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Background: We compared the quality of ethnicity coding within the Public Health Scotland Ethnicity Look-up (PHS-EL) dataset, and other National Health Service datasets, with the 2011 Scottish Census., Methods: Measures of quality included the level of missingness and misclassification. We examined the impact of misclassification using Cox proportional hazards to compare the risk of severe coronavirus disease (COVID-19) (hospitalization & death) by ethnic group., Results: Misclassification within PHS-EL was higher for all minority ethnic groups [12.5 to 69.1%] compared with the White Scottish majority [5.1%] and highest in the White Gypsy/Traveller group [69.1%]. Missingness in PHS-EL was highest among the White Other British group [39%] and lowest among the Pakistani group [17%]. PHS-EL data often underestimated severe COVID-19 risk compared with Census data. e.g. in the White Gypsy/Traveller group the Hazard Ratio (HR) was 1.68 [95% Confidence Intervals (CI): 1.03, 2.74] compared with the White Scottish majority using Census ethnicity data and 0.73 [95% CI: 0.10, 5.15] using PHS-EL data; and HR was 2.03 [95% CI: 1.20, 3.44] in the Census for the Bangladeshi group versus 1.45 [95% CI: 0.75, 2.78] in PHS-EL., Conclusions: Poor quality ethnicity coding in health records can bias estimates, thereby threatening monitoring and understanding ethnic inequalities in health., (© The Author(s) 2023. Published by Oxford University Press on behalf of Faculty of Public Health.)

Background: This study aims to estimate ethnic inequalities in risk for positive SARS-CoV-2 tests, COVID-19 hospitalisations and deaths over time in Scotland., Methods: We conducted a population-based cohort study where the 2011 Scottish Census was linked to health records. We included all individuals ≥ 16 years living in Scotland on 1 March 2020. The study period was from 1 March 2020 to 17 April 2022. Self-reported ethnic group was taken from the census and Cox proportional hazard models estimated HRs for positive SARS-CoV-2 tests, hospitalisations and deaths, adjusted for age, sex and health board. We also conducted separate analyses for each of the four waves of COVID-19 to assess changes in risk over time., Findings: Of the 4 358 339 individuals analysed, 1 093 234 positive SARS-CoV-2 tests, 37 437 hospitalisations and 14 158 deaths occurred. The risk of COVID-19 hospitalisation or death among ethnic minority groups was often higher for White Gypsy/Traveller (HR 2.21, 95% CI (1.61 to 3.06)) and Pakistani 2.09 (1.90 to 2.29) groups compared with the white Scottish group. The risk of COVID-19 hospitalisation or death following confirmed positive SARS-CoV-2 test was particularly higher for White Gypsy/Traveller 2.55 (1.81-3.58), Pakistani 1.75 (1.59-1.73) and African 1.61 (1.28-2.03) individuals relative to white Scottish individuals. However, the risk of COVID-19-related death following hospitalisation did not differ. The risk of COVID-19 outcomes for ethnic minority groups was higher in the first three waves compared with the fourth wave., Interpretation: Most ethnic minority groups were at increased risk of adverse COVID-19 outcomes in Scotland, especially White Gypsy/Traveller and Pakistani groups. Ethnic inequalities persisted following community infection but not following hospitalisation, suggesting differences in hospital treatment did not substantially contribute to ethnic inequalities., Competing Interests: Competing interests: SVK was cochair of the Scottish Government’s Expert Reference Group on Ethnicity and COVID-19 and a member of the Scientific Advisory Group on Emergencies subgroup on ethnicity., (© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY. Published by BMJ.)

Background: Ethnicity can influence susceptibility to infection, as COVID-19 has shown. Few countries have systematically investigated ethnic variations in infection., Methods: We linked the Scotland 2001 Census, including ethnic group, to national databases of hospitalizations/deaths and serological diagnoses of bloodborne viruses for 2001-2013. We calculated age-adjusted rate ratios (RRs) in 12 ethnic groups for all infections combined, 15 infection categories, and human immunodeficiency virus (HIV), hepatitis B (HBV) and hepatitis C (HCV) viruses., Results: We analysed over 1.65 million infection-related hospitalisations/deaths. Compared with White Scottish, RRs for all infections combined were 0.8 or lower for Other White British, Other White and Chinese males and females, and 1.2-1.4 for Pakistani and African males and females. Adjustment for socioeconomic status or birthplace had little effect. RRs for specific infection categories followed similar patterns with striking exceptions. For HIV, RRs were 136 in African females and 14 in males; for HBV, 125 in Chinese females and 59 in males, 55 in African females and 24 in males; and for HCV, 2.3-3.1 in Pakistanis and Africans., Conclusions: Ethnic differences were found in overall rates and many infection categories, suggesting multiple causative pathways. We recommend census linkage as a powerful method for studying the disproportionate impact of COVID-19., (© The Author(s) 2021. Published by Oxford University Press on behalf of Faculty of Public Health.)

Background: Recording patients' ethnic group supports efforts to achieve equity in health care provision. Before the Equality Act (2010), recording ethnic group at hospital admission was poor in Scotland but has improved subsequently. We describe the first analysis of the utility of such data nationally for monitoring ethnic variation., Methods: We analysed all in-patient or day case hospital admissions in 2013. We imputed missing data using the most recent ethnic group recorded for a patient from 2009 to 2015. For episodes lacking an ethnic code, we attributed known ethnic codes proportionately. Using the 2011 Census population, we calculated rates and rate ratios for all-cause admissions and ischaemic heart diseases (IHDs) directly standardized for age., Results: Imputation reduced missing ethnic group codes from 24 to 15% and proportionate redistribution to zero. While some rates for both all-cause and IHD admissions appeared plausible, unexpectedly low or high rates were observed for several ethnic groups particularly amongst White groups and newly coded groups., Conclusions: Completeness of ethnicity recoding on hospital admission records has improved markedly since 2010. However the validity of admission rates based on these data is variable across ethnic groups and further improvements are required to support monitoring of inequality., (© The Author(s) 2019. Published by Oxford University Press on behalf of Faculty of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Objective: Cancer screening should be equitably accessed by all populations. Uptake of colorectal cancer screening was examined using the Scottish Health and Ethnicity Linkage Study that links the Scottish Census 2001 to health data by individual-level self-reported ethnicity and religion., Setting: Data on 1.7 million individuals in two rounds of the Scottish Bowel Cancer Screening Programme (2007-2013) were linked to the 2001 Census using the Scottish Community Health Index number., Main Outcome Measure: Uptake of colorectal cancer screening, reported as age-adjusted risk ratios (RRs) by ethnic group and religion were calculated for men and women with 95% CI., Results: In the first, incidence screening round, compared with white Scottish men, Other White British (RR 109.6, 95% CI 108.8 to 110.3) and Chinese (107.2, 95% CI 102.8 to 111.8) men had higher uptake. In contrast, men of all South Asian groups had lower uptake (Indian RR 80.5, 95% CI 76.1 to 85.1; Pakistani RR 65.9, 95% CI 62.7 to 69.3; Bangladeshi RR 76.6, 95% CI 63.9 to 91.9; Other South Asian RR 88.6, 95% CI 81.8 to 96.1). Comparable patterns were seen among women in all ethnic groups, for example, Pakistani (RR 55.5, 95% CI 52.5 to 58.8). Variation in uptake was also observed by religion, with lower rates among Hindu (RR (95%CI): 78.4 (71.8 to 85.6)), Muslim (69.5 (66.7 to 72.3)) and Sikh (73.4 (67.1 to 80.3)) men compared with the reference population (Church of Scotland), with similar variation among women: lower rates were also seen among those who reported being Jewish, Roman Catholic or with no religion., Conclusions: There are important variations in uptake of bowel cancer screening by ethnic group and religion in Scotland, for both sexes, that require further research and targeted interventions., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY. Published by BMJ.)

Objectives: To investigate ethnic differences in falls and road traffic injuries (RTIs) in Scotland., Study Design: A retrospective cohort of 4.62 million people, linking the Scottish Census 2001, with self-reported ethnicity, to hospitalisation and death records for 2001-2013., Methods: We selected cases with International Classification of Diseases-10 diagnostic codes for falls and RTIs. Using Poisson regression, age-adjusted risk ratios (RRs, multiplied by 100 as percentages) and 95% confidence intervals (CIs) were calculated by sex for 10 ethnic groups with the White Scottish as reference. We further adjusted for country of birth and socio-economic status (SES)., Results: During about 49 million person-years, there were 275,995 hospitalisations or deaths from fall-related injuries and 43,875 from RTIs. Compared with the White Scottish, RRs for falls were higher in most White and Mixed groups, e.g., White Irish males (RR: 131; 95% CI: 122-140) and Mixed females (126; 112-143), but lower in Pakistani males (72; 64-81) and females (72; 63-82) and African females (79; 63-99). For RTIs, RRs were higher in other White British males (161; 147-176) and females (156; 138-176) and other White males (119; 104-137) and females (143; 121-169) and lower in Pakistani females (74; 57-98). The ethnic variations differed by road user type, with few cases among non-White motorcyclists and non-White female cyclists. The RRs were minimally altered by adjustment for country of birth or SES., Conclusion: We found important ethnic variations in injuries owing to falls and RTIs, with generally lower risks in non-White groups. Culturally related differences in behaviour offer the most plausible explanation, including variations in alcohol use. The findings do not point to the need for new interventions in Scotland at present. However, as the ethnic mix of each country is unique, other countries could benefit from similar data linkage-based research., (Copyright © 2020 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Objectives: Immigration into Europe has raised contrasting concerns about increased pressure on health services and equitable provision of health care to immigrants or ethnic minorities. Our objective was to find out if there were important differences in hospital use between the main ethnic groups in Scotland., Study Design: A census-based data linkage cohort study., Methods: We anonymously linked Scotland's Census 2001 records for 4.62 million people, including their ethnic group, to National Health Service general hospitalisation records for 2001-2013. We used Poisson regression to calculate hospitalisation rate ratios (RRs) in 14 ethnic groups, presented as percentages of the White Scottish reference group (RR = 100), for males and females separately. We adjusted for age and socio-economic status and compared those born in the United Kingdom or the Republic of Ireland (UK/RoI) with elsewhere. We calculated mean lengths of hospital stay., Results: 9.79 million hospital admissions were analysed. Compared with the White Scottish, unadjusted RRs for both males and females in most groups were about 50-90, e.g. Chinese males 49 (95% confidence interval [CI] = 45-53) and Indian females 76 (95% CI 71-81). The exceptions were White Irish, males 120 (95% CI 117-124) and females 115 (95% CI 112-119) and Caribbean females, 103 (95% CI 85-126). Adjusting for age increased the RRs for most groups towards or above the reference. Socio-economic status had little effect. In many groups, those born outside the UK/RoI had lower admission rates. Unadjusted mean lengths of stay were substantially lower in most ethnic minorities., Conclusions: Use of hospital beds in Scotland by most ethnic minorities was lower than by the White Scottish majority, largely explained by their younger average age. Other countries should use similar methods to assess their own experience., (Copyright © 2018 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Background: Ethnic minorities often experience barriers to health care. We studied six established quality indicators of health-system performance across ethnic groups in Scotland., Methods: In this population-based cohort study, we linked ethnicity from Scotland's Census 2001 (April 29, 2001) to hospital admissions and mortality records, with follow-up until April 30, 2013. Indicators of health-system performance included amenable deaths (ie, deaths avertable by effective treatment), preventable deaths (ie, deaths avertable by public health policy), avoidable deaths (combined amenable and preventable deaths), avoidable hospital admissions, unplanned readmissions, and length of stay. We calculated rate ratios and odds ratios (with 95% CIs) using Poisson and logistic regression, which we multiplied by 100, adjusting first for age-related covariates and then for socioeconomic-related and birthplace-related covariates. The white Scottish population was the reference (rate ratio [RR] 100)., Findings: The results are based on 4·61 million people. During the 50·5 million person-years of study, 1·17 million avoidable hospital admissions, 587 740 unplanned readmissions, and 166 245 avoidable deaths occurred. South Asian groups had higher avoidable hospital admissions than the white Scottish group, with the highest reported RRs in Pakistani groups (RR 140·6 [95% CI 131·9-150·0] in men; RR 141·0 [129·0-154·1] in women). There was little variation between ethnic groups in length of stay or unplanned readmission. Preventable and amenable mortality were higher in the white Scottish group than several ethnic minorities including other white British, other white, Indian, and Chinese groups. Such differences were partly diminished by adjustment for socioeconomic status, whereas adjustment for country of birth had little additional effect., Interpretation: These data suggest concerns about the access to and quality of primary care to prevent avoidable hospital admissions, especially for south Asians. Relatively high preventable and amenable deaths in white Scottish people, compared with several ethnic minority populations, were unexpected. Future studies should both corroborate and examine explanations for these patterns. Studies using several indicators simultaneously are also required internationally., Funding: Chief Scientist's Office, Medical Research Council, NHS Research Scotland, Farr Institute., (Copyright © 2018 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

Background: Migrant and ethnic minority groups are often assumed to have poor health relative to the majority population. Few countries have the capacity to study a key indicator, mortality, by ethnicity and country of birth. We hypothesized at least 10% differences in mortality by ethnic group in Scotland that would not be wholly attenuated by adjustment for socio-economic factors or country of birth., Methods and Findings: We linked the Scottish 2001 Census to mortality data (2001-2013) in 4.62 million people (91% of estimated population), calculating age-adjusted mortality rate ratios (RRs; multiplied by 100 as percentages) with 95% confidence intervals (CIs) for 13 ethnic groups, with the White Scottish group as reference (ethnic group classification follows the Scottish 2001 Census). The Scottish Index of Multiple Deprivation, education status, and household tenure were socio-economic status (SES) confounding variables and born in the UK or Republic of Ireland (UK/RoI) an interacting and confounding variable. Smoking and diabetes data were from a primary care sub-sample (about 53,000 people). Males and females in most minority groups had lower age-adjusted mortality RRs than the White Scottish group. The 95% CIs provided good evidence that the RR was more than 10% lower in the following ethnic groups: Other White British (72.3 [95% CI 64.2, 81.3] in males and 75.2 [68.0, 83.2] in females); Other White (80.8 [72.8, 89.8] in males and 76.2 [68.6, 84.7] in females); Indian (62.6 [51.6, 76.0] in males and 60.7 [50.4, 73.1] in females); Pakistani (66.1 [57.4, 76.2] in males and 73.8 [63.7, 85.5] in females); Bangladeshi males (50.7 [32.5, 79.1]); Caribbean females (57.5 [38.5, 85.9]); and Chinese (52.2 [43.7, 62.5] in males and 65.8 [55.3, 78.2] in females). The differences were diminished but not eliminated after adjusting for UK/RoI birth and SES variables. A mortality advantage was evident in all 12 minority groups for those born abroad, but in only 6/12 male groups and 5/12 female groups of those born in the UK/RoI. In the primary care sub-sample, after adjustment for age, UK/RoI born, SES, smoking, and diabetes, the RR was not lower in Indian males (114.7 [95% CI 78.3, 167.9]) and Pakistani females (103.9 [73.9, 145.9]) than in White Scottish males and females, respectively. The main limitations were the inability to include deaths abroad and the small number of deaths in some ethnic minority groups, especially for people born in the UK/RoI., Conclusions: There was relatively low mortality for many ethnic minority groups compared to the White Scottish majority. The mortality advantage was less clear in UK/RoI-born minority group offspring than in immigrants. These differences need explaining, and health-related behaviours seem important. Similar analyses are required internationally to fulfil agreed goals for monitoring, understanding, and improving health in ethnically diverse societies and to apply to health policy, especially on health inequalities and inequities.