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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.

Background Although most adults infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) fully recover, a proportion have ongoing symptoms, or post-COVID conditions (PCC), after infection. The objective of this analysis was to estimate the number of United States (US) adults with activity-limiting PCC on 1 November 2021. Methods We modeled the prevalence of PCC using reported infections occurring from 1 February 2020 to 30 September 2021, and population-based, household survey data on new activity-limiting symptoms ≥1 month following SARS-CoV-2 infection. From these data sources, we estimated the number and proportion of US adults with activity-limiting PCC on 1 November 2021 as 95% uncertainty intervals, stratified by sex and age. Sensitivity analyses adjusted for underascertainment of infections and uncertainty about symptom duration. Results On 1 November 2021, at least 3.0–5.0 million US adults, or 1.2%–1.9% of the US adult population, were estimated to have activity-limiting PCC of ≥1 month’s duration. Population prevalence was higher in females (1.4%–2.2%) than males. The estimated prevalence after adjusting for underascertainment of infections was 1.7%–3.8%. Conclusions Millions of US adults were estimated to have activity-limiting PCC. These estimates can support future efforts to address the impact of PCC on the US population.

BackgroundLittle 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.MethodsWe 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 ResultsOverall, 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 ConclusionsThe 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

BackgroundRisk of suicide is complex and often a result of multiple interacting factors. It is vital research identifies predictors of suicide to provide a strong evidence base for targeted interventions.MethodsUsing linked Census and population level mortality data we estimated rates of suicide across different groups in England and Wales and examine which factors are independently associated with the risk of suicide.FindingsThe highest rates of suicide were amongst 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. Rates of suicide were highest in the White and Mixed/multiple ethnic groups compared to other ethnicities, and in people who reported a religious affiliation compared with those who had no religion. Comparison of minimally adjusted models (predictor, sex and age) with fully-adjusted models (sex, age, ethnicity, region, partnership status, religious affiliation, day-to-day impairments, armed forces membership and socioeconomic status) identified key 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. Overall, rates of suicide were higher in men compared to females across all ages, with the highest rates in 40-to-50-year-olds.InterpretationThe findings of this work provide novel population level insights into the risk of suicide by sociodemographic characteristics. Understanding the interaction between key risk factors for suicide has important implications for national suicide prevention strategies.FundingThis study received no specific funding.Research in contextEvidence before this studyPrevious studies have identified key risk factors for suicide; being male and being aged 40 to 50 years of age have the highest rates of suicide. Suicide is a major public health concern, with prevention strategies imperative to minimising events.Added value of this studyFor the first time we make population level estimates of suicide rates in England and Wales using death registration data linked to 2011 Census.Furthermore, we calculate incidence rate ratios for fully adjusted models which provide novel insights into the interplay between different risk factors. For instance, we see that people who report having day-to-day impairments risk of suicide is 2- to 3-times higher for men and women respectively compared to people who do not report day-to-day impairments, after adjusting for other characteristics such as socioeconomic status which are likely associated with impairments.Implications of this studyUnderstanding the groups most at risk of suicide is imperative for national suicide prevention strategies. This work provides novel population level insights into the risk of suicide by sociodemographic characteristics.

Several studies have reported associations between COVID-19 vaccination and risk of cardiac diseases, especially in young people; the impact on mortality, however, remains unclear. We use national, linked electronic health data in England to assess the impact of COVID-19 vaccination and positive SARS-CoV-2 tests on the risk of cardiac and all-cause mortality in young people (12 to 29 years) using a self-controlled case series design. Here, we show there is no significant increase in cardiac or all-cause mortality in the 12 weeks following COVID-19 vaccination compared to more than 12 weeks after any dose. However, we find an increase in cardiac death in women after a first dose of non mRNA vaccines. A positive SARS-CoV-2 test is associated with increased cardiac and all-cause mortality among people vaccinated or unvaccinated at time of testing.

BackgroundEvidence on the long-term employment consequences of SARS-CoV-2 infection is lacking. We used data from a large, community-based sample in the UK to estimate associations between Long Covid and subsequent employment outcomes.MethodsThis was an observational, longitudinal study using a pre-post design. We included UK COVID-19 Infection Survey participants who completed questionnaires on Long Covid from 3 February 2021 to 30 September 2022 when they were aged 16 to 64 years and not in full-time education. We used conditional logit modelling to explore the time-varying relationship between Long Covid status ≥12 weeks after a first test-confirmed SARS-CoV-2 infection (reference: pre-infection) and labour market inactivity (neither working nor looking for work) or workplace absence lasting ≥4 weeks.ResultsOf 206,299 included participants (mean age 45 years, 54% female, 92% white), 15% were ever inactive in the labour market and 10% were ever long-term absent during follow-up. Compared with pre-infection, inactivity was higher in participants reporting Long Covid 30 to ConclusionsLong Covid is likely to have contributed to reduced levels of participation in the UK labour market, though it is unlikely to be the sole driver. Further research is required to quantify the contribution of other factors, such as indirect health effects of the pandemic.

BackgroundThe risk of COVID-19 severity and mortality differs markedly by age, socio-demographic characteristics and pre-existing health status. Various studies have suggested that higher air pollution exposures also increase the likelihood of dying from COVID-19.Objectives: To assess the association between long-term outdoor air pollution (NO2, NOx, PM10and PM2.5) concentrations and the risk of death involving COVID-19, using a large individual-level dataset.MethodsWe used comprehensive individual-level data from the Office for National Statistics’ Public Health Data Asset for September 2020 to January 2022 and London Air Quality Network modelled air pollution concentrations available for 2016. Using Cox proportional hazard regression models, we adjusted for potential confounders including age, sex, vaccination status, dominant virus variants, geographical factors (such as population density), ethnicity, area and household-level deprivation, and health comorbidities.ResultsThere were 737,356 confirmed COVID-19 cases including 9,315 COVID-related deaths. When only adjusting for age, sex, and vaccination status, there was an increased risk of dying from COVID-19 with increased exposure to all air pollutants studied (NO2: HR 1.07 [95% confidence interval: 1.04-1.12] per 10 μg/m3; NOx: 1.05[1.02-1.09] per 20 μg/m3; PM10: 1.32[1.15-1.51] per 10 μg/m3; PM2.5: 1.29[1.12-1.49] per 5 μg/m3). However, after adjustment including ethnicity and socio-economic factors the HRs were close to unity (NO2: 0.98[0.90-1.06]; NOx: 0.99[0.94-1.04]; PM10: 0.95[0.74-1.22]; PM2.5: 0.90[0.67-1.20]). Additional adjustment for dominant variant or pre-existing health comorbidities did not alter the results.ConclusionsObserved associations between long-term outdoor air pollution exposure and COVID-19 mortality in London are strongly confounded by geography, ethnicity and deprivation.SummaryUsing a large individual-level dataset, we found that a positive association between long-term outdoor air pollution and COVID-19 mortality in London did not persist after adjusting for confounders including population density, ethnicity and deprivation.

The diagnosis of a severe physical health condition can cause psychological distress and lead to severe depression. The association between severe physical health conditions and the risk of suicide, and how the risk of suicide changes in the months following diagnosis, are not clear.We estimated whether a diagnosis of severe physical health conditions is associated with an increase in the risk of death by suicide using a dataset based on the 2011 Census linked to hospital records and death registration records covering 47,354,696 people alive on 1 January 2017 in England. Patients diagnosed with a low-survival cancer, chronic ischaemic heart disease, chronic obstructive pulmonary disease, or degenerative neurological condition were matched to individuals using socio-demographic characteristics from the Census. Using the Aalen-Johansen estimator, we estimated the cumulative incidence of death by suicide occurring between 1 January 2017 and 31 December 2021 (registered by 31 December 2021) in patients and matched controls, adjusted for other potential confounders using inverse probability weighting.Diagnosis of severe conditions was associated with an increased risk of dying by suicide. One year after diagnosis, the rate of suicide was 21.6 (95% confidence intervals: 14.9-28.4, number of events (N): 39) per 100,000 low-survival cancer patients compared to 9.5 (5.6-14.6, N:16) per 100,000 matched controls. For COPD patients, the one-year suicide rate was 22.4 (19.4-25.5, N:208) per 100,000 COPD patients (matched controls: 10.6, 8.3-13.0, N:85), for ischaemic heart disease 16.1 (14.1-18.2, N:225) per 100,000 patients (matched controls: 8.8, 7.1-10.4, N:128), for degenerative neurological conditions 114.5 (49.6-194.7, N:11) per 100,000 patients. The increase in risk was more pronounced in the first six months after diagnosis or first treatment.A diagnosis of severe physical illness is associated with higher suicide risk. The interaction of physical and mental illness emphasises the importance of collaborative physical and mental health care in these patients.The Office for National Statistics. KES is the Laing Galazka chair in palliative care at King's College London, funded by an endowment from Cicely Saunders International and the Kirby Laing Foundation.

We investigated long COVID incidence by vaccination status in a random sample of UK adults from April 2020 to November 2021. Persistent symptoms were reported by 9.5% of 3090 breakthrough severe acute respiratory syndrome coronavirus 2 infections and 14.6% of unvaccinated controls (adjusted odds ratio, 0.59 [95% confidence interval, .50–.69]), emphasizing the need for public health initiatives to increase population-level vaccine uptake.

ObjectivesThis 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. ApproachThis 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. ResultsAge-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). ConclusionPublic 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.

ObjectivesDuring 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. ApproachThe 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. ResultsAgreement 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. ConclusionWe 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.

Introduction At the start of the COVID-19 pandemic there was an urgent need to identify individuals at highest risk of severe outcomes, such as hospitalisation and death following infection. The QCOVID risk prediction algorithms emerged as key tools in facilitating this which were further developed during the second wave of the COVID-19 pandemic to identify groups of people at highest risk of severe COVID-19 related outcomes following one or two doses of vaccine. Objectives To externally validate the QCOVID3 algorithm based on primary and secondary care records for Wales, UK. Methods We conducted an observational, prospective cohort based on electronic health care records for 1.66m vaccinated adults living in Wales on 8th December 2020, with follow-up until 15th June 2021. Follow-up started from day 14 post vaccination to allow the full effect of the vaccine. Results The scores produced by the QCOVID3 risk algorithm showed high levels of discrimination for both COVID-19 related deaths and hospital admissions and good calibration (Harrell C statistic: ≥ 0.828). Conclusion This validation of the updated QCOVID3 risk algorithms in the adult vaccinated Welsh population has shown that the algorithms are valid for use in the Welsh population, and applicable on a population independent of the original study, which has not been previously reported. This study provides further evidence that the QCOVID algorithms can help inform public health risk management on the ongoing surveillance and intervention to manage COVID-19 related risks.

No abstract available.

ObjectiveTo estimate associations between covid-19 vaccination and long covid symptoms in adults with SARS-CoV-2 infection before vaccination.DesignObservational cohort study.SettingCommunity dwelling population, UK.Participants28 356 participants in the Office for National Statistics COVID-19 Infection Survey aged 18-69 years who received at least one dose of an adenovirus vector or mRNA covid-19 vaccine after testing positive for SARS-CoV-2 infection.Main outcome measurePresence of long covid symptoms at least 12 weeks after infection over the follow-up period 3 February to 5 September 2021.ResultsMean age of participants was 46 years, 55.6% (n=15 760) were women, and 88.7% (n=25 141) were of white ethnicity. Median follow-up was 141 days from first vaccination (among all participants) and 67 days from second vaccination (83.8% of participants). 6729 participants (23.7%) reported long covid symptoms of any severity at least once during follow-up. A first vaccine dose was associated with an initial 12.8% decrease (95% confidence interval −18.6% to −6.6%, PConclusionsThe likelihood of long covid symptoms was observed to decrease after covid-19 vaccination and evidence suggested sustained improvement after a second dose, at least over the median follow-up of 67 days. Vaccination may contribute to a reduction in the population health burden of long covid, although longer follow-up is needed.

Although most adults infected with SARS-CoV-2 fully recover, a proportion have ongoing symptoms, or post-COVID conditions (PCC), after infection. The objective of this analysis was to estimate the number of US adults with activity-limiting PCC on November 1, 2021.We modeled the prevalence of PCC using reported infections occurring from February 1, 2020 - September 30, 2021, and population-based, household survey data on new activity-limiting symptoms ≥1 month following SARS-CoV-2 infection. From these data sources, we estimated the number and proportion of US adults with activity-limiting PCC on November 1, 2021, as 95% uncertainty intervals, stratified by sex and age. Sensitivity analyses adjusted for under-ascertainment of infections and uncertainty about symptom duration.On November 1, 2021, at least 3.0-5.0 million US adults were estimated to have activity-limiting PCC of ≥1 month duration, or 1.2%-1.9% of US adults. Population prevalence was higher in females (1.4%-2.2%) than males. The estimated prevalence after adjusting for under-ascertainment of infections was 1.7%-3.8%.Millions of US adults were estimated to have activity-limiting PCC. These estimates can support future efforts to address the impact of PCC on the U.S. population.

ObjectivesTo assess whether there is a change in the incidence of cardiac and all-cause death in young people following COVID-19 vaccination or SARS-CoV-2 infection in unvaccinated individuals.DesignSelf-controlled case series.SettingNational, linked electronic health record data in England.Study populationIndividuals aged 12-29 who had received at least one dose of COVID-19 vaccination and died between 8 December 2020 and 2 February 2022 and registered by 16 February 2022 within 12 weeks of COVID-19 vaccination; Individuals aged 12-29 who died within 12 weeks of testing positive for SARS-CoV-2.Main outcome measuresCardiac and all-cause deaths occurring within 12 weeks of vaccination or SARS-CoV-2 infection.ResultsCompared to the baseline period, there was no evidence of a change in the incidence of cardiac death in the six weeks after vaccination, whether for each of weeks 1 to 6 or the whole six-week period. There was a decrease in the risk of all-cause death in the first week after vaccination and no change in each of weeks 2 to 6 after vaccination or whole six-week period after vaccination. Subgroup analyses by sex, age, vaccine type, and last dose also showed no change in the risk of death in the first six weeks after vaccination. There was a large increase in the incidence of cardiac and all-cause death in the overall risk period after SARS-CoV-2 infection among the unvaccinated.ConclusionThere is no evidence of an association between COVID-19 vaccination and an increased risk of death in young people. By contrast, SARS-CoV-2 infection was associated with substantially higher risk of cardiac related death and all-cause death.What is already known on this topicSeveral studies have highlighted the association between COVID-19 vaccination and the risk of myocarditis, myopericarditis, and other cardiac problems, especially in young people, but associated risk of mortality is unclear. Since younger people have lower risk of COVID-19 hospitalisation and mortality, the mortality risk associated with vaccination is potentially more important to them in balancing the risk and benefit of vaccination.What this study addsAlthough there is a risk of myocarditis or myopericarditis with COVID-19, there is no evidence of increased risk of cardiac or all-cause mortality following COVID-19 vaccination in young people aged 12 to 29. Given the increased risk of mortality following SARS-CoV-2 infection in this group, the risk-benefit analysis favours COVID-19 vaccination for this age group.

ObjectiveTo examine socio-demographic disparities in SARS-CoV-2 case rates during the second (Alpha) and third (Delta) waves of the COVID-19 pandemic.DesignRetrospective, population-based cohort study.SettingResident population of England.Participants39,006,194 people aged 10 years and over who were enumerated at the 2011 Census, registered with the National Health Service (NHS) and alive on 1 September 2020.Main outcome measuresTesting positive for SARS-CoV-2 during the second wave (1 September 2020 to 22 May 2021) or third wave (23 May to 10 December 2021) of the pandemic. We calculated age-standardised case rates by socio-demographic characteristics and used logistic regression models to estimate adjusted odds ratios (ORs).ResultsDuring the study period, 5,767,584 individuals tested positive for SARS-CoV-2. In the second wave, the fully-adjusted odds of having a positive test, relative to the White British group, were highest for the Bangladeshi (OR: 1.88, 95% CI 1.86 to 1.90) and Pakistani (1.81, 1.79 to 1.82) ethnic groups. Relative to the Christian group, Muslim and Sikh religious groups had fully-adjusted ORs of 1.58 (1.57 to 1.59) and 1.74 (1.72 to 1.76), respectively. Greater area deprivation, disadvantaged socio-economic position, living in a care home and low English language proficiency were also associated with higher odds of having a positive test. However, the disparities between groups varied over time. Being Christian, White British, non-disabled, and from a more advantaged socio-economic position were all associated with increased odds of testing positive during the third wave.ConclusionThere are large socio-demographic disparities on SARS-CoV-2 cases which have varied between different waves of the pandemic. Research is now urgently needed to understand why these disparities exist to inform policy interventions in future waves or pandemics.What is already known on this topicPeople with pre-existing health conditions or disability, ethnic minority groups, the elderly, some religious groups, people with low socio-economic status, and those living in deprived areas have been disproportionately affected by the COVID-19 pandemic in terms of risk of infection and adverse outcomes.What this study addsUsing linked data on 39 million people in England, we found that during the second wave, COVID-19 case rates were highest among the Bangladeshi and Pakistani ethnic groups, the Muslim religious group, individuals from deprived areas and of low socio-economic position; during the third wave, being Christian, White British, non-disabled, and from a more advantaged socio-economic position were all associated with increased odds of receiving a positive testAdjusting for geographical factors, socio-demographic characteristics, and pre-pandemic health status explained some, but not all, of the excess riskWhen stratifying the dataset by broad age groups, the odds of receiving a positive test remained higher among the Bangladeshi and Pakistani ethnic groups aged 65 years and over during the third wave, which may partly explain the continued elevated mortality rates in these groups

BackgroundIt is unclear whether receiving two COVID-19 vaccinations before SARS-CoV-2 infection reduces the risk of developing Long Covid symptoms. We examined whether the likelihood of symptoms 12 weeks after infection differed by vaccination status.MethodsWe included COVID-19 Infection Survey participants aged 18-69 years who tested positive for SARS-CoV-2 between 26 April 2020 and 30 November 2021; we excluded participants who, before their first test-confirmed infection, had suspected COVID-19 or Long Covid symptoms, or were single-vaccinated. Participants who were double-vaccinated ≥14 days before infection were 1:1 propensity-score matched, based on socio-demographic characteristics and time from infection to follow-up for Long Covid, to those unvaccinated at time of infection. We estimated adjusted odds ratios (aOR) of Long Covid symptoms ≥12 weeks post-infection, comparing double-vaccinated with unvaccinated (reference group) participants.ResultsThe study sample comprised 3,090 double-vaccinated participants (mean age 49 years, 54% female, 92% white, median follow-up from infection 96 days) and matched control participants. Long Covid symptoms were reported by 294 double-vaccinated participants (prevalence 9.5%) compared with 452 unvaccinated participants (14.6%), corresponding to an aOR for Long Covid symptoms of 0.59 (95% CI: 0.50 to 0.69). There was no evidence of heterogeneity by adenovirus vector versus messenger ribonucleic acid vaccines (p=0.25).ConclusionsCOVID-19 vaccination is associated with reduced risk of Long Covid, emphasising the need for public health initiatives to increase population-level vaccine uptake. Longer follow-up is needed, as is the assessment of further vaccine doses and the Omicron variant.

Obesity and ethnicity are known risk factors for COVID-19 outcomes, but their combination has not been extensively examined. We investigate the association between body mass index (BMI) and COVID-19 mortality across different ethnic groups using linked national Census, electronic health records and mortality data for adults in England from the start of pandemic (January 2020) to December 2020. There were 30,067 (0.27%), 1,208 (0.29%), 1,831 (0.29%), 845 (0.18%) COVID-19 deaths in white, Black, South Asian and other ethnic minority groups, respectively. Here we show that BMI was more strongly associated with COVID-19 mortality in ethnic minority groups, resulting in an ethnic risk of COVID-19 mortality that was dependant on BMI. The estimated risk of COVID-19 mortality at a BMI of 40 kg/m2 in white ethnicities was equivalent to the risk observed at a BMI of 30.1 kg/m2, 27.0 kg/m2, and 32.2 kg/m2 in Black, South Asian and other ethnic minority groups, respectively.

ObjectiveTo estimate associations between COVID-19 vaccination and Long Covid symptoms in adults who were infected with SARS-CoV-2 prior to vaccination.DesignObservational cohort study using individual-level interrupted time series analysis.SettingRandom sample from the community population of the UK.Participants28,356 COVID-19 Infection Survey participants (mean age 46 years, 56% female, 89% white) aged 18 to 69 years who received at least their first vaccination after test-confirmed infection.Main outcome measuresPresence of long Covid symptoms at least 12 weeks after infection over the follow-up period 3 February to 5 September 2021.ResultsMedian follow-up was 141 days from first vaccination (among all participants) and 67 days from second vaccination (84% of participants). First vaccination was associated with an initial 12.8% decrease (95% confidence interval: −18.6% to −6.6%) in the odds of Long Covid, but increasing by 0.3% (−0.6% to +1.2%) per week after the first dose. Second vaccination was associated with an 8.8% decrease (−14.1% to −3.1%) in the odds of Long Covid, with the odds subsequently decreasing by 0.8% (−1.2% to −0.4%) per week. There was no statistical evidence of heterogeneity in associations between vaccination and Long Covid by socio-demographic characteristics, health status, whether hospitalised with acute COVID-19, vaccine type (adenovirus vector or mRNA), or duration from infection to vaccination.ConclusionsThe likelihood of Long Covid symptoms reduced after COVID-19 vaccination, and the improvement was sustained over the follow-up period after the second dose. Vaccination may contribute to a reduction in the population health burden of Long Covid, though longer follow-up time is needed.Summary boxWhat is already known on this topicCOVID-19 vaccines are effective at reducing rates of SARS-CoV-2 infection, transmission, hospitalisation, and deathThe incidence of Long Covid may be reduced if infected after vaccination, but the relationship between vaccination and pre-existing long COVID symptoms is unclear, as published studies are generally small and with self-selected participantsWhat this study addsThe likelihood of Long Covid symptoms reduced after COVID-19 vaccination, and the improvement was sustained over the follow-up period after the second doseThere was no evidence of differences in this relationship by socio-demographic characteristics, health-related factors, vaccine type, or duration from infection to vaccinationAlthough causality cannot be inferred from this observational evidence, vaccination may contribute to a reduction in the population health burden of Long Covid; further research is needed to understand the biological mechanisms that may ultimately contribute to the development of therapeutics for Long Covid

BackgroundMonitoring differences in COVID-19 vaccination uptake in different groups is crucial to help inform the policy response to the pandemic. A key gap is the absence of data on uptake by occupation.MethodsUsing nationwide population-level data, we calculated the proportion of people who had received two doses of a COVID-19 vaccine (assessed on 31 August 2021) by detailed occupational categories in adults aged 40-64 and estimated adjusted odds ratios to examine whether these differences were driven by occupation or other factors, such as education. We also examined whether vaccination rates differed by ability to work from home.ResultsOur study population included 14,298,147 adults 40-64. Vaccination rates differed markedly by occupation, being higher in administrative and secretarial occupations (90.8%); professional occupations (90.7%); and managers, directors and senior officials (90.6%); and lowest (83.1%) in people working in elementary occupations. We found substantial differences in vaccination rates looking at finer occupational groups even after adjusting for confounding factors, such as education. Vaccination rates were higher in occupations which can be done from home and lower in those which cannot. Many occupations with low vaccination rates also involved contact with the public or with vulnerable peopleConclusionsIncreasing vaccination coverage in occupations with low vaccination rates is crucial to help protecting the public and control infection, especially in occupations that cannot be done from home and involve contacts with the public. Policies such as ‘work from home if you can’ may only have limited future impact on hospitalisations and deathsWhat is already known on this subject?Whilst several studies highlight differences in vaccination coverage by ethnicity, religion, socio-demographic factors and certain underlying health conditions, there is very little evidence on how vaccination coverage varies by occupation, in the UK and elsewhere. The few study looking at occupational differences in vaccine hesitancy focus on healthcare workers or only examined broad occupational groups. There is currently no large-scale study on occupational differences in COVID-19 vaccination coverage in the UK.What this study adds?Using population-level linked data combining the 2011 Census, primary care records, mortality and vaccination data, we found that the vaccination rates of adults aged 40 to 64 years in England differed markedly by occupation. Vaccination rates were high in administrative and secretarial occupations, professional occupations and managers, directors and senior officials and low in people working in elementary occupations. Adjusting for other factors likely to be linked to occupation and vaccination, such as education, did not substantially alter the results. Vaccination rates were also associated with the ability to work from home, with the vaccination rate being higher in occupations which can be done performed from home. Policies aiming to increase vaccination rates in occupations that cannot be done from home and involve contacts with the public should be priorities

Background Updatable estimates of COVID-19 onset, progression, and trajectories underpin pandemic mitigation efforts. To identify and characterise disease trajectories, we aimed to define and validate ten COVID-19 phenotypes from nationwide linked electronic health records (EHR) using an extensible framework. Methods In this cohort study, we used eight linked National Health Service (NHS) datasets for people in England alive on Jan 23, 2020. Data on COVID-19 testing, vaccination, primary and secondary care records, and death registrations were collected until Nov 30, 2021. We defined ten COVID-19 phenotypes reflecting clinically relevant stages of disease severity and encompassing five categories: positive SARS-CoV-2 test, primary care diagnosis, hospital admission, ventilation modality (four phenotypes), and death (three phenotypes). We constructed patient trajectories illustrating transition frequency and duration between phenotypes. Analyses were stratified by pandemic waves and vaccination status. Findings Among 57 032 174 individuals included in the cohort, 13 990 423 COVID-19 events were identified in 7 244 925 individuals, equating to an infection rate of 12·7% during the study period. Of 7 244 925 individuals, 460 737 (6·4%) were admitted to hospital and 158 020 (2·2%) died. Of 460 737 individuals who were admitted to hospital, 48 847 (10·6%) were admitted to the intensive care unit (ICU), 69 090 (15·0%) received non-invasive ventilation, and 25 928 (5·6%) received invasive ventilation. Among 384 135 patients who were admitted to hospital but did not require ventilation, mortality was higher in wave 1 (23 485 [30·4%] of 77 202 patients) than wave 2 (44 220 [23·1%] of 191 528 patients), but remained unchanged for patients admitted to the ICU. Mortality was highest among patients who received ventilatory support outside of the ICU in wave 1 (2569 [50·7%] of 5063 patients). 15 486 (9·8%) of 158 020 COVID-19-related deaths occurred within 28 days of the first COVID-19 event without a COVID-19 diagnoses on the death certificate. 10 884 (6·9%) of 158 020 deaths were identified exclusively from mortality data with no previous COVID-19 phenotype recorded. We observed longer patient trajectories in wave 2 than wave 1. Interpretation Our analyses illustrate the wide spectrum of disease trajectories as shown by differences in incidence, survival, and clinical pathways. We have provided a modular analytical framework that can be used to monitor the impact of the pandemic and generate evidence of clinical and policy relevance using multiple EHR sources. Funding British Heart Foundation Data Science Centre, led by Health Data Research UK.

IntroductionThe coronavirus pandemic has been particularly severe in the UK, with high infection and death rates, including among working age population.ObjectiveTo estimate occupational differences in COVID-19 mortality, taking into account confounding factors, such as regional differences, ethnicity, education, deprivation and pre-pandemic health.MethodsWe used data on 14,295,900 individuals who completed the UK Census in 2011, who were alive on 24 January 2020, were employed and aged 31–55 years in 2011. Data were linked to death and other health records. We examined differences between occupational groups in the risk of COVID-19 death from 24 January to 28 December 2020. We estimated age-standardised mortality rates per 100,000 person-years at risk stratified by sex and occupations. To estimate the effect of occupation due to work-related exposures, we used Cox proportional hazard models to adjust for confounding factors.ResultsThere is wide variation between occupations in COVID-19 mortality. Several occupations, particularly those involving contact with patients or the public, show three- or four-fold risks. These elevated risks were greatly attenuated after adjustment for confounding and mediating factors. For example, the hazard ratio (HR) for men working as taxi and cab drivers or chauffeurs changed from 4.60 [95%CI 3.62–5.84] to 1.47 [1.14–1.89] after adjustment. The overall HR for men working in essential occupations compared with men in non-essential occupations changed from 1.45 [1.34 - 1.56] to 1.22 [1.13 - 1.32] after adjustment. For most occupations, confounding and other mediating factors explained about 70% to 80% of the age-adjusted hazard ratios.ConclusionsWorking conditions are likely to play a role in COVID-19 mortality, particularly in occupations involving contact with COVID-19 patients or the public. However, there is also a substantial contribution from non-workplace factors, including regional factors, socio-demographic factors, and pre-pandemic health.

BackgroundThe UK began an ambitious COVID-19 vaccination programme on 8th December 2020. This study describes variation in vaccination coverage by sociodemographic characteristics between December 2020 and August 2021.MethodsUsing population-level administrative records linked to the 2011 Census, we estimated monthly first dose vaccination rates by age group and sociodemographic characteristics amongst adults aged 18 years or over in England. We also present a tool to display the results interactively.FindingsOur study population included 35,223,466 adults. A lower percentage of males than females were vaccinated in the young and middle age groups (18-59 years) but not in the older age groups. Vaccination rates were highest among individuals of White British and Indian ethnic backgrounds and lowest among Black Africans (aged ≥80 years) and Black Caribbeans (18-79 years). Differences by ethnic group emerged as soon as vaccination roll-out commenced and widened over time. Vaccination rates were also lower among individuals who identified as Muslim, lived in more deprived areas, reported having a disability, did not speak English as their main language, lived in rented housing, belonged to a lower socio-economic group, and had fewer qualifications.InterpretationWe found inequalities in COVID-19 vaccination rates by sex, ethnicity, religion, area deprivation, disability status, English language proficiency, socio-economic position, and educational attainment, but some of these differences varied by age group. Research is urgently needed to understand why these inequalities exist and how they can be addressed.Research in contextEvidence before this studyWe searched PubMed for publications on sociodemographic inequalities in COVID-19 vaccination coverage. Several studies have reported differences in coverage by characteristics such as ethnicity and religion, however these have focused on older adults and the clinically vulnerable who were initially prioritized for vaccination. There is little evidence on sociodemographic inequalities in vaccination coverage among younger adults and evidence is also lacking on coverage by a wider range of characteristics such as sex, disability status, English language proficiency, socio-economic position, and educational attainment.Added value of this studyThis study provides the first evidence for sociodemographic inequalities in COVID-19 vaccination coverage among the entire adult population in England, using population-level administrative records linked to the 2011 Census. By disaggregating the data by age group, we were able to show that disparities in coverage by some sociodemographic characteristics differed by age group. For example, a lower proportion of males than females were vaccinated in the young and middle age groups (18-59 years) but not in the older age groups, and vaccination rates were lowest among Black Africans in those aged ≥80 years but lowest among Black Caribbeans for all other age groups. Vaccination rates were also lower among individuals who identified as Muslim, lived in more deprived areas, reported having a disability, did not speak English as their main language, lived in rented housing, belonged to a lower socio-economic group, and had fewer qualifications.Implications of all the available evidenceMany of the groups with the lowest rates of COVID-19 vaccination are also the groups that have been disproportionately affected by the pandemic, including severe illness and mortality. Research is urgently needed to understand why these disparities exist and how they can be addressed, for example through public health or community engagement programmes. Since the relationships between sociodemographic characteristics and vaccination coverage may differ by age group, it is important for future research to disaggregate by age group when examining these inequalities.

ImportanceObesity and ethnicity are well characterised risk factors for severe COVID-19 outcomes, but the differential effects of obesity on COVID-19 outcomes by race/ethnicity has not been examined robustly in the general population.ObjectiveTo investigate the association between body mass index (BMI) and COVID-19 mortality across different ethnic groups.Design, Setting, and ParticipantsThis is a retrospective cohort study using linked national Census, electronic health records and mortality data for English adults aged 40 years or older who were alive at the start of pandemic (24th January 2020).ExposuresBMI obtained from electronic health records. Self-reported ethnicity (white, black, South Asian, other) was the effect-modifying variable.Main Outcomes and MeasuresCOVID-19 related death identified by ICD-10 codes U07.1 or U07.2 mentioned on the death certificate from 24th January 2020 until December 28th 2020.ResultsThe analysis included white (n = 11,074,708; mean age 61.9 [±13.4] years; 54% women), black (n = 416,542; 56.4 [±11.7] years; 57% women), South Asian (621,691; 55.7 [±12.4] years; 51% women) and other (n = 478,196; 55.3 [±11.6] years; 55% women) ethnicities with linked BMI data. The association between BMI and COVID-19 mortality was stronger in ethnic minority groups. Compared to a BMI of 22.5 kg/m2 in white ethnicities, the adjusted HR for COVID-19 mortality at a BMI of 30 kg/m2 in white, black, South Asian and other ethnicities was 0.95 (95% CI: 0.87-1.03), 1.72 (1.52-1.94), 2.00 (1.78-2.25) and 1.39 (1.21-1.61), respectively. The estimated risk of COVID-19 mortality at a BMI of 40 kg/m2 in white ethnicities (HR = 1.73) was equivalent to the risk observed at a BMI of 30.1 kg/m2, 27.0 kg/m2, and 32.2 kg/m2 in black, South Asian and other ethnic groups, respectively.ConclusionsThis population-based study using linked Census and electronic health care records demonstrates that the risk of COVID-19 mortality associated with obesity is greater in ethnic minority groups compared to white populations.QuestionDoes the association between BMI and COVID-19 mortality vary by ethnicity?FindingsIn this study of 12.6 million adults, BMI was associated with COVID-19 in all ethnicities, but with stronger associations in ethnic minority populations such that the risk of COVID-19 mortality for a BMI of 40 kg/m2 in white ethnicities was observed at a BMI of 30.1 kg/m2, 27.0 kg/m2, and 32.2 kg/m2 in black, South Asian and other ethnicities, respectively.MeaningBMI is a stronger risk factor for COVID-19 mortality in ethnic minorities. Obesity management is therefore a priority in these populations.

ObjectiveTo estimate occupational differences in COVID-19 mortality, and test whether these are confounded by factors, such as regional differences, ethnicity and education or due to non-workplace factors, such as deprivation or pre-pandemic health.DesignRetrospective cohort studySettingPeople living in private households EnglandParticipants14,295,900 people aged 40-64 years (mean age 52 years, 51% female) who were alive on 24 January 2020, living in private households in England in 2019, were employed in 2011, and completed the 2011 census.Main outcome measuresCOVID-19 related death, assessed between 24 January 2020 and 28 December 2020. We estimated age-standardised mortality rates per 100,000 person-years at risk (ASMR) stratified by sex and occupations. To estimate the effect of occupation due to work-related exposures, we used Cox proportional hazard models to adjust for confounding (region, ethnicity, education), as well as non-workplace factors that are related to occupation.ResultsThere is wide variation between occupations in COVID-19 mortality. Several occupations, particularly those involving contact with patients or the public, show three-fold or four-fold risks. These elevated risks were greatly attenuated after adjustment for confounding and mediating non-workplace factors. For example, the hazard ratio (HR) for men working as taxi and cab drivers or chauffeurs changed from 4.60 [95%CI 3.62-5.84] to 1.47 [1.14-1.89] after adjustment. More generally, the overall HR for men working in essential occupations compared with men in non-essential occupations changed from 1.45 [1.34 - 1.56] to 1.22 [1.13 - 1.32] after adjustment. For most occupations, confounding and other mediating factors explained about 70% to 80% of the age-adjusted hazard ratios.ConclusionsWorking conditions are likely to play a role in COVID-19 mortality, particularly in occupations involving contact with COVID-19 patients or the public. However, there is also a substantial contribution from non-workplace factors, including regional factors, socio-demographic factors, and pre-pandemic health.

ObjectiveTo examine inequalities in COVID-19 vaccination rates amongst elderly adults in EnglandDesignCohort studySettingPeople living in private households and communal establishments in EnglandParticipants6,829,643 adults aged ≥ 70 years (mean 78.7 years, 55.2% female) who were alive on 15 March 2021.Main outcome measuresHaving received the first dose of a vaccine against COVID-19 by 15 March 2021. We calculated vaccination rates and estimated unadjusted and adjusted odds ratios using logistic regression models.ResultsBy 15 March 2021, 93.2% of people living in England aged 70 years and over had received at least one dose of a COVID-19 vaccine. While vaccination rates differed across all factors considered apart from sex, the greatest disparities were seen between ethnic and religious groups. The lowest rates were in people of Black African and Black Caribbean ethnic backgrounds, where only 67.2% and 73.9% had received a vaccine, with adjusted odds of not being vaccinated at 5.01 (95% CI 4.86 - 5.16) and 4.85 (4.75 - 4.96) times greater than the White British group. The proportion of individuals self-identifying as Muslim and Buddhist who had received a vaccine was 79.1% and 84.1%, respectively. Older age, greater area deprivation, less advantaged socio-economic position (proxied by living in a rented home), being disabled and living either alone or in a multi-generational household were also associated with higher odds of not having received the vaccine.ConclusionPeople disproportionately affected seem most hesitant to COVID-19 vaccinations. Policy Interventions to improve these disparities are urgently needed.Summary BoxWhat is already known on this subject?The UK began an ambitious vaccination programme to combat the COVID-19 pandemic on 8th December 2020. Existing evidence suggests that COVID-19 vaccination rates differ by level of area deprivation, ethnicity and certain underlying health conditions, such as learning disability and mental health problems.What does this study add?Our study shows that first dose vaccination rates in adults aged 70 or over differed markedly by ethnic group and self-reported religious affiliation, even after adjusting for geography, socio-demographic factors and underlying health conditions. Our study also highlights differences in vaccination rates by deprivation, household composition, and disability status, factors disproportionately associated with SARS-CoV-2 infection. Public health policy and community engagement aimed at promoting vaccination uptake is these groups are urgently needed.Strengths and limitations of this studyUsing nationwide linked population-level data from clinical records and the 2011 Census, we examined a wide range of socio-demographic characteristics not available n electronic health recordsMost demographic and socio-economic characteristics are derived from the 2011 Census and therefore are 10 years old. However, we focus primarily on characteristics that are unlikely to change over time, such as ethnicity or religion, or likely to be stable for our populationBecause the data are based on the 2011 Census, it excluded people living in England in 2011 but not taking part in the 2011 Census; respondents who could not be linked to the 2011-2013 NHS patients register; recent migrants. Consequently, we excluded 5.4% of vaccinated people who could not be linked

ObjectiveTo quantify rates of organ specific dysfunction in individuals with covid-19 after discharge from hospital compared with a matched control group from the general population.DesignRetrospective cohort study.SettingNHS hospitals in England.Participants47 780 individuals (mean age 65, 55% men) in hospital with covid-19 and discharged alive by 31 August 2020, exactly matched to controls from a pool of about 50 million people in England for personal and clinical characteristics from 10 years of electronic health records.Main outcome measuresRates of hospital readmission (or any admission for controls), all cause mortality, and diagnoses of respiratory, cardiovascular, metabolic, kidney, and liver diseases until 30 September 2020. Variations in rate ratios by age, sex, and ethnicity.ResultsOver a mean follow-up of 140 days, nearly a third of individuals who were discharged from hospital after acute covid-19 were readmitted (14 060 of 47 780) and more than 1 in 10 (5875) died after discharge, with these events occurring at rates four and eight times greater, respectively, than in the matched control group. Rates of respiratory disease (Pv4.6 (4.3 to 4.8) for age ≥70, and 11.4 (9.8 to 13.3) for non-whitev5.2 (5.0 to 5.5) for white individuals).ConclusionsIndividuals discharged from hospital after covid-19 had increased rates of multiorgan dysfunction compared with the expected risk in the general population. The increase in risk was not confined to the elderly and was not uniform across ethnicities. The diagnosis, treatment, and prevention of post-covid syndrome requires integrated rather than organ or disease specific approaches, and urgent research is needed to establish the risk factors.

ObjectivesThe epidemiology of post-COVID syndrome (PCS) is currently undefined. We quantified rates of organ-specific impairment following recovery from COVID-19 hospitalisation compared with those in a matched control group, and how the rate ratio (RR) varies by age, sex, and ethnicity.DesignObservational, retrospective, matched cohort study.SettingNHS hospitals in England.Participants47,780 individuals (mean age 65 years, 55% male) in hospital with COVID-19 and discharged alive by 31 August 2020, matched to controls on demographic and clinical characteristics.Outcome measuresRates of hospital readmission, all-cause mortality, and diagnoses of respiratory, cardiovascular, metabolic, kidney and liver diseases until 30 September 2020.ResultsMean follow-up time was 140 days for COVID-19 cases and 153 days for controls. 766 (95% confidence interval: 753 to 779) readmissions and 320 (312 to 328) deaths per 1,000 person-years were observed in COVID-19 cases, 3.5 (3.4 to 3.6) and 7.7 (7.2 to 8.3) times greater, respectively, than in controls. Rates of respiratory, diabetes and cardiovascular events were also significantly elevated in COVID-19 cases, at 770 (758 to 783), 127 (122 to 132) and 126 (121 to 131) events per 1,000 person-years, respectively. RRs were greater for individuals aged ConclusionsIndividuals discharged from hospital following COVID-19 face elevated rates of multi-organ dysfunction compared with background levels, and the increase in risk is neither confined to the elderly nor uniform across ethnicities. The diagnosis, treatment and prevention of PCS require integrated rather than organ- or disease-specific approaches. Urgent research is required to establish risk factors for PCS.

BackgroundCOVID-19 mortality risk is associated with demographic and behavioural factors; furthermore, religious gatherings have been linked with the spread of COVID-19. We sought to understand the variation in risk of COVID-19-related death across religious groups in England and Wales both before and after the first national lockdown.MethodsWe conducted a retrospective cohort study of usual residents in England and Wales enumerated at the 2011 Census (n=47 873 294, estimated response rate 94%) for risk of death involving COVID-19 using linked death certificates. Cox regression models were estimated to compare risks between religious groups. Time-dependent coefficients were added to the model allowing HRs before and after lockdown period to be estimated separately.ResultsCompared with Christians, all religious groups had an elevated risk of death involving COVID-19; the largest age-adjusted HRs were for Muslim and Jewish males at 2.5 (95% CI 2.3 to 2.7) and 2.1 (95% CI 1.9 to 2.5), respectively. The corresponding HRs for Muslim and Jewish females were 1.9 (95% CI 1.7 to 2.1) and 1.5 (95% CI 1.7 to 2.1), respectively. The difference in risk between groups contracted after lockdown. Those who affiliated with no religion had the lowest risk of COVID-19-related death before and after lockdown.ConclusionThe majority of the variation in COVID-19 mortality risk was explained by controlling for sociodemographic and geographic determinants; however, those of Jewish affiliation remained at a higher risk of death compared with all other groups. Lockdown measures were associated with reduced differences in COVID-19 mortality rates between religious groups; further research is required to understand the causal mechanisms.

There are important differences in the risk of SARS-CoV-2 infection and death depending on occupation. Infections in healthcare workers have received the most attention, and there are clearly increased risks for intensive care unit workers who are caring for COVID-19 patients. However, a number of other occupations may also be at an increased risk, particularly those which involve social care or contact with the public. A large number of data sets are available with the potential to assess occupational risks of COVID-19 incidence, severity, or mortality. We are reviewing these data sets as part of the Partnership for Research in Occupational, Transport, Environmental COVID Transmission (PROTECT) initiative, which is part of the National COVID-19 Core Studies. In this report, we review the data sets available (including the key variables on occupation and potential confounders) for examining occupational differences in SARS-CoV-2 infection and COVID-19 incidence, severity and mortality. We also discuss the possible types of analyses of these data sets and the definitions of (occupational) exposure and outcomes. We conclude that none of these data sets are ideal, and all have various strengths and weaknesses. For example, mortality data suffer from problems of coding of COVID-19 deaths, and the deaths (in England and Wales) that have been referred to the coroner are unavailable. On the other hand, testing data is heavily biased in some periods (particularly the first wave) because some occupations (e.g. healthcare workers) were tested more often than the general population. Random population surveys are, in principle, ideal for estimating population prevalence and incidence, but are also affected by non-response. Thus, any analysis of the risks in a particular occupation or sector (e.g. transport), will require a careful analysis and triangulation of findings across the various available data sets.

Less schooling is associated with increased biological risks for chronic disease, but whether increasing years of schooling through policy interventions reduces these risks remains unclear. We examine the effect of a major education reform introduced in 1959 that raised the minimum school leaving age from 14 to 16 years in France, offering a unique natural experiment. We assess the causal impact of increased schooling duration on 16 biomarkers of cardiovascular, metabolic, organ and immune function in a large cohort of men and women born around 1953. Using a Regression Discontinuity Design, we find that the reform led to a significant increase in schooling duration among children from disadvantaged families; but longer schooling did not translate into better biomarker profiles in adulthood. Eligibility to the reform had no impact on the biomarker profile of respondents from intermediate or high social class families, while it led to increased blood pressure and white cells counts in adulthood among those from low parental social class. These findings were robust across several sensitivity analyses. They emphasize the importance of considering the institutional context and the respondents' social origins when evaluating the health effects of compulsory schooling reforms. Our results do not necessarily question the premise that education leads to better health, but they suggest that law-mandated increases in schooling alone may not improve the health of disadvantaged groups.

In this paper, we examine whether longer compulsory schooling has a causal effect on mental health, exploiting a 1972 reform which raised the minimum school leaving age from age 15 to 16 in Great Britain. Using a regression discontinuity design, we find that the reform did not improve mental health. We provide evidence that extending the duration of compulsory schooling impacts mental health through channels other than increased educational attainment. We argue that these effects may mitigate or offset the health returns to increased educational attainment.

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