Ethnic differences in COVID-19 mortality in the second and third waves of the pandemic in England during the vaccine roll-out.

Objectives This study aims to assess whether ethnic differences in COVID-19 mortality in England have continued into the third wave and to what extent differences in vaccination rates contributed to excess COVID-19 mortality after accounting for other risk factors.  Approach This Cohort study of 28.8 million adults living in private households or communal establishments in England is based on data from the Office for National Statistics (ONS) Public Health Data Asset (PHDA). The ONS PHDA is a linked dataset combining the 2011 Census, mortality records, the General Practice Extraction Service (GPES) Data for Pandemic Planning and Research (GDPPR), Hospital Episode Statistics (HES) and vaccination data from the National Immunisation Management System (NIMS). We calculated hazard ratios (HRs) for death involving COVID-19 during the second (8 December 2020 to 12 June 2021) and third wave (13 June 2021 to 1 December 2021) of the pandemic separately for males to females to assess the association between ethnic group and death involving COVID-19 in each wave, sequentially adjusting for age, residence type, geographical factors, sociodemographic characteristics, pre-pandemic health, and vaccination status. Results Age-adjusted HRs of death involving COVID-19 were higher for most ethnic minority groups than the White British group during both waves, particularly for groups with lowest vaccination rates (Bangladeshi, Pakistani, Black African and Black Caribbean). In both waves, HRs were attenuated after adjusting for geographical factors, sociodemographic characteristics, and pre-pandemic health. Further adjusting for vaccination status substantially reduced residual HRs for Black African, Black Caribbean, and Pakistani groups in the third wave. The only groups where fully-adjusted HRs remained elevated were the Bangladeshi group (men: 2.19, 95% CI 1.72 to 2.78; women: 2.12, 95% CI 1.58 to 2.86) and men from the Pakistani group (1.24, 95% CI 1.06 to 1.46).  Conclusion Public health strategies to increase vaccination uptake in ethnic minority groups could reduce disparities in COVID-19 mortality that cannot be accounted for by pre-existing risk factors

Associations between residential greenspace exposure and mortality in 4 645 581 adults living in London, UK: a longitudinal study

BACKGROUND: Urban greenspaces could reduce non-communicable disease (NCD) risk. The links between greenspaces and NCD-related mortality remain unclear. We aimed to estimate associations between residential greenspace quantity and access and all-cause mortality, cardiovascular disease mortality, cancer mortality, respiratory mortality, and type 2 diabetes mortality. METHODS: We linked 2011 UK Census data of London-dwelling adults (aged ≥18 years) to data from the UK death registry and the Greenspace Information for Greater London resource. We calculated percentage greenspace area, access point density (access points per km2), and distance in metres to the nearest access point for each respondent's residential neighbourhood (defined as 1000 m street network buffers) for greenspaces overall and by park type using a geographic information system. We estimated associations using Cox proportional hazards models, adjusted for a range of confounders. FINDINGS: Data were available for 4 645 581 individuals between March 27, 2011, and Dec 31, 2019. Respondents were followed up for a mean of 8·4 years (SD 1·4). All-cause mortality did not differ with overall greenspace coverage (hazard ratio [HR] 1·0004, 95% CI 0·9996-1·0012), increased with increasing access point density (1·0076, 1·0031-1·0120), and decreased slightly with increasing distance to the nearest access point (HR 0·9993, 0·9987-0·9998). A 1 percentage point (pp) increase in pocket park (areas for rest and recreation under 0·4 hectares) coverage was associated with a decrease in all-cause mortality risk (0·9441, 0·9213-0·9675), and an increase of ten pocket park access points per km2 was associated with a decreased respiratory mortality risk (0·9164, 0·8457-0·9931). Other associations were observed, but the estimated effects were small (eg, all-cause mortality risk for increases of 1 pp in regional park area were 0·9913, 0·9861-0·9966 and increases of ten small open space access points per km2 were 1·0247, 1·0151-1·0344). INTERPRETATION: Increasing the quantity of, and access to, pocket parks might help mitigate mortality risk. More research is needed to elucidate the mechanisms that could explain these associations. FUNDING: Health Data Research UK (HDRUK)

Socio-demographic differences in access to psychological treatment services: evidence from a national cohort study

BACKGROUND: Since 2008, the Improving Access to Psychological Therapies (IAPT) programme has offered adults in England evidence-based psychological treatments for common mental disorders (CMDs) such as depression and anxiety disorders. However, inequalities in access have not been explored at the national level. METHODS: Using a unique individual patient dataset that linked 2011 Census information of English residents to national IAPT data collected between April 2017 and March 2018, we estimated the rate of access by a wide range of socio-demographic characteristics that are not routinely available. A large household survey was used to estimate the prevalence of probable CMDs by these socio-demographic characteristics. We estimated the probability of access to IAPT amongst people with CMDs by comparing the rates of access from IAPT data and the estimates of prevalence of CMDs from the household survey. Both unadjusted and adjusted (for important patient characteristics) access rates were estimated in logistic regression models. RESULTS: As a proportion of those with a probable CMD, access to IAPT varied markedly by socio-demographic characteristics. Older adults, males, people born outside of the UK, people with religious beliefs, people from Asian ethnic backgrounds, people reporting a disability and those without any academic or professional qualifications were underrepresented in IAPT services nationally, in adjusted models. CONCLUSIONS: The identification of patients who may be underrepresented in IAPT provides an opportunity for services to target outreach and engagement with these groups. Further understanding of barriers to access should help increase equity in access

Assessing the reliability of ethnicity data recorded in health-related administrative datasets in England.

Objectives During the COVID-19 pandemic, higher mortality among some ethnic minority groups was identified and has become the subject of significant public and government interest, highlighting an urgent requirement to quantify the reliability of ethnicity classification across health administrative data sets, which are utilised in health analysis and pandemic planning. Approach The aim of our work was to assess how ethnicity data recorded in Census and health admin records varied across ethnicities and provide recommendations for how missingness can be accounted for by statisticians. Combining population level data from general practice (GP) records with hospital episode statistics (HES) for patients in England, we created a linked data set with Census 2011 data to reliably assess coverage and missingness between data sources. Most recent and modal ethnicity classifications were derived on a person-level from both HES and GP administrative data for comparison to gold-standard Census 2011 records. Results Agreement rates were calculated to assess the reliability of ethnicity data recorded in health administrative datasets compared to Census data. We found that the agreement rates vary by ethnic group and other demographic characteristics. Furthermore, we highlighted groups of people who exist in one health-admin source, but not Census, and vice versa, illustrating the importance of accounting for the sample bias in health analysis when relying solely on primary or secondary care data sources. Implementation of techniques to account for bias and missingness were tested to propose methodology to improve reliability of ethnicity estimates from both HES and GP data, in order to ensure estimates of health disparities are as accurate as possible. Conclusion We have linked GP records to Census 2011 and HES data to provide population-based ethnicity estimates of coverage, missingness and bias between data sources, in order to improve our understanding of ethnicity data quality. This work aims to inform policies tackling ethnic health inequalities in England

Risk of new-onset Long Covid following reinfection with SARS-CoV-2: community-based cohort study

Background: Little is known about the risk of Long Covid following reinfection with SARS-CoV-2. We estimated the likelihood of new-onset, self-reported Long Covid after a second SARS-CoV-2 infection, and compared to a first infection. // Methods: We included UK COVID-19 Infection Survey participants who tested positive for SARS-CoV-2 between 1 November 2021 and 8 October 2022. The primary outcome was self-reported Long Covid 12 to 20 weeks after each infection. Separate analyses were performed for those <16 years and ≥16 years. We estimated adjusted odds ratios (aORs) for new-onset Long Covid using logistic regression, comparing second to first infections, controlling for socio-demographic characteristics and calendar date of infection, plus vaccination status in those ≥16 years. // Results: Overall, Long Covid was reported by those ≥16 years after 4.0% and 2.4% of first and second infections, respectively; the corresponding estimates among those <16 years were 1.0% and 0.6%. The aOR for Long Covid after second compared to first infections was 0.72 (95% confidence interval: 0.63–0.81) for those ≥16 years and 0.93 (0.57–1.53) for those <16 years. // Conclusions: The risk of new-onset Long Covid after a second SARS-CoV-2 infection is lower than that after a first infection for those ≥16 years, though there is no evidence of a difference in risk for those <16 years. However, there remains some risk of new-onset Long Covid after a second infection, with around 1 in 40 of those ≥16 years and 1 in 165 of those <16 years reporting Long Covid after a second infection

Sociodemographic inequalities of suicide: A population-based cohort study of adults in England and Wales 2011-2021

Objectives With suicide a major public health concern, it is vital research identifies predictors of suicide to support vulnerable groups who should be targeted for intervention. We use a novel linkage of 2011 Census and population level mortality data to assess which risk factors are important predictors of suicide. Methods Exposures of interest were identified from Census 2011 and were sex, age, ethnicity, marital status, day-to-day impairments, religion, region, National Statistics Socio-economic Classification. Our study population consisted of 35,136,917 people aged 18-to-74; there were 35,928 suicides in our study period (28/03/2011-31/12/2021), with 73.9\% occurring in men. We fitted generalised linear models with a Poisson link function, with suicide being the outcome of interest. The natural logarithm of exposure time was included as an offset term. To estimate rates of suicide per 100,000 people for each level of our exposure, by sex for the average age, we calculated marginal means. Results The groups with the highest rates of suicide were those who reported an impairment affecting their day-to-day activities, those who were long term unemployed or never had worked, or those who were single or separated. Comparison of minimally adjusted models with models accounting for all other characteristics identified predictors which remain important risk factors after accounting for other characteristics; day-to-day impairments were still found to increase the incidence of suicide relative to those whose activities were not impaired after adjusting for employment status. Additionally, the estimated rates of suicide remained lowest in London compared to other regions in our fully adjusted estimates. Overall, rates of suicide were higher in men compared to females across all ages, with the highest rates in 40- to 50-year-olds. Conclusion The findings of this work provide novel population level insights into the risk of suicide by sociodemographic characteristics, this work should pave the way for further research exploring the interaction of factors which lead to suicide and drive policy change for targeted intervention

Deaths involving COVID-19 by self-reported disability status during the first two waves of the COVID-19 pandemic in England: a retrospective, population-based cohort study.

BACKGROUND: People with learning disabilities are at substantially increased risk of COVID-19 mortality, but evidence on risks of COVID-19 mortality for disabled people more generally is limited. We aimed to use population-level data to estimate the association between self-reported disability and death involving COVID-19 during the first two waves of the COVID-19 pandemic in England. METHODS: We conducted a retrospective, population-based cohort study of adults aged 30-100 years living in private households or communal establishments in England, using data from the Office for National Statistics Public Health Data Asset. Participants were present at the 2011 Census and alive on Jan 24, 2020. Participants reported being limited a lot in their daily activities, limited a little, or not limited at all, in response to a question from the 2011 Census. The outcome was death involving COVID-19, occurring between Jan 24, 2020, and Feb 28, 2021. We used Cox proportional hazards regression to calculate hazard ratios (HRs) for the association between disability and death involving COVID-19, sequentially adjusting for age, residence type (private household, care home, or other communal establishment), geographical characteristics (local authority district and population density), sociodemographic characteristics (ethnicity, highest qualification, Index of Multiple Deprivation decile, household characteristics [National Statistics Socio-economic Classification of the household reference person, tenure of household, household size, family status, household composition, and key worker in household], key worker type, individual and household exposure to disease, and individual and household proximity to others), and health status (pre-existing health conditions, body-mass index, and number of admissions to hospital and days spent in hospital over the previous 3 years). FINDINGS: 29 293 845 adults were included in the study (13 806 623 [47%] men, 15 487 222 [53%] women), of whom 3 038 772 (10%) reported being limited a little and 2 011 576 (7%) reported being limited a lot. During follow-up, 105 213 people died from causes involving COVID-19 in England, 61 416 (58%) of whom were disabled. Age-adjusted analyses showed higher mortality involving COVID-19 among disabled people who were limited a lot (HR 3·05 [95% CI 2·98-3·11] for men; 3·48 [3·41-3·56] for women) and disabled people who were limited a little (HR 1·88 [1·84-1·92] for men; 2·03 [1·98-2·08] for women) than among non-disabled people. Adjustment for residence type, geography, sociodemographics, and health conditions reduced but did not eliminate the associations between disability and death involving COVID-19 (HR 1·35 [1·32-1·38] for men who were limited a lot; 1·21 [1·18-1·23] for men who were limited a little; 1·55 [1·51-1·59] for women who were limited a lot; and 1·28 [1·25-1·31] for women who were limited a little). INTERPRETATION: Given the association between disability and mortality involving COVID-19, verification of these findings and consideration of recommendations for protective measures are now required. FUNDING: None