181 research outputs found

    Winnipeg Quality of Life Project Phase One Report

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    This project addresses the lack of neighbourhood statistical data and survey information on the quality of life in the inner city available to community groups. Many organizations and individuals in Winnipeg’s inner city are working to enhance individual quality of life in the inner city and to raise the standard of living. However, there is no adequate way, at this time, to measure change occurring in neighbourhoods. Inner city organizations and larger governmental and non-governmental organizations collect data useful to measure outcomes of specific programs and general social trends; unfortunately these data and the survey instruments used are not standardized between organizations. It is difficult to use these data when measuring the community-wide impacts of programs, perceptions of residents, and the social or economic progress of neighbourhoods and communities

    Linking Canadian Administrative Data: Income Trajectories, Residential and School Mobility, and Grade 3 Academic Achievement.

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    Objective The objective is to examine the association between trajectories of childhood residential and school mobility and academic achievement (literacy, numeracy) in Grade 3 using linked whole-population administrative data in Manitoba, Canada. Secondarily, we assessed childhood residential/school mobility based on neighbourhood income levels (moving in/out of low- or mid-/high-income neighbourhoods). Approach This retrospective cohort study used linkable, de-identified administrative data (health, education, national census, provincial survey) from the provincial Population Research Data Repository housed at the Manitoba Centre for Health Policy (MCHP). Among kindergarteners from 2005 to 2014 (n = 83,894), those not having continuous residency in Manitoba, valid education assessments, and relevant family-level covariates were excluded. We followed this eligible cohort from kindergarten to Grade 3 based on various neighbourhood income trajectories of residential and school mobility. To assess Grade 3 literacy and numeracy scores based on trajectories, log-binomial regression models were conducted using SAS® version 9.4. Results The total cohort included 36,754 children; at the end of kindergarten, 14.2% resided in low-income neighbourhoods, and 84.8% lived in mid-/high-income neighbourhoods. Moving between two low-income neighborhoods between kindergarten to Grade 3 was associated with an increased risk of poor Grade 3 numeracy and literacy scores (numeracy aRR=1.39 [1.16,1.67]; literacy aRR=1.31 [1.08,1.59]). When moving between neighborhood income levels, the association was stronger for children moving into low-income neighbourhoods (e.g., mid-/high-income to low-income: numeracy aRR=1.41 [1.19,1.67]) than children moving into mid/high-income neighbourhoods (e.g., low-income to mid-/high-income: numeracy aRR=1.31 [1.08,1.59]). Changing schools between kindergarten and Grade 3 was also associated with poorer numeracy and literacy scores in Grade 3 (numeracy aRR=1.31 [1.22,1.40]; literacy aRR=1.34 [1.24,1.44]); however, the strength varied based on residential mobility patterns. Conclusion Moving homes/schools can differentially impact children’s educational attainment depending upon the income level of residing neighborhood(s). Stakeholders should recognize different levels of risks related to mobility and provide support accordingly to reduce the adverse impact. Support systems should be tailored to not only children but also families and neighbourhoods

    Translating the Knowledge Gap Between Researchers and Communication Designers for Improved mHealth Research

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    Our industry insight focuses on the challenges for health researchers collaborating with communication designers during the development of an App for improving maternal mental health and parenting stress. We discuss the challenges around explicating and communicating tacit and domain knowledge across disciplinary boundaries. We believe this report can widen communication design’s traditional focus on users in mHealth research to consider partnerships with academic researchers. The lessons learned from our experience developing a mHealth program can be used to reduce challenges in future mHealth research, especially for collaborations between health researchers and communications designers. Considering the growth of interest in mHealth, this is extremely relevant for future team satisfaction, the optimal use of research funds and industry time, and faster development of effective mHealth tools.This is the accepted manuscript version of the following publication: Rioux, C., Weedon, S., MacKinnon, A. L., Watts, D., Salisbury, M. R., Penner-Goeke, L., Simpson, K. M., Harrington, J., Tomfohr-Madsen, L. M. & Roos, L. E. (2022). Translating the Knowledge Gap Between Researchers and Communication Designers for Improved mHealth Research. SIGDOC '22: The 40th ACM International Conference on Design of Communication, USA, 157–160. doi: 10.1145/3513130.3558997BEAM was funded by a Research Manitoba COVID-19 Rapid Response Operating Grant. CR was supported by a Postdoctoral fellowship from Research Manitoba and the Children’s Hospital Foundation of Manitoba. ALM was supported by a Social Sciences & Humanities Research Council (SSHRC) Banting Postdoctoral Fellowship (#01353-000).Ye

    Influenza Vaccine Effectiveness in the Elderly Based on Administrative Databases: Change in Immunization Habit as a Marker for Bias

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    Administrative databases provide efficient methods to estimate influenza vaccine effectiveness (IVE) against severe outcomes in the elderly but are prone to intractable bias. This study returns to one of the linked population databases by which IVE against hospitalization and death in the elderly was first assessed. We explore IVE across six more recent influenza seasons, including periods before, during, and after peak activity to identify potential markers for bias.Acute respiratory hospitalization and all-cause mortality were compared between immunized/non-immunized community-dwelling seniors ≥65 years through administrative databases in Manitoba, Canada between 2000-01 and 2005-06. IVE was compared during pre-season/influenza/post-season periods through logistic regression with multivariable adjustment (age/sex/income/residence/prior influenza or pneumococcal immunization/medical visits/comorbidity), stratification based on prior influenza immunization history, and propensity scores. Analysis during pre-season periods assessed baseline differences between immunized and unimmunized groups. The study population included ∼140,000 seniors, of whom 50-60% were immunized annually. Adjustment for key covariates and use of propensity scores consistently increased IVE. Estimates were paradoxically higher pre-season and for all-cause mortality vs. acute respiratory hospitalization. Stratified analysis showed that those twice consecutively and currently immunized were always at significantly lower hospitalization/mortality risk with odds ratios (OR) of 0.60 [95%CI0.48-0.75] and 0.58 [0.53-0.64] pre-season and 0.77 [0.69-0.86] and 0.71 [0.66-0.77] during influenza circulation, relative to the consistently unimmunized. Conversely, those forgoing immunization when twice previously immunized were always at significantly higher hospitalization/mortality risk with OR of 1.41 [1.14-1.73] and 2.45 [2.21-2.72] pre-season and 1.21 [1.03-1.43] and 1.78 [1.61-1.96] during influenza circulation.The most pronounced IVE estimates were paradoxically observed pre-season, indicating bias tending to over-estimate vaccine protection. Change in immunization habit from that of the prior two years may be a marker for this bias in administrative data sets; however, no analytic technique explored could adjust for its influence. Improved methods to achieve valid interpretation of protection in the elderly are needed

    A Meta-analysis of Multiple Myeloma Risk Regions in African and European Ancestry Populations Identifies Putatively Functional Loci

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    Genome-wide association studies (GWAS) in European populations have identified genetic risk variants associated with multiple myeloma (MM)
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