Konstantinos Daras

Individual factors explain neighbourhood variations in accidents to children under 5 years of age

Previous studies have identified possible neighbourhood-level influences on the risk of injuries to preschool children, but none have had sufficient data at both household and area level to explain these neighbourhood effects. We used data from the Avon Longitudinal Study of Parents and Children, which recruited over 14,062 children at birth in the former county of Avon, UK, and collected information about accidents, as well as extensive social, health and developmental data throughout the first 5 years of life. This information was combined with census and geographical data in order to identify neighbourhood influences on accident risks and then attempt to explain these using multilevel regression modelling. A small but statistically significant amount of between-neighbourhood variance in accident risk was found, with neighbourhood intraclass correlation coefficients of 0.82% for any accident, and 0.84% for accidents resulting in injury requiring medical attention. This was entirely accounted for by a variety of child, parental and household level variables. Independent risk factors for both outcomes were children who were developmentally more advanced or displayed greater conduct and behavioural problems, mothers who were of younger age, who were without work, who were smokers, whose partners were unemployed or drank alcohol excessively, and households in which there had recently been adverse life events, or which were under financial stress. The mothers perceptions of neighbourhood quality also explained some of the risks for any accident, but not for medically attended accidents, and this was a variable that operated at the level of individual households rather than at the level of neighbourhoods. The implications of this study are that differences in accident risk between neighbourhoods are explained by geographical clustering of similar types of children, families and households. Interventions should focus more on parental factors and household social circumstances than on the physical environment or community based risks. However, many of these factors are those most resistant to modification without broader societal change.

Internal migration around the world: comparing distance travelled and its frictional effect

This paper examines how internal migration distance and its frictional effect vary between countries. Such comparisons are hampered by differences in the number and configuration of spatial units for which data are available − the modifiable area unit problem (MAUP). We use the flexible aggregation routines embedded in the IMAGE Studio, a bespoke software platform which incorporates a spatial interaction model, to elucidate these scale and pattern effects in a set of countries for which finely grained origin-destination matrices are available. We model the relationship between mean migration distance and mean area size and we show that the frictional effect of distance remains remarkably stable across spatial scale, except where zones have small populations and are poorly connected. This stability allows robust comparisons between countries even though zonal systems differ. We find that mean migration distances vary widely, being highest in large, low-density countries and positively associated with urbanisation, HDI and GDP per capita. This suggests a positive link between development and migration distance, paralleling that between development and migration intensity. We find less variation in the beta parameter that measures distance friction but identify clear spatial divisions between more developed countries, with lower friction in larger, less dense countries undergoing rapid population growth.

Developing an openly accessible multi-dimensional small area index of ‘Access to Healthy Assets and Hazards’ for Great Britain, 2016

&NA; Health geographers have been long concerned with understanding how the accessibility of individuals to certain environmental features may influence health and wellbeing. Such insights are increasingly being adopted by policy makers for designing healthy neighbourhoods. To support and inform decision making, there is a need for small area national level data. This paper details the creation of a suite of open access health indicators, including a novel multidimensional index summarising 14 health‐related features of neighbourhoods for Great Britain. We find no association of our overall index with physical health measures, but a significant association to mental wellbeing. HighlightsThere is greater need for open data on health‐related features of neighbourhoods.Designing multi‐dimensional indices can help to describe environments.The overall index is associated with mental wellbeing, but not physical health.The domains of AHAH are consistently associated to our health outcomes.All data are openly available at http://maps.cdrc.ac.uk.