Ethnic inequalities in hospital admissions in England: an observational study.

BACKGROUND: Ethnic inequalities in health are well-known and partly explained by social determinants such as poorer living and working conditions, health behaviours, discrimination, social exclusion, and healthcare accessibility factors. Inequalities are known both for self-reported health and for diseases such as diabetes, cardiovascular diseases, respiratory diseases, and non-specific chest pains. Most studies however concern individual diseases or self-reported health and do not provide an overview that can detect gaps in existing knowledge. The aim of this study is thus to identify ethnic inequalities in inpatient hospital admission for all major disease categories in England. METHODS: Observational study of the inpatient hospital admission database in England enhanced with ethnicity coding of participants' surnames. The primary diagnosis was coded to Level 1 of the Global Burden of Disease groups. For each year, only the first admission for each condition for each participant was included. If a participant was readmitted within two days only the first admission was counted. Admission risk for all major disease groups for each ethnic group relative to the White British group were calculated using logistic regression adjusting for age and area deprivation. RESULTS: 40,928,105 admissions were identified between April 2009 and March 2014. Ethnic inequalities were found in cardiovascular diseases, respiratory diseases, chest pain, and diabetes in line with previous studies. Additional inequalities were found in nutritional deficiencies, endocrine disorders, and sense organ diseases. CONCLUSIONS: The results of this study were consistent with known inequalities, but also found previously unreported disparities in nutritional deficiencies, endocrine disorders, and sense organ diseases. Further studies would be required to map out the relevant care pathways for ethnic minorities and establish whether preventive measures can be strengthened.

Regional surnames and genetic structure in Great Britain.

Following the increasing availability of DNA-sequenced data, the genetic structure of populations can now be inferred and studied in unprecedented detail. Across social science, this innovation is shaping new bio-social research agendas, attracting substantial investment in the collection of genetic, biological and social data for large population samples. Yet genetic samples are special because the precise populations that they represent are uncertain and ill-defined. Unlike most social surveys, a genetic sample's representativeness of the population cannot be established by conventional procedures of statistical inference, and the implications for population-wide generalisations about bio-social phenomena are little understood. In this paper, we seek to address these problems by linking surname data to a censored and geographically uneven sample of DNA scans, collected for the People of the British Isles study. Based on a combination of global and local spatial correspondence measures, we identify eight regions in Great Britain that are most likely to represent the geography of genetic structure of Great Britain's long-settled population. We discuss the implications of this regionalisation for bio-social investigations. We conclude that, as the often highly selective collection of DNA and biomarkers becomes a more common practice, geography is crucial to understanding variation in genetic information within diverse populations.

British surname origins, population structure and health outcomes-an observational study of hospital admissions.

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.

Delineating Europe's cultural regions: population structure and surname clustering.

Surnames (family names) show distinctive geographical patterning and in many disciplines remain an underutilized source of information about population origins, migration and identity. This paper investigates the geographical structure of surnames, using a unique individual level database assembled from registers and telephone directories from 16 European countries. We develop a novel combination of methods for exhaustively analyzing this multinational data set, based upon the Lasker Distance, consensus clustering and multidimensional scaling. Our analysis is both data rich and computationally intensive, entailing as it does the aggregation, clustering and mapping of 8 million surnames collected from 152 million individuals. The resulting regionalization has applications in developing our understanding of the social and cultural complexion of Europe, and offers potential insights into the long and short-term dynamics of migration and residential mobility. The research also contributes a range of methodological insights for future studies concerning spatial clustering of surnames and population data more widely. In short, this paper further demonstrates the value of surnames in multinational population studies and also the increasing sophistication of techniques available to analyze them.

The geography of intergenerational social mobility in Britain.

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.

Names-based ethnicity enhancement of hospital admissions in England, 1999-2013.

BACKGROUND: Accurate recording of ethnicity in electronic healthcare records is important for the monitoring of health inequalities. Yet until the late 1990s, ethnicity information was absent from more than half of records of patients who received inpatient care in England. In this study, we report on the usefulness of a names-based ethnicity classification, Ethnicity Estimator (EE), for addressing this gap in the hospital records. MATERIALS AND METHODS: Data on inpatient hospital admissions were obtained from Hospital Episode Statistics (HES) between April 1999 and March 2014. The data were enhanced with ethnicity coding of participants' surnames using the EE software. Only data on the first episode for each patient each year were included. RESULTS: A total of 111,231,653 patient-years were recorded between April 1999 and March 2014. The completeness of ethnicity records improved from 59.5 % in 1999 to 90.5 % in 2013 (financial year). Biggest improvement was seen in the White British group, which increased from 55.4 % in 1999 to 73.9 % in 2013. The correct prediction of NHS-reported ethnicity varied by ethnic group (2013 figures): White British (89.8 %), Pakistani (81.7 %), Indian (74.6 %), Chinese (72.9 %), Bangladeshi (63.4 %), Black African (57.3 %), White Other (50.5 %), White Irish (45.0 %). For other ethnic groups the prediction success was low to none. Prediction success was above 70 % in most areas outside London but fell below 40 % in parts of London. CONCLUSION: Studies of ethnic inequalities in hospital inpatient care in England are limited by incomplete data on patient ethnicity collected in the 1990s and 2000s. The prediction success of a names-based ethnicity classification tool has been quantified in HES for the first time and the results can be used to inform decisions around the optimal analysis of ethnic groups using this data source.

Ethnicity estimation using family naming practices.

This paper examines the association between given and family names and self-ascribed ethnicity as classified by the 2011 Census of Population for England and Wales. Using Census data in an innovative way under the new Office for National Statistics (ONS) Secure Research Service (SRS; previously the ONS Virtual Microdata Laboratory, VML), we investigate how bearers of a full range of given and family names assigned themselves to 2011 Census categories, using a names classification tool previously described in this journal. Based on these results, we develop a follow-up ethnicity estimation tool and describe how the tool may be used to observe changing relations between naming practices and ethnic identities as a facet of social integration and cosmopolitanism in an increasingly diverse society.

Ethnicity and population structure in personal naming networks.

Personal naming practices exist in all human groups and are far from random. Rather, they continue to reflect social norms and ethno-cultural customs that have developed over generations. As a consequence, contemporary name frequency distributions retain distinct geographic, social and ethno-cultural patterning that can be exploited to understand population structure in human biology, public health and social science. Previous attempts to detect and delineate such structure in large populations have entailed extensive empirical analysis of naming conventions in different parts of the world without seeking any general or automated methods of population classification by ethno-cultural origin. Here we show how 'naming networks', constructed from forename-surname pairs of a large sample of the contemporary human population in 17 countries, provide a valuable representation of cultural, ethnic and linguistic population structure around the world. This innovative approach enriches and adds value to automated population classification through conventional national data sources such as telephone directories and electoral registers. The method identifies clear social and ethno-cultural clusters in such naming networks that extend far beyond the geographic areas in which particular names originated, and that are preserved even after international migration. Moreover, one of the most striking findings of this approach is that these clusters simply 'emerge' from the aggregation of millions of individual decisions on parental naming practices for their children, without any prior knowledge introduced by the researcher. Our probabilistic approach to community assignment, both at city level as well as at a global scale, helps to reveal the degree of isolation, integration or overlap between human populations in our rapidly globalising world. As such, this work has important implications for research in population genetics, public health, and social science adding new understandings of migration, identity, integration and social interaction across the world.