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Population structure is a confounder on pathways linking genotypes to health outcomes. This study examines whether the historical, geographical origins of British surnames are associated with health outcomes today. We coded hospital admissions of over 30 million patients in England between 1999 and 2013 to their British surname origin and divided their diagnoses into 125 major disease categories (of which 94 were complete-case). A base population was constructed with patients’ first admission of any kind. Age- and sex-standardised odds ratios were calculated with logistic regression using patients with ubiquitous English surnames such as “Smith” as reference (alpha = .05; Benjamini–Hochberg false discovery rate (FDR) = .05). The results were scanned for “signals”, where a branch of related surname origins all had significantly higher or lower risk. Age- and sex-standardised admission (alpha = .05) was calculated for each signal across area deprivation and surname origin density quintiles. Signals included three branches of English surnames (disorders of teeth and jaw, fractures, upper gastrointestinal disorders). Although the signal with fractures was considered unusual overall, 2 out of the 9 origins in the branch would only be significant at a FDR > .05: OR 0.92 (95% confidence interval 0.86–0.98) and 0.70 (0.55–0.90). The risk was only different in the quintile with the highest density of that group. Differential risk remained when studied across quintiles of area deprivation. The study shows that surname origins are associated with diverse health outcomes and thus act as markers of population structure over and above area deprivation.

Empirical analysis of social mobility is typically framed by outcomes recorded for only a single, recent generation, ignoring intergenerational preconditions and historical conferment of opportunity. We use the detailed geography of relative deprivation (hardship) to demonstrate that different family groups today experience different intergenerational outcomes and that there is a distinct Great Britain-wide geography to these inequalities. We trace the evolution of these inequalities back in time by coupling family group level data for the entire Victorian population with a present day population-wide consumer register. Further geographical linkage to neighbourhood deprivation data allows us to chart the different social mobility outcomes experienced by every one of the 13,378 long-established family groups. We identify clear and enduring regional divides in England and Scotland. In substantive terms, use of family names and new historical digital census resources are central to recognising that geography is pivotal to understanding intergenerational inequalities., Intergenerational preconditions and historical conferment of opportunity play a role in social mobility. This study considers the geography of relative deprivation to show how different family groups across Great Britain experience different intergenerational outcomes.

A geodemographic classification provides a set of categorical summaries of the built and socio-economic characteristics of small geographic areas. Many classifications, including that developed in this paper, are created entirely from data extracted from a single decennial census of population. Such classifications are often criticised as becoming less useful over time because of the changing composition of small geographic areas. This paper presents a methodology for exploring the veracity of this assertion, by examining changes in UK census-based geodemographic indicators over time, as well as a substantive interpretation of the overall results. We present an innovative methodology that classifies both 2001 and 2011 census data inputs utilising a unified geography and set of attributes to create a classification that spans both census periods. Through this classification, we examine the temporal stability of the clusters and whether other secondary data sources and internal measures might usefully indicate local uncertainties in such a classification during an intercensal period.

Geodemographics offers the prospects of integrating, modelling and mapping health care needs and other health indicators that are useful for targeting neighbourhoods in public health campaigns. Yet reports about this application domain has to date been sporadic. The purpose of this paper is to examine the potential of a bespoke geodemographic system for neighbourhood targeting in an inner city public health authority, Southwark Primary Care Trust, London. This system, the London Output Area Classification (LOAC), is compared to six other geodemographic systems from both governmental and commercial sources. The paper proposes two new indicators for assessing the performance of geodemographic systems for neighbourhood targeting based on local hospital demand data. The paper also analyses and discusses the utility of age- and sex standardisation of geodemographic profiles of health care demand.

This paper begins by reviewing the ways in which the innovation of Google Maps has transformed our ability to reference and view geographically referenced data. We describe the ways in which the GMap Creator tool developed under the ESRC National Centre for e Social Science (NCeSS) programme enables users to ‘mashup’ thematic choropleth maps using the Google API. We illustrate the application of GMap Creator using the example of www.londonprofiler.org, which presents a repository of choropleth maps across a range of domains including health, education and other socioeconomic datasets against a backcloth of Google Maps data. Our conclusions address the ways in which Google Map mashups developed using GMap Creator facilitate online exploratory cartographic visualisation in a range of areas of policy concern.

The success of GIS has in some ways proved to be a mixed blessing to academic geography. While quantitative geography has developed as a disciplinary specialism over a long period of time, the infusion of GIS has been more rapid and applications-led. Geography has been a consumer, not producer, of mainstream GIS software, and as such GIS may even contribute towards accelerated de-skilling of the discipline. The technology nevertheless provides a crucial means of dealing with the current proliferation of digital data, and has important implications for the future development of geography.

This paper introduces the mechanism of diffusion-limited aggregation (DLA) as a new basis for understanding urban growth. Through DLA, urban form is related to the processes of rural-to-urban migration and contiguous growth. However, despite being based on very simple principles, DLA simulations are shown to have properties found in most urban areas such as negative density gradients and ordered chaotic structures. The paper examines variations in the simulated urban structures produced by different assumptions regarding the rural-to-urban migration mechanism. An important finding is that urban density gradients can occur independently of the generally accepted reasons for their presence. We also comment on boundary effects in the measurement of urban density gradients.