Paul Brindley

Outdoor Air Pollution and Stroke in Sheffield, United Kingdom: A Small-Area Level Geographical Study

Background and Purpose— Current evidence suggests that stroke mortality and hospital admissions should be higher in areas with elevated levels of outdoor air pollution because of the combined acute and chronic exposure effects of air pollution. We examined this hypothesis using a small-area level ecological correlation study. Methods— We used 1030 census enumeration districts as the unit of analysis and examined stroke deaths and hospital admissions from 1994 to 1998, with census denominator counts for people ≥45 years. Modeled air pollution data for particulate matter (PM10), nitrogen oxides (NOx), and carbon monoxide (CO) were interpolated to census enumeration districts. We adjusted for age, sex, socioeconomic deprivation, and smoking prevalence. Results— The analysis was based on 2979 deaths, 5122 admissions, and a population of 199 682. After adjustment for potential confounders, stroke mortality was 37% (95% CI, 19 to 57), 33% (95% CI, 14 to 56), and 26% (95% CI, 10 to 46) higher in the highest, relative to the lowest, NOx, PM10, and CO quintile categories, respectively. Corresponding increases in risk for admissions were 13% (95% CI, 1 to 27), 13% (95% CI, −1 to 29), and 11% (95% CI, −1 to 25). Conclusion— The results are consistent with an excess risk of stroke mortality and, to a lesser extent, hospital admissions in areas with high outdoor air pollution levels. If causality were assumed, 11% of stroke deaths would have been attributable to outdoor air pollution. Targeting policy interventions at high pollution areas may be a feasible option for stroke prevention.

The effect of alternative representations of population location on the areal interpolation of air pollution exposure

Abstract Relatively new accurate commercial point databases incorporating population distribution are now available which could enhance areal interpolation estimates required for an underlying population. This paper explores the level to which results will be dependent on how well the underlying population is represented. Using a number of different levels of detail to represent the population distribution (postcode units, enumeration districts (ED) population centroids and no population information), this paper shows the differences that can occur in computing average ED dose levels due to the degree to which the population is represented. Although generally the differing methodologies gave similar overall patterns, there were substantial disparities between specific ED results obtained. As anticipated, the sensitivity of results were influenced by the degree to which the methods assumptions were adhered to. In the case of the ED population centroid approach, the extent to which the summarising points reflect the underlying spatial objects is critical to the estimated result. For areal weighting, the results were significantly influenced by the level of homogeneity within the variable of interest (population distribution). Generally, greater variation within the pollution surface exacerbates any breach in the methods underlying assumptions.

Outdoor NOx and stroke mortality: adjusting for small area level smoking prevalence using a Bayesian approach.

There is increasing evidence, mainly from daily time series studies, linking air pollution and stroke. Small area level geographical correlation studies offer another means of examining the air pollution-stroke association. Populations within small areas may be more homogeneous than those within larger areal units, and census-based socioeconomic information may be available to adjust for confounding effects. Data on smoking from health surveys may be incorporated in spatial analyses to adjust for potential confounding effects but may be sparse at the small area level. Smoothing, using data from neighbouring areas, may be used to increase the precision of smoking prevalence estimates for small areas. We examined the effect of modelled outdoor NOx levels on stroke mortality using a Bayesian hierarchical spatial model to incorporate random effects, in order to allow for unmeasured confounders and to acknowledge sampling error in the estimation of smoking prevalence. We observed an association between NOx and stroke mortality after taking into account random effects at the small area level. We found no association between smoking prevalence and stroke mortality at the small area level after modelling took into account imprecision in estimating smoking prevalence. The approach we used to incorporate smoking as a covariate in a single large model is conceptually sound, though it made little difference to the substantive results.

A data driven approach to mapping urban neighbourhoods

Neighbourhoods have been described by the UK Secretary of State for Communities and Local Government as the building blocks of public service society. Despite this, difficulties in data collection combined with the concepts subjective nature have left most countries lacking official neighbourhood definitions. This issue has implications not only for policy, but for the field of computational social science as a whole (with many studies being forced to use administrative units as proxies despite the fact that these bear little connection to resident perceptions of social boundaries). In this paper we illustrate that the mass linguistic datasets now available on the internet need only be combined with relatively simple linguistic computational models to produce definitions that are not only probabilistic and dynamic, but do not require a priori knowledge of neighbourhood names.

Creating a Corpus of Geospatial Natural Language

The description of location using natural language is of interest for a number of research activities including the automated interpretation and generation of natural language to ease interaction with geographic information systems. For such activities, examples of geospatial natural language are usually collected from the personal knowledge of researchers, or in small scale collection activities specific to the project concerned. This paper describes the process used to develop a more generic corpus of geospatial natural language. n nThe paper discusses the development and evaluation of four methods for semi-automated harvesting of geospatial natural language clauses from text to create a corpus of geospatial natural language. The most successful method uses a set of geospatial syntactic templates that describe common patterns of grammatical geospatial word categories and provide a precision of 0.66. Particular challenges were posed by the range of English dialects included, as well as metaphoric and sporting references.

Generating vague neighbourhoods through data mining of passive web data

ABSTRACT Neighbourhoods have been described as ‘the building blocks of public services society’. Their subjective nature, however, and the resulting difficulties in collecting data, means that in many countries there are no officially defined neighbourhoods either in terms of names or boundaries. This has implications not only for policy but also business and social decisions as a whole. With the absence of neighbourhood boundaries many studies resort to using standard administrative units as proxies. Such administrative geographies, however, often have a poor fit with those perceived by residents. Our approach detects these important social boundaries by automatically mining the Web en masse for passively declared neighbourhood data within postal addresses. Focusing on the United Kingdom (UK), this research demonstrates the feasibility of automated extraction of urban neighbourhood names and their subsequent mapping as vague entities. Importantly, and unlike previous work, our process does not require any neighbourhood names to be established a priori.

Alcohol outlet density and alcohol related hospital admissions in England: a national small-area level ecological study: Alcohol outlet density and hospital admissions

Abstract Background and aims Excessive alcohol consumption has a substantial impact on public health services. A key element determining alcohol availability is alcohol outlet density. This study investigated the relationship between on‐trade and off‐trade outlets and hospital admission rates in local neighbourhoods. Design National small‐area level ecological study. Setting and participants All 32u2009482 lower layer super output census areas (LSOAs) in England (42u2009227u2009108 million people aged 15+ years). Densities for six outlet categories (outlets within a 1‐km radius of residential postcode centroids, averaged for all postcodes within each LSOA) were calculated. Measurements Main outcome measures were admissions due to acute or chronic conditions wholly or partially attributable to alcohol consumption from 2002/03 to 2013/14. Findings There were 1u2009007u2009137 admissions wholly, and 2u2009153u2009874 admissions partially, attributable to alcohol over 12 years. After adjustment for confounding, higher densities of on‐trade outlets (pubs, bars and nightclubs; restaurants licensed to sell alcohol; other on‐trade outlets) and convenience stores were associated with higher admission rate ratios for acute and chronic wholly attributable conditions. For acute wholly attributable conditions, admission rate ratios were 13% (95% confidence interval = 11–15%), 9% (7–10%), 12% (10–14%) and 10% (9–12%) higher, respectively, in the highest relative to the lowest density categories by quartile. For chronic wholly attributable conditions, rate ratios were 22% (21–24%), 9% (7–11%), 19% (17–21%) and 7% (6–9%) higher, respectively. Supermarket density was associated with modestly higher acute and chronic admissions but other off‐trade outlet density was associated only with higher admissions for chronic wholly attributable conditions. For partially attributable conditions, there were no strong patterns of association with outlet densities. Conclusions In England, higher densities of several categories of alcohol outlets appear to be associated with higher hospital admission rates for conditions wholly attributable to alcohol consumption.

Domestic gardens and self-reported health: a national population study

BackgroundThere is a growing recognition of the health benefits of the natural environment. Whilst domestic gardens account for a significant proportion of greenspace in urban areas, few studies, and no population level studies, have investigated their potential health benefits. With gardens offering immediate interaction with nature on our doorsteps, we hypothesise that garden size will affect general health—with smaller domestic gardens associated with poorer health.MethodsA small area ecological design was undertaken using two separate analyses based on data from the 2001 and 2011 UK census. The urban population of England was classified into ‘quintiles’ based on deprivation (Index of Multiple Deprivation) and average garden size (Generalised Land Use Database). Self-reported general health was obtained from the UK population census. We controlled for greenspace exposure, population density, air pollution, house prices, smoking, and geographic location. Models were stratified to explore the associations.ResultsSmaller domestic gardens were associated with a higher prevalence of self-reported poor health. The adjusted prevalence ratio of poor self-reported general health for the quintile with smallest average garden size was 1.13 (95% CI 1.12–1.14) relative to the quintile with the largest gardens. Additionally, the analysis suggested that income-related inequalities in health were greater in areas with smaller gardens. The adjusted prevalence ratio for poor self-reported general health for the most income deprived quintile compared against the least deprived was 1.72 (95% CI 1.64–1.79) in the areas with the smallest gardens, compared to 1.31 (95% CI 1.21–1.42) in areas with the largest gardens.ConclusionsResidents of areas with small domestic gardens have the highest levels of poor health/health inequality related to income deprivation. Although causality needs to be confirmed, the implications for new housing are that adequate garden sizes may be an important means of reducing socioeconomic health inequalities. These findings suggest that the trend for continued urban densification and new housing with minimal gardens could have adverse impacts on health.