The changing interaction of ethnic and socio-economic segregation in England and Wales, 1991–2011

Ethnicities ◽  
2015 ◽  
Vol 17 (3) ◽  
pp. 320-349 ◽  
Author(s):  
Richard Harris ◽  
Ron Johnston ◽  
David Manley
Keyword(s):  
Ethnic Groups ◽  
Minority Groups ◽  
Census Data ◽  
Economic Disadvantage ◽  
Full Time ◽  
Ethnic Segregation ◽  
Contributing Factors ◽  
England And Wales ◽  
Ethnic Residential Segregation ◽  
The Uk

Following the publication of the 2001 and 2011 Census data, considerable attention has been given to patterns of ethnic residential segregation within the UK. The evidence contributes to debates about integration; however, as Kapoor (2013) has argued, discussion about it also risks promoting the idea that what we measure is voluntary segregation, arising from the outcome of residential choices and a preference to live with one's ethno-cultural peers. In reality, ethnic and social segregation overlap and are easily confounded; it is important to pay attention to where they geographically coincide. In this paper we use an area typology to assess whether minority ethnic groups are disproportionately concentrated in neighbourhoods in England and Wales containing the lowest proportions of their adult populations in full-time employment, and evaluate how those concentrations have changed between 1991 and 2011. We consider the (residential) exposure of the ethnic groups to the White British and also to each other, and identify the groups affected by the persistence of economic disadvantage. The analysis shows that patterns of ethnic segregation intersect strongly with neighbourhoods of socio-economic disadvantage, with inequalities in the labour market and the increase of part-time working suggested as contributing factors. A decreased exposure to the White British is an increased characteristic of the disadvantaged neighbourhoods where minority groups live. However, exposure between those groups has increased.

scholarly journals Implementing a Multilevel Index of Dissimilarity in R with a case study of the changing scales of residential ethnic segregation in England and Wales

2017 ◽  
Vol 45 (6) ◽  
pp. 1003-1021 ◽  
Author(s):  
Richard Harris ◽  
Dewi Owen
Keyword(s):  
Residential Segregation ◽  
Open Source Software ◽  
Minority Groups ◽  
Census Data ◽  
Scale Effects ◽  
Ethnic Segregation ◽  
Geographic Scale ◽  
England And Wales ◽  
Index Of Dissimilarity

This paper introduces the Multilevel Index of Dissimilarity package, which provides tools and functions to fit a Multilevel Index of Dissimilarity in the open source software, R. It extends the conventional Index of Dissimilarity to measure both the amount and geographic scale of segregation, thereby capturing the two principal dimensions of segregation, unevenness and clustering. The statistical basis for the multilevel approach is discussed, making connections to other work in the field and looking especially at the relationships between the Index of Dissimilarity, variance as a measure of segregation, and the partitioning of the variance to identify scale effects. A brief tutorial for the package is provided followed by a case study of the scales of residential segregation for various ethnic groups in England and Wales. Comparing 2001 with 2011 Census data, we find that patterns of segregation are emerging at less localised geographical scales but the Index of Dissimilarity is falling. This is consistent with a process whereby minority groups have spread out into more ethnically mixed neighbourhoods.

scholarly journals The Office for National Statistics Longitudinal Study

2019 ◽  
Vol 4 (3) ◽  
Author(s):  
Alison Sizer ◽  
Oliver Duke-Williams
Keyword(s):  
Longitudinal Study ◽  
Census Data ◽  
Sampling Bias ◽  
Large Sample Size ◽  
England And Wales ◽  
Large Sample ◽  
Small Areas ◽  
Pension Age ◽  
The Uk ◽  
State Pension

Background and Rationale The ONS Longitudinal Study (‘the LS’) covers England and Wales and includes individual data from the 1971 – 2011 decennial censuses and linked information on births, deaths and cancer registrations. It is representative of the population of England and Wales. Aim This presentation describes the LS and the linked administrative data, and showcases recent/ prominent examples of research. Methods and Approach The LS is built around samples drawn from decennial censuses, with its initial sample drawn from the 1971 Census. It also contains information about other people living in a sample-member’s household. Substantial emphasis is placed on security of access to the data and its responsible use. All research outputs are checked and are only released to users once disclosure control requirements are met. Linkage of study members from one census to another and vital events is carried out by ONS. Results The LS has been used for a variety of research. Using linked census and death records occupational differences in mortality rates have been researched. Individual records from all five censuses have been used to contribute to research social mobility, and research has also investigated the effects of long-term exposure to air pollution. Research has provided evidence of impact for social policy issues, e.g. health inequalities and the State Pension Age Review. Discussion The main strength of the LS is its large sample size (>1 million), making it the largest nationally representative longitudinal dataset in the UK. This allows analysis of small areas and specific population groups. Sampling bias is almost nil, and response rates are very high relative to other cohort and panel studies. Conclusion The ONS Longitudinal Study is a vital UK research asset, providing access to a large sample of census data linked across five censuses. It is strengthened through linkage to events data.

scholarly journals Measuring the exposure of Black, Asian and other ethnic groups to Covid-infected neighbourhoods in English towns and cities.

2021 ◽  
Author(s):  
Richard Harris ◽  
Chris Brunsdon
Keyword(s):  
Ethnic Groups ◽  
Minority Groups ◽  
House Prices ◽  
Poisson Model ◽  
Linear Predictor ◽  
Random Intercept ◽  
Black Residents ◽  
Occupational And Environmental Exposure ◽  
Index Of Exposure ◽  
The Uk

Abstract Drawing on the work of The Doreen Lawrence Review – a report on the disproportionate impact of Covid-19 on Black, Asian and minority ethnic communities in the UK – this paper develops an index of exposure, measuring which ethnic groups have been most exposed to Covid-19 infected residential neighbourhoods during the first and second waves of the pandemic in England. The index is based on a Bayesian Poisson model with a random intercept in the linear predictor, allowing for extra-Poisson variation at neighbourhood and town/city scales. This permits within-city differences to be decoupled from broader regional trends in the disease. The research finds that members of ethnic minority groups tend to be living in areas with higher infection rates but also that the risk of exposure is distributed unevenly across these groups. Initially, in the first wave, the disease disproportionately affected Black residents. As the pandemic has progressed, especially the Pakistani but also the Bangladeshi and Indian groups have had the highest exposure. This higher exposure of the Pakistani group is not straightforwardly a function of neighbourhood deprivation because it is present across a range of average house prices. However, we find evidence to support the view, expressed in The Doreen Lawrence Review, that it is linked to occupational and environmental exposure, particularly residential density.

scholarly journals Comparing ethnic segregation across cities—measurement issues matter

2020 ◽  
Author(s):  
Moritz Meister ◽  
Annekatrin Niebuhr
Keyword(s):  
Ethnic Groups ◽  
Minority Groups ◽  
Spatial Clustering ◽  
Minority Group ◽  
Average Level ◽  
Ethnic Segregation ◽  
Cross Sectional ◽  
Measurement Issues ◽  
The Impact ◽  
German Cities

AbstractThis paper investigates how important measurement issues such as the modifiable areal unit problem (MAUP), random unevenness and spatial autocorrelation affect cross-sectional studies of ethnic segregation. We use geocoded data for German cities to investigate the impact of these measurement problems on the average level of segregation and on the ranking of cities. The findings on the average level of residential segregation turn out to be rather robust. The ranking of cities is, however, sensitive to the assumptions regarding reallocation of population across neighbourhoods that the use of different segregation measures involves. Moreover, the results suggest that standard aspatial approaches tend to underrate the degree of segregation because they ignore the spatial clustering of ethnic groups. In contrast, non-consideration of random unevenness gives rise to a moderate upward bias of the mean segregation level and involves minor changes in the ranking of cities if the minority group is large. However, the importance of random segregation significantly increases as the size of the minority group declines. If the size of specific ethnic groups differs across regions, this may also affect the ranking of regions. Thus, the necessity to properly account for measurement issues increases as segregation analyses become more detailed and consider specific (small) minority groups.

scholarly journals Measuring the changing pattern of ethnic segregation in England and Wales with Consumer Registers

2020 ◽  
pp. 239980832091977
Author(s):  
Tian Lan ◽  
Jens Kandt ◽  
Paul Longley
Keyword(s):  
Residential Segregation ◽  
Large Scale ◽  
Ethnic Segregation ◽  
Time Intervals ◽  
England And Wales ◽  
Ethnic Residential Segregation ◽  
Ethnic Classification ◽  
Changing Patterns ◽  
Annual Resolution

Analysis of changing patterns of ethnic residential segregation is usually framed by the coarse categorisations of ethnicity used in censuses and other large-scale public sector surveys and by the infrequent time intervals at which such surveys are conducted. In this paper, we use names-based classification of Consumer Registers to investigate changing degrees of segregation in England and Wales over the period 1997–2016 at annual resolution. We find that names-based ethnic classification of the individuals that make up Consumer Registers provides reliable estimates of the residential patterning of different ethnic groups and the degree to which they are segregated. Building upon this finding, we explore more detailed segregation patterns and trends of finer groups at annual resolutions and discover some unexpected trends that have hitherto remained unrecorded by Census-based studies. We conclude that appropriately processed Consumer Registers hold considerable potential to contribute to various domains of urban geography and policy.

Researching Behavioural Differences among Ethnic Minority Groups: The Case for Inferring Ethnicity on the Basis of People's Names

2010 ◽  
Vol 52 (2) ◽  
pp. 191-215 ◽  
Author(s):  
Richard Webber
Keyword(s):  
Ethnic Groups ◽  
Customer Service ◽  
Minority Groups ◽  
Emergency Services ◽  
Relative Size ◽  
Inappropriate Use ◽  
Family Names ◽  
Minority Ethnic Groups ◽  
The Uk ◽  
The Impact

This paper reviews the growing use of personal and family names as a basis for inferring ethnicity, for researching behavioural differences among ethnic groups, and as a basis for market segmentation. It argues that, in the UK, ethnicity is used in market research to a lesser degree than is warranted by the extent of behavioural differences between ethnic groups. The reasons for this are held to include the impact of the inclusion of an ethnicity question on response, the difficulty in generating sufficient numbers of records to support the analysis of categories, most of which represent small proportions of the total population, the propensity of some consumers to belong to multiple categories and difficulties in establishing the relative size of different ethnic segments in base populations. The paper then contrasts the way in which commercial and public-sector organisations currently use ethnicity data, concluding that ethnicity is more often researched to assist compliance with diversity legislation than to deliver genuine insights of the sort that result in improved customer service. Then follows an explanation of the methodology whereby consumers can be classified on the basis of their personal and family names. The UK's British National Party and a research project resulting in reductions in the inappropriate use of accident and emergency services are used as case studies. The paper then considers how effectively a classification based on names overcomes the problems previously cited as constraining the successful use of ethnicity as a survey demographic. The paper concludes by suggesting the vertical markets in which name-based classification offers organisations the best opportunity for improving their reputation among minority ethnic groups as a result of a better understanding of their particular needs.

scholarly journals Ethnic minority groups in England and Wales - factors affecting the size and timing of elevated COVID-19 mortality: a retrospective cohort study linking Census and death records

2020 ◽  
Author(s):  
Daniel Ayoubkhani ◽  
Vahe Nafilyan ◽  
Chris White ◽  
Peter Goldblatt ◽  
Charlotte Gaughan ◽  
...  
Keyword(s):  
Cohort Study ◽  
Ethnic Minority ◽  
Ethnic Groups ◽  
Mortality Risk ◽  
Retrospective Cohort Study ◽  
Retrospective Cohort ◽  
Minority Groups ◽  
Cox Regression ◽  
Ethnic Minority Groups ◽  
England And Wales

Objectives: To estimate population-level associations between ethnicity and coronavirus disease 2019 (COVID-19) mortality, and to investigate how ethnicity-specific mortality risk evolved over the course of the pandemic. Design: Retrospective cohort study using linked administrative data. Setting: England and Wales, deaths occurring 2 March to 15 May 2020. Participants: Respondents to the 2011 Census of England and Wales aged ≤100 years and enumerated in private households, linked to death registrations and adjusted to account for emigration before the outcome period, who were alive on 1 March 2020 (n=47,872,412). Main outcome measure: Death related to COVID-19, registered by 29 May 2020. Statistical methods: We estimated hazard ratios (HRs) for ethnic minority groups compared with the White population using Cox regression models, controlling for geographical, demographic, socio-economic, occupational, and self-reported health factors. HRs were estimated on the full outcome period and separately for pre- and post-lockdown periods in the UK. Results: In the age-adjusted models, people from all ethnic minority groups were at elevated risk of COVID-19 mortality; the HRs for Black males and females were 3.13 [95% confidence interval: 2.93 to 3.34] and 2.40 [2.20 to 2.61] respectively. However, in the fully adjusted model for females, the HRs were close to unity for all ethnic groups except Black (1.29 [1.18 to 1.42]). For males, COVID-19 mortality risk remained elevated for the Black (1.76 [1.63 to 1.90]), Bangladeshi/Pakistani (1.35 [1.21 to 1.49]) and Indian (1.30 [1.19 to 1.43]) groups. The HRs decreased after lockdown for all ethnic groups, particularly Black and Bangladeshi/Pakistani females. Conclusions: Differences in COVID-19 mortality between ethnic groups were largely attenuated by geographical and socio-economic factors, although some residual differences remained. Lockdown was associated with reductions in excess mortality risk in ethnic minority populations, which has major implications for a second wave of infection or local spikes. Further research is needed to understand the causal mechanisms underpinning observed differences in COVID-19 mortality between ethnic groups.

scholarly journals Measuring the exposure of Black, Asian and other ethnic groups to COVID-infected neighbourhoods in English towns and cities

2021 ◽  
Author(s):  
Richard Harris ◽  
Chris Brunsdon
Keyword(s):  
Ethnic Groups ◽  
Minority Groups ◽  
House Prices ◽  
Poisson Model ◽  
Linear Predictor ◽  
Random Intercept ◽  
Black Residents ◽  
Occupational And Environmental Exposure ◽  
Index Of Exposure ◽  
The Uk

AbstractDrawing on the work of The Doreen Lawrence Review—a report on the disproportionate impact of COVID-19 on Black, Asian and minority ethnic communities in the UK—this paper develops an index of exposure, measuring which ethnic groups have been most exposed to COVID-19 infected residential neighbourhoods during the first and second waves of the pandemic in England. The index is based on a Bayesian Poisson model with a random intercept in the linear predictor, allowing for extra-Poisson variation at neighbourhood and town/city scales. This permits within-city differences to be decoupled from broader regional trends in the disease. The research finds that members of ethnic minority groups can be living in areas with higher infection rates but also that the risk of exposure is distributed unevenly across these groups. Initially, in the first wave, the disease disproportionately affected Black residents but, as the pandemic has progressed, especially the Pakistani but also the Bangladeshi and Indian groups have had the highest exposure. This higher exposure of the Pakistani group is not straightforwardly a function of neighbourhood deprivation because it is present across a range of average house prices. We find evidence to support the view, expressed in The Doreen Lawrence Review, that it is linked to occupational and environmental exposure, particularly residential density but, having allowed for these factors, differences between the towns and cities remain.

scholarly journals Does segregation reduce socio-spatial mobility? Evidence from four European countries with different inequality and segregation contexts

Urban Studies ◽  
2019 ◽  
Vol 57 (1) ◽  
pp. 176-197 ◽  
Author(s):  
Jaap Nieuwenhuis ◽  
Tiit Tammaru ◽  
Maarten van Ham ◽  
Lina Hedman ◽  
David Manley
Keyword(s):  
The Netherlands ◽  
Low Income ◽  
Census Data ◽  
Economic Status ◽  
European Countries ◽  
Spatial Mobility ◽  
England And Wales ◽  
Deprived Neighbourhoods ◽  
Income Inequalities ◽  
The Uk

The neighbourhood in which people live reflects their social class and preferences, so studying socio-spatial mobility between neighbourhood types gives insight into the openness of spatial class structures of societies and into the ability of people to leave disadvantaged neighbourhoods. In this paper we study the extent to which people move between different types of neighbourhoods by socio-economic status in different inequality and segregation contexts in four European countries: Sweden, the Netherlands, the UK (England and Wales), and Estonia. The study is based on population registers and census data for the 2001–2011 period. For England and Wales, which has long had high levels of income inequalities and high levels of socio-economic segregation, we find that levels of mobility between neighbourhood types are low and opportunities to move to more socio-economically advantaged neighbourhoods are modest. In Estonia, which used to be one of the most equal and least segregated countries in Europe, and now is one of the most unequal countries, we find high levels of mobility, but these reproduce segregation patterns and it is difficult to move to less deprived neighbourhoods for those in the most deprived neighbourhoods. In the Netherlands and Sweden, where income inequalities are the smallest, it is the easiest to move from the most deprived to less deprived neighbourhoods. The conclusion is that the combination of high levels of income inequalities and high levels of spatial segregation tend to lead to a vicious circle of segregation for low-income groups, where it is difficult to undertake upward socio-spatial mobility.

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