Suchergebnisse

Despite rapid and vast development of wind turbines across the Canadian province of Ontario, there is no map available indicating the location of each wind turbine. A map of this nature is crucial for health and environmental risk research and has many applications in other fields. Research examining health and wind turbines is limited by the available maps showing the nearest community to a wind farm as opposed to each unique wind turbine. Data from provincial-level organizations, developers, and municipalities were collected using government development approval documents, planning documents, and data given directly from municipalities and developers. Wind turbines were mapped using Google Earth, coordinate lists, shapefiles, and translating data from other maps. In total, 1,420 wind turbines were mapped from 56 wind farms. The limitations of each data source and mapping method are discussed. There are numerous challenges in creating a map of this nature, for example incorrect inclusion of wind farms and inaccuracies in wind turbine locations. The resultant map is the first of its kind to be discussed in the literature, can be used for a variety of health and environmental risk studies to assess dose-response, wind turbine density, visibility, and to create sound and vibration models.

This research explores associations between land use types and young offender residential location in the Regional Municipality of York, Ontario, Canada, at a small-area level. Employing a Bayesian spatial modelling approach, we found that after controlling for socio-economic risk factors, proportion of open area land use was positively associated, and road density negatively associated, with residential location of young offenders. Map decomposition, which visualises the contribution of each risk factor to total young offender risk, demonstrated that open area land use contributed more risk in rural areas than urban, and that road density contributed less risk in urban areas than rural. We propose explanations for these results focused on social disorganisation theory and accessibility to structured leisure activities and apply findings to inform law enforcement and land use planning. Results provide a criminological perspective not often considered in planning and urban studies research and contrast land use policies generally motivated by public health and the environment.

BackgroundThe COVID-19 pandemic has resulted in delayed diagnosis and treatment for cancer patients and increases in elective surgery waiting lists. The impact on other 'long-term' conditions (LTCs) is unclear. We examined the effects of the pandemic on the recorded incidence of 20 LTCs to inform decisions on treatment pathways and resource allocation.
ApproachWe included Welsh residents diagnosed with any of 20 LTCs for the first time between 2000-2021.
Data were accessed and analysed within the Secure Anonymised Information Linkage (SAIL) Databank.
The primary aim was to assess the impact of the COVID-19 pandemic on trends in recorded incidence. Secondarily we examined incidence by socio-demographic and clinical subgroups: age, sex, deprivation quintile, ethnicity, frailty score and learning disability.
Incidence were presented as monthly rates for each LTC. We performed interrupted time series analyses to estimate; the immediate and long-term change in rates following the pandemic; and the size of the undiagnosed population.
ResultsWe included 2,206,070 individuals diagnosed with at least one LTC.
An immediate reduction in recording of new diagnoses was observed in April 2020 across all 20 LTCs, followed by a gradual recovery towards pre-pandemic levels over the next 18 months, though at different rates across conditions. The largest difference between observed and expected (as predicted using pre-pandemic trends) incidence between January 2020 and June 2021 were in the diagnoses of COPD (-43%, 95% CI (-50%, -34%)), Asthma, Hypertension and Depression and the smallest difference was in Type 1 diabetes, dementia, stroke and TIA (-8%, 95% CI (-19% ,5%)).
Differences in the proportions of incidence by socio-demographic and clinical subgroups in the years preceding and following the pandemic have also been analysed (results to be finalised).
ConclusionThere was an abrupt reduction in the observed incidence of all 20 LTCs after March 2020 followed by a gradual recovery over consequent months towards pre-pandemic levels. Of 20 LTCs, 15 strongly indicate a reservoir of yet undiagnosed patients. The results from this study will have implications in resource allocation.