Is there an association between spatial access to parks/green space and childhood overweight/obesity in Calgary, Canada?

<p>Abstract</p> <p>Background</p> <p>The recent increase in childhood obesity is expected to add significantly to the prevalence of chronic diseases. We used multivariate multilevel analysis to examine associations between parks/green space and childhood overweight/obesity across communities in Calgary, Canada, a city characterized by intensified urban sprawl and high car use.</p> <p>Methods</p> <p>Body Mass Index was calculated from measured height and weight data obtained from 6,772 children (mean age = 4.95 years) attending public health clinics for pre-school vaccinations. Each child's home postal code was geocoded using ESRI ArcGIS 9.2. We examined four measures of spatial access to parks/green space (based on Geographic Information Systems): 1) the number of parks/green spaces per 10,000 residents, 2) the area of parks/green space as a proportion of the total area within a community, 3) average distance to a park/green space, and 4) the proportion of parks/green space service area as a proportion of the total area within a community. Analyses were adjusted for dissemination area median family income (as a proxy for an individual child's family income) community-level education, and community-level proportion of visible minorities.</p> <p>Results</p> <p>In general, parks/green space at the community level was not associated with overweight/obesity in Calgary, with the exception of a marginally significant effect whereby a moderate number of parks/green spaces per 10,000 residents was associated with lower odds of overweight/obesity. This effect was non-significant in adjusted analyses.</p> <p>Conclusion</p> <p>Our null findings may reflect the popularity of car travel in Calgary, Canada and suggest that the role built environment characteristics play in explaining health outcomes may differ depending on the type of urban environment being studied.</p

Action Planning for Daily Mouth Care in Long-Term Care: The Brushing Up on Mouth Care Project

Research focusing on the introduction of daily mouth care programs for dependent older adults in long-term care has met with limited success. There is a need for greater awareness about the importance of oral health, more education for those providing oral care, and organizational structures that provide policy and administrative support for daily mouth care. The purpose of this paper is to describe the establishment of an oral care action plan for long-term care using an interdisciplinary collaborative approach. Methods. Elements of a program planning cycle that includes assessment, planning, implementation, and evaluation guided this work and are described in this paper. Findings associated with assessment and planning are detailed. Assessment involved exploration of internal and external factors influencing oral care in long-term care and included document review, focus groups and one-on-one interviews with end-users. The planning phase brought care providers, stakeholders, and researchers together to design a set of actions to integrate oral care into the organizational policy and practice of the research settings. Findings. The establishment of a meaningful and productive collaboration was beneficial for developing realistic goals, understanding context and institutional culture, creating actions suitable and applicable for end-users, and laying a foundation for broader networking with relevant stakeholders and health policy makers

Optimising medication data collection in a large-scale clinical trial

© 2019 Lockery et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Objective: Pharmaceuticals play an important role in clinical care. However, in community-based research, medication data are commonly collected as unstructured free-text, which is prohibitively expensive to code for large-scale studies. The ASPirin in Reducing Events in the Elderly (ASPREE) study developed a two-pronged framework to collect structured medication data for 19,114 individuals. ASPREE provides an opportunity to determine whether medication data can be cost-effectively collected and coded, en masse from the community using this framework. Methods: The ASPREE framework of type-to-search box with automated coding and linked free text entry was compared to traditional method of free-text only collection and post hoc coding. Reported medications were classified according to their method of collection and analysed by Anatomical Therapeutic Chemical (ATC) group. Relative cost of collecting medications was determined by calculating the time required for database set up and medication coding. Results Overall, 122,910 participant structured medication reports were entered using the type-tosearch box and 5,983 were entered as free-text. Free-text data contributed 211 unique medications not present in the type-to-search box. Spelling errors and unnecessary provision of additional information were among the top reasons why medications were reported as freetext. The cost per medication using the ASPREE method was approximately USD $0.03 compared with USD$0.20 per medication for the traditional method. Conclusion Implementation of this two-pronged framework is a cost-effective alternative to free-text only data collection in community-based research. Higher initial set-up costs of this combined method are justified by long term cost effectiveness and the scientific potential for analysis and discovery gained through collection of detailed, structured medication data

Design and development of the Australian and New Zealand (ANZ) myeloma and related diseases registry

© 2016 The Author(s). Background: Plasma cell dyscrasias (PCD) are a spectrum of disorders resulting from the clonal expansion of plasma cells, ranging from the pre-malignant condition monoclonal gammopathy of undetermined significance (MGUS) to multiple myeloma (MM). MM generates a significant burden of disease on the community and it is predicted that it will increase in both incidence and prevalence owing to an ageing population and longer survival secondary to new therapeutic options. Robust and comprehensive clinical data are currently lacking but are required to define current diagnostic, investigational and management patterns in Australia and New Zealand (ANZ) for comparison to both local and international guidelines for standards of care. A clinical registry can provide this information and subsequently support development of strategies to address any differences, including providing a platform for clinical trials. The Myeloma and Related Diseases Registry (MRDR) was developed to monitor and explore variations in practices, processes and outcomes in ANZ and provide benchmark outcomes nationally and internationally for PCD. This paper describes the MRDR aims, development and implementation and discusses challenges encountered in the process. Methods: The MRDR was established in 2012 as an online database for a multi-centre collaboration across ANZ, collecting prospective data on patients with a diagnosis of MGUS, MM, solitary plasmacytoma or plasma cell leukaemia. Development of the MRDR required multi-disciplinary team participation, IT and biostatistical support as well as financial resources. Results: More than 1250 patients have been enrolled at 23 sites to date. Here we describe how database development, data entry and securing ethics approval have been major challenges for participating sites and the coordinating centre, and our approaches to resolving them. Now established, the MRDR will provide clinically relevant and credible monitoring, therapy and 'real world' outcome data, to support the conduction of high quality studies. In addition, the Myeloma 1000 sub-study is establishing a repository of paired peripheral blood specimens from registry patients to study mechanisms underlying disease progression. Conclusion: Establishment of the MRDR has been challenging, but it is a valuable investment that will provide a platform for coordinated national and international collaboration for clinical research in PCD in ANZ

Overcoming challenges to data quality in the ASPREE clinical trial

© 2019 The Author(s). Background: Large-scale studies risk generating inaccurate and missing data due to the complexity of data collection. Technology has the potential to improve data quality by providing operational support to data collectors. However, this potential is under-explored in community-based trials. The Aspirin in reducing events in the elderly (ASPREE) trial developed a data suite that was specifically designed to support data collectors: the ASPREE Web Accessible Relational Database (AWARD). This paper describes AWARD and the impact of system design on data quality. Methods: AWARD's operational requirements, conceptual design, key challenges and design solutions for data quality are presented. Impact of design features is assessed through comparison of baseline data collected prior to implementation of key functionality (n = 1000) with data collected post implementation (n = 18,114). Overall data quality is assessed according to data category. Results: At baseline, implementation of user-driven functionality reduced staff error (from 0.3% to 0.01%), out-of-range data entry (from 0.14% to 0.04%) and protocol deviations (from 0.4% to 0.08%). In the longitudinal data set, which contained more than 39 million data values collected within AWARD, 96.6% of data values were entered within specified query range or found to be accurate upon querying. The remaining data were missing (3.4%). Participant non-attendance at scheduled study activity was the most common cause of missing data. Costs associated with cleaning data in ASPREE were lower than expected compared with reports from other trials. Conclusions: Clinical trials undertake complex operational activity in order to collect data, but technology rarely provides sufficient support. We find the AWARD suite provides proof of principle that designing technology to support data collectors can mitigate known causes of poor data quality and produce higher-quality data. Health information technology (IT) products that support the conduct of scheduled activity in addition to traditional data entry will enhance community-based clinical trials. A standardised framework for reporting data quality would aid comparisons across clinical trials

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