Reconsidering movement and exposure: Towards a more dynamic health geography

Acknowledging a paucity of emerging research, and some variation by sub‐field, the geographical measures of exposure used in health and medical geography have largely stagnated often focusing on residence‐based (‘static’) conceptualisations to define an individuals mobility or exposure. Detailed spatiotemporal data, such as smartphone data, allow richer understandings of the influence of the environment, or more broadly of place, on individual health outcomes and behaviours. However, while researchers are increasingly aware of such ‘dynamic’ definitions of place these are seldom employed in empirical evidence. Moreover, there may be differences in mobility by population groups which has not to our knowledge been examined fully. The main aim of this article is to provide a critical review of progress in the conceptualisation of location in health‐related geospatial research to understand the evolution of key concepts and to provoke the reader into considering the utility of a (more) dynamic health geography. We explore the origins of time geography, activity spaces, before moving to recent developments in the area of the exposome and the linked dynamic conceptualisations of exposure in health geography. To illuminate and operationalise findings from our review for readers, we provide a small case study to demonstrate how ‘static’ and ‘dynamic’ approaches differ. Moreover, we consider why understanding heterogeneity in mobility could be particularly salient in the field of health geography, and to the discipline of geography more broadly. To conclude, we help readers understand the practical considerations of data privacy, the process of data collection, data processing, and interpretation, and dissemination of findings to offer practical assistance for those who are grappling with ‘dynamic’ definitions of mobility and conceptualisations of exposure

Accomodation-sharing platforms and small towns in the Covid-19 era

Accommodation-sharing platforms, such as Airbnb, provide the owners of accommodation, including private homes, with the opportunity to offer all or part of their home, or bed space in it, for accommodation-sharing. Accommodationsharing platforms are seen as inherently and deeply disruptive to the conventional accommodation sector and rental markets in many cities and regions worldwide. In regional towns in Aotearoa New Zealand, accommodation sharing is seen as an important part of the total visitor accommodation and an important influence in the rental accommodation and housing markets. The aim of this short field note is to share some thoughts on the planning and the policy implications of Building Better Homes, Towns and Cities National Science Challenge: Ko ngā wā kāinga hei whakamāhorahora research that sought to demonstrate the likely ‘spill-over’ effects of accommodation-sharing on local housing waiting lists and rental prices over time. It draws on insights gleaned from a series of local government workshops focused on accommodation-sharing, and collaboration with the Waitaki Housing Taskforce supporting the development of a district housing strategy

Statin use and association with colorectal cancer survival and risk:Case control study with prescription data linkage

Background: In Scotland colorectal cancer (CRC) is the third most common cancer and a leading cause of cancer death. Epidemiological studies have reported conflicting associations between statins and CRC risk and there is one published report of the association between statins and CRC survival.Methods: Analysis was carried out on 309 cases and 294 controls from the Scottish Study of Colorectal Cancer (SOCCS). Cox's hazard and logistic regression models were applied to investigate the association between statin use and CRC risk and survival.Results: In an adjusted logistic regression model, statins were found to show a statistically significant association for three of the four statin variables and were found to not show a statistically significant association with either all-cause or CRC-specific mortality (OR 0.49; 95%CI 0.49-1.36; p-value = 0.17 and OR 0.33; 95%CI 0.08-1.35; P-value = 0.12, respectively).Conclusion: We did find a statistically significant association between statin intake and CRC risk but not statin intake and CRC-specific mortality. However, the study was insufficiently powered and larger scale studies may be advisable.</p