Search

Background: While studying the etiology of multiple sclerosis (MS) in children has several methodological advantages over studying etiology in adults, studies are limited by small sample sizes. Objective: Using a rigorous methodological process, we developed the Pediatric MS Tool-Kit, a measurement framework that includes a minimal set of core variables to assess etiological risk factors. Methods: We solicited input from the International Pediatric MS Study Group to select three risk factors: environmental tobacco smoke (ETS) exposure, sun exposure, and vitamin D intake. To develop the Tool-Kit, we used a Delphi study involving a working group of epidemiologists, neurologists, and content experts from North America and Europe. Results: The Tool-Kit includes six core variables to measure ETS, six to measure sun exposure, and six to measure vitamin D intake. The Tool-Kit can be accessed online (www.maelstrom-research.org/mica/network/tool-kit). Conclusion: The goals of the Tool-Kit are to enhance exposure measurement in newly designed pediatric MS studies and comparability of results across studies, and in the longer term to facilitate harmonization of studies, a methodological approach that can be used to circumvent issues of small sample sizes. We believe the Tool-Kit will prove to be a valuable resource to guide pediatric MS researchers in developing study-specific questionnaire [ABSTRACT FROM AUTHOR]

Background: Urbanization and ageing have important implications for public mental health and well-being. Cities pose major challenges for older citizens, but also offer opportunities to develop, test, and implement policies, services, infrastructure, and interventions that promote mental well-being. The MINDMAP project aims to identify the opportunities and challenges posed by urban environmental characteristics for the promotion and management of mental well-being and cognitive function of older individuals.Methods: MINDMAP aims to achieve its research objectives by bringing together longitudinal studies from 11 countries covering over 35 cities linked to databases of area-level environmental exposures and social and urban policy indicators. The infrastructure supporting integration of this data will allow multiple MINDMAP investigators to safely and remotely co-analyse individual-level and area-level data. Individual-level data is derived from baseline and follow-up measurements of ten participating cohort studies and provides information on mental well-being outcomes, sociodemographic variables, health behaviour characteristics, social factors, measures of frailty, physical function indicators, and chronic conditions, as well as blood derived clinical biochemistry-based biomarkers and genetic biomarkers. Area-level information on physical environment characteristics (e.g. green spaces, transportation), socioeconomic and sociodemographic characteristics (e.g. neighbourhood income, residential segregation, residential density), and social environment characteristics (e.g. social cohesion, criminality) and national and urban social policies is derived from publically available sources such as geoportals and administrative databases. The linkage, harmonization, and analysis of data from different sources are being carried out using piloted tools to optimize the validity of the research results and transparency of the methodology.Discussion: MINDMAP is a novel research collaboration that is combining population-based cohort data with publicly available datasets not typically used for ageing and mental well-being research. Integration of various data sources and observational units into a single platform will help to explain the differences in ageing-related mental and cognitive disorders both within as well as between cities in Europe, the US, Canada, and Russia and to assess the causal pathways and interactions between the urban environment and the individual determinants of mental well-being and cognitive ageing in older adults. [ABSTRACT FROM AUTHOR]

Background: Individual-level data pooling of large population-based studies across research centres in international research projects faces many hurdles. The BioSHaRE (Biobank Standardisation and Harmonisation for Research Excellence in the European Union) project aims to address these issues by building a collaborative group of investigators and developing tools for data harmonization, database integration and federated data analyses. Methods: Eight population-based studies in six European countries were recruited to participate in the BioSHaRE project. Through workshops, teleconferences and electronic communications, participating investigators identified a set of 96 variables targeted for harmonization to answer research questions of interest. Using each study's questionnaires, standard operating procedures, and data dictionaries, harmonization potential was assessed. Whenever harmonization was deemed possible, processing algorithms were developed and implemented in an open-source software infrastructure to transform study-specific data into the target (i.e. harmonized) format. Harmonized datasets located on server in each research centres across Europe were interconnected through a federated database system to perform statistical analysis. Results: Retrospective harmonization led to the generation of common format variables for 73% of matches considered (96 targeted variables across 8 studies). Authenticated investigators can now perform complex statistical analyses of harmonized datasets stored on distributed servers without actually sharing individual-level data using the DataSHIELD method. Conclusion: New Internet-based networking technologies and database management systems are providing the means to support collaborative, multi-center research in an efficient and secure manner. The results from this pilot project show that, given a strong collaborative relationship between participating studies, it is possible to seamlessly co-analyse internationally harmonized research databases while allowing each study to retain full control over individual-level data. We encourage additional collaborative research networks in epidemiology, public health, and the social sciences to make use of the open source tools presented herein. [ABSTRACT FROM AUTHOR]

Background: While studying the etiology of multiple sclerosis (MS) in children has several methodological advantages over studying etiology in adults, studies are limited by small sample sizes., Objective: Using a rigorous methodological process, we developed the Pediatric MS Tool-Kit, a measurement framework that includes a minimal set of core variables to assess etiological risk factors., Methods: We solicited input from the International Pediatric MS Study Group to select three risk factors: environmental tobacco smoke (ETS) exposure, sun exposure, and vitamin D intake. To develop the Tool-Kit, we used a Delphi study involving a working group of epidemiologists, neurologists, and content experts from North America and Europe., Results: The Tool-Kit includes six core variables to measure ETS, six to measure sun exposure, and six to measure vitamin D intake. The Tool-Kit can be accessed online ( www.maelstrom-research.org/mica/network/tool-kit )., Conclusion: The goals of the Tool-Kit are to enhance exposure measurement in newly designed pediatric MS studies and comparability of results across studies, and in the longer term to facilitate harmonization of studies, a methodological approach that can be used to circumvent issues of small sample sizes. We believe the Tool-Kit will prove to be a valuable resource to guide pediatric MS researchers in developing study-specific questionnaire.