provided an area under the curve of 0.71 (95%CI 0.68-0.74). This increased to 0.77 (95%CI 0.73-0.80) with addition of candidate biomarkers (random glucose, haemoglobin A1c (HbA1c), fructosamine, adiponectin, sex hormone binding globulin, triglycerides), but was not improved by addition of NMR metabolites (0.77; 95%CI 0.74-0.81). Clinically translatable models for GDM prediction including readily measurable variables e.g. mid-arm circumference, age, systolic blood pressure, HbA1c and adiponectin are described. Using a ≥35% risk threshold, all models identified a group of high risk obese women of whom approximately 50% (positive predictive value) later developed GDM, with a negative predictive value of 80%. Tools for early pregnancy identification of obese women at risk of GDM are described which could enable targeted interventions for GDM prevention in women who will benefit the most

Boosting Long-term Memory via Wakeful Rest: Intentional Rehearsal is not Necessary, Automatic Consolidation is Sufficient.

<div><p>People perform better on tests of delayed free recall if learning is followed immediately by a short wakeful rest than by a short period of sensory stimulation. Animal and human work suggests that wakeful resting provides optimal conditions for the consolidation of recently acquired memories. However, an alternative account cannot be ruled out, namely that wakeful resting provides optimal conditions for intentional rehearsal of recently acquired memories, thus driving superior memory. Here we utilised non-recallable words to examine whether wakeful rest boosts long-term memory, even when new memories could not be rehearsed intentionally during the wakeful rest delay. The probing of non-recallable words requires a recognition paradigm. Therefore, we first established, via Experiment 1, that the rest-induced boost in memory observed via free recall can be replicated in a recognition paradigm, using concrete nouns. In Experiment 2, participants heard 30 non-recallable non-words, presented as ‘foreign names in a bridge club abroad’ and then either rested wakefully or played a visual spot-the-difference game for 10 minutes. Retention was probed via recognition at two time points, 15 minutes and 7 days after presentation. As in Experiment 1, wakeful rest boosted recognition significantly, and this boost was maintained for at least 7 days. Our results indicate that the enhancement of memory via wakeful rest is <i>not</i> dependent upon intentional rehearsal of learned material during the rest period. We thus conclude that consolidation is <i>sufficient</i> for this rest-induced memory boost to emerge. We propose that wakeful resting allows for superior memory consolidation, resulting in stronger and/or more veridical representations of experienced events which can be detected via tests of free recall and recognition.</p></div

Organizational factors and depression management in community-based primary care settings

Abstract Background Evidence-based quality improvement models for depression have not been fully implemented in routine primary care settings. To date, few studies have examined the organizational factors associated with depression management in real-world primary care practice. To successfully implement quality improvement models for depression, there must be a better understanding of the relevant organizational structure and processes of the primary care setting. The objective of this study is to describe these organizational features of routine primary care practice, and the organization of depression care, using survey questions derived from an evidence-based framework. Methods We used this framework to implement a survey of 27 practices comprised of 49 unique offices within a large primary care practice network in western Pennsylvania. Survey questions addressed practice structure (e.g., human resources, leadership, information technology (IT) infrastructure, and external incentives) and process features (e.g., staff performance, degree of integrated depression care, and IT performance). Results The results of our survey demonstrated substantial variation across the practice network of organizational factors pertinent to implementation of evidence-based depression management. Notably, quality improvement capability and IT infrastructure were widespread, but specific application to depression care differed between practices, as did coordination and communication tasks surrounding depression treatment. Conclusions The primary care practices in the network that we surveyed are at differing stages in their organization and implementation of evidence-based depression management. Practical surveys such as this may serve to better direct implementation of these quality improvement strategies for depression by improving understanding of the organizational barriers and facilitators that exist within both practices and practice networks. In addition, survey information can inform efforts of individual primary care practices in customizing intervention strategies to improve depression management.http://deepblue.lib.umich.edu/bitstream/2027.42/78269/1/1748-5908-4-84.xmlhttp://deepblue.lib.umich.edu/bitstream/2027.42/78269/2/1748-5908-4-84-S1.PDFhttp://deepblue.lib.umich.edu/bitstream/2027.42/78269/3/1748-5908-4-84.pdfPeer Reviewe

A characteristics framework for Semantic Information Systems Standards

Semantic Information Systems (IS) Standards play a critical role in the development of the networked economy. While their importance is undoubted by all stakeholders—such as businesses, policy makers, researchers, developers—the current state of research leaves a number of questions unaddressed. Terminological confusion exists around the notions of “business semantics”, “business-to-business interoperability”, and “interoperability standards” amongst others. And, moreover, a comprehensive understanding about the characteristics of Semantic IS Standards is missing. The paper addresses this gap in literature by developing a characteristics framework for Semantic IS Standards. Two case studies are used to check the applicability of the framework in a “real-life” context. The framework lays the foundation for future research in an important field of the IS discipline and supports practitioners in their efforts to analyze, compare, and evaluate Semantic IS Standard