Who is returning to public transport for non-work trips after COVID-19? Evidence from older citizens' smart cards in the UK's second largest city region.

Harnessing a unique data source - longitudinal travel smartcard data linked to passenger demographics from 2019 to 2022 - we use methods of survival analysis to model the recovery of public transport patronage among 183,891 senior citizens resident in the West Midlands metropolitan region in the United Kingdom. Comparing pre and peri-pandemic patronage, we identify pronounced social and spatial inequalities in the speed of return to public transport. We find that male, younger and non-White passengers are more likely to return to public transport as soon as movement restrictions were lifted, whereas passengers from White ethnic background and affluent areas do not return to public transport within the first year after the outbreak. Pronounced social inequalities persist into the middle of 2021, and only thence they began to attenuate as part of a wider return to public transport among passengers post retirement age. In 2022, 80% of these passengers have returned to public transport but the frequency of use has remained lower than prior to the pandemic. We discuss implications for transport policy and planning.

Accessibility and Essential Travel: Public Transport Reliance Among Senior Citizens During the COVID-19 Pandemic.

Using smart card travel data, we compare demand for bus services by passengers of age 65 or older prior to and during the COVID-19 pandemic to identify public transport-reliant users residing in more car-dependent environments-i.e., people who rely on public transport services to carry out essential activities, such as daily shopping and live in areas with low public transport accessibility. Viewing lockdowns as natural experiments, we use spatial analysis combined with multilevel logistic regressions to characterize the demographic and geographic context of those passengers who continued to use public transport services in these areas during lockdown periods, or quickly returned to public transport when restrictions were eased. We find that this particular type of public transport reliance is significantly associated with socio-demographic characteristics alongside urban residential conditions. Specifically, we identify suburban geographies of public transport reliance, which are at risk of being overlooked in approaches that view public transport dependence mainly as an outcome of deprivation. Our research demonstrates once again that inclusive, healthy and sustainable mobility can only be achieved if all areas of metropolitan regions are well and reliably served by public transport.

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.

Ethnic disparities in preventable hospitalisation in England: an analysis of 916 375 emergency admissions.

OBJECTIVES: To study ethnic inequalities in ambulatory care sensitive conditions (ACSC) in England. DESIGN: Observational study of inpatient hospital admission database enhanced with ethnicity coding of patient surnames. The primary diagnosis of the first episode in spells with emergency admission were coded with definitions for acute ACSC, chronic ACSC and vaccine-preventable diseases. SETTING: National Health Service England. PARTICIPANTS: 916 375 ACSC emergency admissions in 7 39 618 patients were identified between April 2011 and March 2012. MAIN OUTCOME MEASURES: ORs of ACSC for each ethnic group relative to the White British majority group adjusted for age, sex and area deprivation. RESULTS: Acute ACSC admission risk adjusted for age and sex was particularly high among Other (OR 1.73; 95% CI 1.69 to 1.77) and Pakistani (1.51; 95% CI 1.48 to 1.54) compared with White British patients. For chronic ACSC, high risk was found among Other (2.02; 95% CI 1.97 to 2.08), Pakistani (2.07; 95% CI 2.02 to 2.12) and Bangladeshi (1.36; 95% CI 1.30 to 1.42). For vaccine-preventable diseases, other (2.42; 95% CI 2.31 to 2.54), Pakistani (1.94; 95% CI 1.85 to 2.04), Bangladeshi (1.48; 95% CI 1.36 to 1.62), Black African (1.45; 95% CI 1.36 to 1.54) and white other (1.38; 95% CI 1.33 to 1.43) groups. Elevated risk was only partly explained in analyses also adjusting for area deprivation. CONCLUSIONS: ACSC admission was especially high among individuals of Bangladeshi, Pakistani, Black African, white other or other background with up to twofold differences compared with the white British group. This suggests that these ethnic groups are not receiving optimal primary care.

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.

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.

ActEarly: a City Collaboratory approach to early promotion of good health and wellbeing.

Economic, physical, built, cultural, learning, social and service environments have a profound effect on lifelong health. However, policy thinking about health research is dominated by the 'biomedical model' which promotes medicalisation and an emphasis on diagnosis and treatment at the expense of prevention. Prevention research has tended to focus on 'downstream' interventions that rely on individual behaviour change, frequently increasing inequalities. Preventive strategies often focus on isolated leverage points and are scattered across different settings. This paper describes a major new prevention research programme that aims to create City Collaboratory testbeds to support the identification, implementation and evaluation of upstream interventions within a whole system city setting. Prevention of physical and mental ill-health will come from the cumulative effect of multiple system-wide interventions. Rather than scatter these interventions across many settings and evaluate single outcomes, we will test their collective impact across multiple outcomes with the goal of achieving a tipping point for better health. Our focus is on early life (ActEarly) in recognition of childhood and adolescence being such critical periods for influencing lifelong health and wellbeing.

Social practice, plural lifestyles and health inequalities in the United Kingdom.

Persistent health inequalities pose a continued research and policy challenge in the United Kingdom and elsewhere. Current approaches to health research and promotion are predicated on a distinction between wider, social structural causes and individual, health-related behaviours often conceived of as lifestyle choices. Drawing on Bourdieu's theory of social practice, this paper develops an integrated perspective by observing associations between health and structured lifestyle practices. Using the UK Understanding Society household survey, a taxonomy of eight lifestyle clusters is identified, which exhibit significant health inequalities on a number of indicators. But the plurality of practices and subjective orientations inherent in the taxonomy reveals a finer, more complex differentiation of the social gradient in health. In addition, lifestyle appears to at least in parts mediate the relationship between social, material conditions and health. A feature of the taxonomy is that it admits a relational and contextual apprehension of health-relevant, behavioural aspects within a more holistic notion of lifestyles. Based on this view, strategic approaches can be developed that respond to group-specific situations and pathways and their varying roots in upstream or downstream domains of policy.

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.

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.