Search

ObjectiveTo examine sociodemographic inequalities in people with SARS-CoV-2 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 older who were enumerated in the 2011 census, registered with the NHS, and alive on 1 September 2020.Main outcome measuresAge standardised SARS-CoV-2 case rates (ie, the number of people who received a positive test result per 100 000 person weeks at risk) during the second wave (1 September 2020 to 22 May 2021) or third wave (23 May to 10 December 2021) of the pandemic. Age standardised rates were calculated by sociodemographic characteristics and adjusted rate ratios were estimated using generalised linear regression models with a Poisson distribution (models were adjusted for covariates including sex, age, geographical variables, and sociodemographic characteristics).ResultsDuring the study period, 5 767 584 people (14.8% of the study population) tested positive for SARS-CoV-2. In the second wave, the fully adjusted relative risks of having a positive test were highest for the Bangladeshi and Pakistani ethnic groups compared with the white British group, with rate ratios of 1.75 (95% confidence interval 1.73 to 1.77) and 1.69 (1.68 to 1.70), respectively. Muslim and Sikh religious groups had fully adjusted rate ratios of 1.51 (1.50 to 1.51) and 1.64 (1.63 to 1.66), respectively, compared with the Christian group. Greater area deprivation, disadvantaged socioeconomic position, living in a care home, and low English language proficiency were also associated with higher relative risk of having a positive test. However, the inequalities among groups varied over time. Being Christian, white British, without a disability, and from a more advantaged socioeconomic position were associated with increased relative risk of testing positive during the third wave.ConclusionResearch is urgently needed to understand the large sociodemographic inequalities in SARS-CoV-2 case rates in order to inform policy interventions in future waves or pandemics.

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.

BackgroundEstimating real-world vaccine effectiveness is vital to assess the impact of the vaccination programme on the pandemic and inform the ongoing policy response. However, estimating vaccine effectiveness using observational data is inherently challenging because of the non-randomised design and the potential for unmeasured confounding.MethodsWe used a Regression Discontinuity Design (RDD) to estimate vaccine effectiveness against COVID-19 mortality in England, exploiting the discontinuity in vaccination rates resulting from the UK’s age-based vaccination priority groups. We used the fact that people aged 80 or over were prioritised for the vaccine roll-out in the UK to compare the risk of COVID-19 and non-COVID-19 death in people aged 75–79 and 80–84.FindingsThe prioritisation of vaccination of people aged 80 or above led to a large discrepancy in vaccination rates in people 80–84 compared to those 75–79 at the beginning of the vaccination campaign. We found a corresponding difference in COVID-19 mortality, but not in non-COVID-19 mortality, suggesting that our approach appropriately addresses the issue of unmeasured confounding factors. Our results suggest that the first vaccine dose reduced the risk of COVID-19 death by 52.6% (95% Cl 26.6–84.2) in those aged 80.InterpretationsOur results support existing evidence that a first dose of a COVID-19 vaccine has a strong protective effect against COVID-19 mortality in older adults. The RDD estimate of vaccine effectiveness is comparable to previously published studies using different methods, suggesting that unmeasured confounding factors are unlikely to substantially bias these studies.FundingOffice for National Statistics.Research in ContextEvidence before this studyWe searched PubMed for studies reporting on the ‘real-world’ effectiveness of the COVID-19 vaccination on risk of death using terms such as “COVID-19”, “vaccine effectiveness”, “mortality” and “death”. The relevant published studies on this topic report vaccine effectiveness estimates against risk of death ranging from 64.2% to 98.7%, for varying times post-vaccination. All of these are observational studies and therefore potentially subject to bias from unmeasured confounding. We found no studies that used a quasi-experimental method such as regression discontinuity design, which is not subject to bias from unmeasured confounding, to calculate the effectiveness of the COVID-19 vaccination on risk of COVID-19 death, or on other outcomes such as hospitalisation or infection.Added value of this studyThe estimates of vaccine effectiveness based on observational data may be biased by unmeasured confounding. This study uses a regression discontinuity design to estimate vaccine effectiveness, exploiting the fact that the vaccination campaign in the UK was rolled out following age-based priority groups. This enables the calculation of an unbiased estimate of the effectiveness of the COVID-19 vaccine against risk of death.The vaccine effectiveness estimate of 52.6% (95% Cl 26.6–84.2) is slightly lower but similar to previously published estimates, therefore suggesting that these estimates are not substantially affected by unmeasured confounding factors and confirming the effectiveness of the COVID-19 vaccine against risk of COVID-19 death.Implications of all the available evidenceObtaining an unbiased estimate of COVID-19 vaccine effectiveness is of vital importance in informing policy for lifting COVID-19 related measures. The regression discontinuity design provides confidence that the existing estimates from observational studies are unlikely to be substantially biased by unmeasured confounding.

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.

Large reductions in emergency department attendances and hospitalisations with non-COVID acute medical illness early during the pandemic were attributed to reluctance to seek medical help and higher referral thresholds. Here, we compare acute medical admissions with a comparison cohort from 2017. Deaths in the same geographic area were examined, and Wales-wide deaths during these 4 weeks in 2020 were compared with a seasonally matched period in 2019. There were 528 patients admitted with non-COVID illness in 2020, versus 924 in 2017 (a reduction of 43%). Deaths from non-COVID causes increased by 10.9% compared with 2017, over half this rise being from neurological causes including stroke and dementia. While far fewer patients required hospitalisation as medical emergencies, rises in local non-COVID deaths proved small. Wales-wide non-COVID deaths rose by just 1% compared with 2019. The findings suggest that changes in population behaviour and lifestyle during lockdown brought about unforeseen health benefits.

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.

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.

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.

ObjectiveTo examine inequalities in COVID-19 vaccination rates among elderly adults in England.DesignCohort study.SettingPeople living in private households and communal establishments in England.Participants6 655 672 adults aged ≥70 years (mean 78.8 years, 55.2% women) 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 ORs 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 73.8% had received a vaccine, with adjusted odds of not being vaccinated at 5.01 (95% CI 4.86 to 5.16) and 4.85 (4.75 to 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 socioeconomic position (proxied by living in a rented home), being disabled and living either alone or in a multigenerational household were also associated with higher odds of not having received the vaccine.ConclusionResearch is now urgently needed to understand why disparities exist in these groups and how they can best be addressed through public health policy and community engagement.

BackgroundEthnic minorities have experienced disproportionate COVID-19 mortality rates in the UK and many other countries. We compared the differences in the risk of COVID-19 related death between ethnic groups in the first and second waves the of COVID-19 pandemic in England. We also investigated whether the factors explaining differences in COVID-19 death between ethnic groups changed between the two waves.MethodsUsing data from the Office for National Statistics Public Health Data Asset on individuals aged 30-100 years living in private households, we conducted an observational cohort study to examine differences in the risk of death involving COVID-19 between ethnic groups in the first wave (from 24th January 2020 until 31st August 2020) and second wave (from 1st September to 28th December 2020). We estimated age-standardised mortality rates (ASMR) in the two waves stratified by ethnic groups and sex. We also estimated hazard ratios (HRs) for ethnic-minority groups compared with the White British population, adjusted for geographical factors, socio-demographic characteristics, and pre-pandemic health conditions.ResultsThe study population included over 28.9 million individuals aged 30-100 years living in private households. In the first wave, all ethnic minority groups had a higher risk of COVID-19 related death compared to the White British population. In the second wave, the risk of COVID-19 death remained elevated for people from Pakistani (ASMR: 339.9 [95% CI: 303.7 – 376.2] and 166.8 [141.7 – 191.9] deaths per 100,000 population in men and women) and Bangladeshi (318.7 [247.4 – 390.1] and 127.1 [91.1 – 171.3] in men and women)background but not for people from Black ethnic groups. Adjustment for geographical factors explained a large proportion of the differences in COVID-19 mortality in the first wave but not in the second wave. Despite an attenuation of the elevated risk of COVID-19 mortality after adjusting for sociodemographic characteristics and health status, the risk was substantially higher in people from Bangladeshi and Pakistani background in both the first and the second waves.ConclusionBetween the first and second waves of the pandemic, the reduction in the difference in COVID-19 mortality between people from Black ethnic background and people from the White British group shows that ethnic inequalities in COVID-19 mortality can be addressed. The continued higher rate of mortality in people from Bangladeshi and Pakistani background is alarming and requires focused public health campaign and policy changes.*VN and NI contributed equally to this paperResearch in contextEvidence before this studyA recent systematic review by Pan and colleagues demonstrated that people of ethnic minority background in the UK and the USA have been disproportionately affected by the Coronavirus (COVID-19) pandemic, compared to White populations. While several studies have investigated whether adjusting for socio-demographic and economic factors and medical history reduces the estimated difference in risk of mortality and hospitalisation, the reasons for the differences in the risk of experiencing harms from COVID-19 are still being explored during the course of the pandemic. Studies so far have analysed the ethnic differences in COVID-19 mortality in the first wave of the pandemic. The evidence on the temporal trend of ethnic inequalities in COVID-19 mortality, especially those from the second wave of the pandemic, is scarce.Added value of this studyUsing data from the Office for National Statistics (ONS) Public Health Data Asset on 29 million adults aged 30-100 years living in private households in England, we conducted an observational cohort study to examine the differences in the risk of death involving COVID-19 between ethnic groups in the first wave (from 24th January 2020 until 31st August 2020) and second wave (from 1st September to 28th December 2020). We find that in the first wave all ethnic minority groups were at elevated risk of COVID-19 related death compared to the White British population. In the second wave, the differences in the risk of COVID-19 related death attenuated for Black African and Black Caribbean groups, remained substantially higher in people from Bangladeshi background, and worsened in people from Pakistani background. We also find that some of the factors explaining these differences in mortality have changed in the two waves.Implications of all the available evidenceThe risk of COVID-19 mortality during the first wave of the pandemic was elevated in people from ethnic minority background. An appreciable reduction in the difference in COVID-19 mortality in the second wave of the pandemic between people from Black ethnic background and people from the White British group is reassuring, but the continued higher rate of mortality in people from Bangladeshi and Pakistani background is alarming and requires focused public health campaign and policy response. Focusing on treating underlying conditions, although important, may not be enough in reducing the inequalities in COVID-19 mortality. Focused public health policy as well as community mobilisation and participatory public health campaign involving community leaders may help reduce the existing and widening inequalities in COVID-19 mortality.

ObjectivesTo assess the association between self-reported disability and deaths involving COVID-19 among adults in England.DesignCohort study of >29 million adults using data from the Office for National Statistics Public Health Data Asset.SettingPeople living in private households or communal establishments (including care homes) in England.Participants29,293,845 adults (47% male) aged 30-100 years (mean age = 56) present at the 2011 Census who were alive on 24 January 2020. The main exposure was self-reported disability from the 2011 Census.Main outcome measuresDeath involving COVID-19, occurring between 24 January 2020 and 28 February 2021. We estimated the age-standardised mortality rate per 100,000 person-years at-risk, stratified by sex, disability status, and wave of the pandemic. We calculated hazard ratios (HRs) for disabled people compared with non-disabled people, adjusted for geographical factors, socio-demographic characteristics, and pre-pandemic health conditions.ResultsDisabled people made up 17% of the study population, including 7% who were ‘more-disabled’ and 10% ‘less-disabled’. From 24 January 2020 to 28 February 2021, 105,213 people died from causes involving COVID-19 in England, 58% of whom were disabled. Age-adjusted analyses showed that, compared to non-disabled people, mortality involving COVID-19 was higher among both more-disabled people (HR=3.05, 95% CI: 2.98 to 3.11 in males; 3.48, 3.41 to 3.56 in females) and less-disabled people (HR=1.88, 95% CI: 1.84 to 1.92 in males; 2.03, 1.98 to 2.08 in females). Among people aged 30-69, HRs reached 8.47 (8.01 to 8.95) among more-disabled females and 5.42 (5.18 to 5.68) for more-disabled males. Sequential adjustment for residence type, geography, socio-demographics, and health conditions partly explained the associations, indicating that a combination of these factors contributed towards the increased risk.ConclusionDisabled people in England had markedly increased risk of mortality involving COVID-19 compared to non-disabled people and should be prioritised within the pandemic response.

BackgroundEthnic minorities have experienced disproportionate COVID-19 mortality rates. We estimated associations between household composition and COVID-19 mortality in older adults (≥ 65 years) using a newly linked census-based dataset, and investigated whether living in a multi-generational household explained some of the elevated COVID-19 mortality amongst ethnic minority groups.MethodsUsing retrospective data from the 2011 Census linked to Hospital Episode Statistics (2017-2019) and death registration data (up to 27th July 2020), we followed adults aged 65 years or over living in private households in England from 2 March 2020 until 27 July 2020 (n=10,078,568). We estimated hazard ratios (HRs) for COVID-19 death for people living in a multi-generational household compared with people living with another older adult, adjusting for geographical factors, socio-economic characteristics and pre-pandemic health. We conducted a causal mediation analysis to estimate the proportion of ethnic inequalities explained by living in a multi-generational household.ResultsLiving in a multi-generational household was associated with an increased risk of COVID-19 death. After adjusting for confounding factors, the HRs for living in a multi-generational household with dependent children were 1.13 [95% confidence interval 1.01-1.27] and 1.17 [1.01-1.35] for older males and females. The HRs for living in a multi-generational household without dependent children were 1.03 [0.97 - 1.09] for older males and 1.22 [1.12 - 1.32] for older females. Living in a multi-generational household explained between 10% and 15% of the elevated risk of COVID-19 death among older females from South Asian background, but very little for South Asian males or people in other ethnic minority groups.ConclusionOlder adults living with younger people are at increased risk of COVID-19 mortality, and this is a notable contributing factor to the excess risk experienced by older South Asian females compared to White females. Relevant public health interventions should be directed at communities where such multi-generational households are highly prevalent.FundingThis research was funded by the Office for National Statistics.

Background We estimated population-level associations between ethnicity and coronavirus disease 2019 (COVID-19) mortality using a newly linked census-based data set and investigated how ethnicity-specific mortality risk evolved during the pandemic. Methods We conducted a retrospective cohort study of respondents to the 2011 Census of England and Wales in private households, linked to death registrations and adjusted for emigration (n = 47 872 412). The outcome of interest was death involving COVID-19 between 2 March 2020 and 15 May 2020. We estimated hazard ratios (HRs) for ethnic-minority groups compared with the White population, controlling for individual, household and area characteristics. HRs were estimated on the full outcome period and separately for pre- and post-lockdown periods. Results In age-adjusted models, people from all ethnic-minority groups were at elevated risk of COVID-19 mortality; the HRs for Black males and females were 3.13 (95% confidence interval: 2.93 to 3.34) and 2.40 (2.20 to 2.61), respectively. However, in fully adjusted models for females, the HRs were close to unity for all ethnic groups except Black [1.29 (1.18 to 1.42)]. For males, the mortality risk remained elevated for the Black [1.76 (1.63 to 1.90)], Bangladeshi/Pakistani [1.35 (1.21 to 1.49)] and Indian [1.30 (1.19 to 1.43)] groups. The HRs decreased after lockdown for all ethnic groups, particularly Black and Bangladeshi/Pakistani females. Conclusion Differences in COVID-19 mortality between ethnic groups were largely attenuated by geographical and socio-demographic factors, though some residual differences remained. Lockdown was associated with reductions in excess mortality risk in ethnic-minority populations, which has implications for a second wave of infection.

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

Background Strategies in many countries have sought to improve palliative care and reduce hospital deaths for non-cancer patients, but their effects are not evaluated. We aimed to determine the trends and factors associated with dying in hospital in two common progressive respiratory diseases, and the impact of a national end of life care (EoLC) strategy to reduce deaths in hospital. Methods This population-based observational study linked death registration data for people in England dying from chronic obstructive pulmonary disease (COPD) or interstitial pulmonary diseases (IPD). We plotted age- and sex-standardised trends, assessed during the pre-strategy (2001–2004), first strategy phase (2004–2008), and strategy intensification (2009–2014) periods, and identified factors associated with hospital death using multiple adjusted proportion ratios (PRs). Results Over 14 years, 380,232 people died from COPD (334,520) or IPD (45,712). Deaths from COPD and IPD increased by 0.9% and 9.2% annually, respectively. Death in hospital was most common (67% COPD, 70% IPD). Dying in hospice was rare (0.9% COPD, 2.9% IPD). After a plateau in 2004–2005, hospital deaths fell (PRs 0.92–0.94). Co-morbidities and deprivation independently increased the chances of dying in hospital, with larger effects in IPD (PRs 1.01–1.55) than COPD (PRs 1.01–1.39) and dose-response gradients. The impact of multimorbidity increased over time; hospital deaths did not fall for people with two or more co-morbidities in COPD, nor one or more in IPD. Living in rural areas (PRs 0.94–0.94) or outside London (PRs, 0.89–0.98) reduced the chances of hospital death. In IPD, increased age reduced the likelihood of hospital death (PR 0.81, ≥ 85 versus ≤ 54 years); divergently, in COPD, being aged 65–74 years was associated with increased hospital deaths (PR 1.13, versus ≤ 54 years). The independent effects of sex and marital status differed for COPD versus IPD (PRs 0.89–1.04); in COPD, hospital death was associated with being married. Conclusions The EoLC strategy appeared to have contributed to tangible reductions in hospital deaths, but did not reach people with multimorbidity and this gap widened over time. Integrating palliative care earlier in the disease trajectory especially in deprived areas and cities, and where multimorbidity is present, should be boosted, taking into account the different demographic factors in COPD and IPD. Electronic supplementary material The online version of this article (doi:10.1186/s12916-016-0776-2) contains supplementary material, which is available to authorized users.

SUMMARY: In the lifetime of the National Children's Bureau childhood death and serious infection have become increasingly rare. Chronic disease and disability may have become more common, partly as a result of the increased number of survivors of once fatal conditions. Income and social class are strongly associated with health, children in unskilled manual households being twice as likely to die before the age of 15 years as children in the professional social class. The proportion of children living in poverty doubled in the last decade. The rational allocation of resources to improve the health of children and teenagers is discussed.

OBJECTIVE: To study the differential distribution of transportation injury mortality by educational level in nine European settings, among people older than 30 years, during the 1990s. METHODS: Deaths of men and women older than 30 years from transportation injuries were studied. Rate differences and rate ratios (RR) between high and low educational level rates were obtained. RESULTS: Among men, those of low educational level had higher death rates in all settings, a pattern that was maintained in the different settings; no inequalities were found among women. Among men, in all the settings, the RR was higher in the 30-49 age group (RR 1.46, 95% CI 1.32 to 1.61) than in the age groups 50-69 and > or = 70 years, a pattern that was maintained in the different settings. For women for all the settings together, no differences were found among educational levels in the three age groups. In the different settings, only three had a high RR in the youngest age group, Finland (RR 1.33, 95% CI 1.01 to 1.74), Belgium (RR 1.38; 95% CI 1.13 to 1.67), and Austria (RR 1.49, 95% CI 0.75 to 2.96). CONCLUSION: This study provides new evidence on the importance of socioeconomic inequalities in transportation injury mortality across Europe. This applies to men, but not to women. Greater attention should be placed on opportunities to select intervention strategies tailored to tackle socioeconomic inequalities in transportation injuries.

This study assesses whether stroke mortality trends have been less favorable among lower than among higher socioeconomic groups. Longitudinal data on mortality by socioeconomic status were obtained for Finland, Norway, Denmark, Sweden, England/Wales, and Turin, Italy. Data covered the entire population or a representative sample. Stroke mortality rates were calculated for the period 1981-1995. Changes in stroke mortality rate ratios were analyzed using Poisson regression and compared with rate ratios in ischemic heat disease mortality. Trends in stroke mortality were generally as favorable among lower as among higher socioeconomic groups, such that socioeconomic disparities in stroke mortality persisted and remained of a similar magnitude in the 1990s as in the 1980s. In Norway, however, occupational disparities in stroke mortality significantly widened, and a nonsignificant increase was observed in some countries. In contrast, disparities in ischemic heart disease mortality widened throughout this period in most populations. Improvements in hypertension prevalence and treatment may have contributed to similar stroke mortality declines in all socioeconomic groups in most countries. Socioeconomic disparities in stroke mortality generally persisted and may have widened in some populations, which fact underlines the need to improve preventive and secondary care for stroke among the lower socioeconomic groups.

Background: Little is known about place of death in chronic neurological diseases. Mortality statistics are ideal for examining trends in place of death, but analyses are limited by coding rule changes. Aim: To examine the relationship between place of death and underlying cause of death in Parkinson’s disease, multiple sclerosis and motor neurone disease and the impact of coding rule changes on analysis of place of death. Design: Population-based study. Proportion ratios for death in hospice, home, care home and hospital were calculated according to underlying cause of death, using multivariable Poisson regression. Participants: Deaths in England (1993–2010) with any mention of Parkinson’s disease, multiple sclerosis or motor neurone disease as a cause of death, identified from national mortality data. Results: In this study, 125,242 patients with Parkinson’s disease, 23,501 with multiple sclerosis, and 27,030 with motor neurone disease were included. Home deaths ranged from 9.7% (Parkinson’s disease) to 27.1% (motor neurone disease), hospice deaths ranged from 0.6% (Parkinson’s disease) to 11.2% (motor neurone disease) and hospital deaths ranged from 43.4% (Parkinson’s disease) to 55.8% (multiple sclerosis). In Parkinson’s disease and multiple sclerosis, cancer as underlying cause of death increased likelihood of hospice death (proportion ratio (PR): 18.8, 95% confidence interval (CI) = 16.1–22.0; 8.88, 95% CI = 7.49–10.5) and home death (PR: 1.91, 95% CI = 1.80–2.04; 1.71, 95% CI = 1.56–1.88). Dementia as underlying cause of death increased likelihood of care home death in Parkinson’s disease (PR: 1.25, 95% CI = 1.19–1.32), multiple sclerosis (PR: 1.73, 95% CI = 1.22–2.45) and motor neurone disease (PR: 2.36, 95% CI = 1.31–4.27). Conclusions: Underlying cause of death has a marked effect on place of death. The effects of coding rule changes are an essential consideration for all research using underlying cause of death to study place of death.

Wei Gao and colleagues describe how location of death has changed for patients with cancer in England between 1993 and 2010., Background Most patients with cancer prefer to die at home or in a hospice, but hospitals remain the most common place of death (PoD).This study aims to explore the changing time trends of PoD and the associated factors, which are essential for end-of-life care improvement. Methods and Findings The study analysed all cancer deaths in England collected by the Office for National Statistics during 1993–2010 (n = 2,281,223). Time trends of age- and gender-standardised proportion of deaths in individual PoDs were evaluated using weighted piecewise linear regression. Variables associated with PoD (home or hospice versus hospital) were determined using proportion ratio (PR) derived from the log-binomial regression, adjusting for clustering effects. Hospital remained the most common PoD throughout the study period (48.0%; 95% CI 47.9%–48.0%), followed by home (24.5%; 95% CI 24.4%–24.5%), and hospice (16.4%; 95% CI 16.3%–16.4%). Home and hospice deaths increased since 2005 (0.87%; 95% CI 0.74%–0.99%/year, 0.24%; 95% CI 0.17%–0.32%/year, respectively, p, Editors' Summary Background Death is the only certain event in our lives. Consequently, end-of-life care is an issue that is relevant to everyone, and everyone hopes for a “good death” (a death that is free from avoidable distress and suffering) for themselves and for their loved ones. Many factors contribute to a good death, including the place of death. When asked, most people say they would rather die at home or in a hospice (a care facility that gives supportive care to people in the final phase of a terminal illness and that focuses on comfort and quality of life rather than on cure) than in a hospital. Importantly, patients who die at home or in a hospice often have a better quality of life than those who die in hospital, and caring for terminally ill patients in the community is less expensive than caring for them in hospital. Why Was This Study Done? Many countries have introduced end-of-life care policies that are designed to enable more people to die at home or in hospices. England, for example, implemented its National End of Life Care Programme in 2004. However, to improve end-of-life care services and to enable more people to die in their preferred place, we need to understand how the patterns of place of death and the factors that affect the place of death are changing over time. In this population-based study, the researchers examine the changing pattern of place of death of people with cancer and the factors associated with place of death in England between 1993 and 2010. Cancer is a leading cause of death globally and is responsible for 8 million deaths annually. Deaths from cancer still occur most commonly in hospitals, which are the least preferred place of death for people with cancer; home and hospices are the first and second preferred places of death, respectively, for such people. What Did the Researchers Do and Find? The researchers used death registration data collected by the Office of National Statistics to identify all the adult cancer deaths in England between 1993 and 2010 (2.28 million deaths) and to determine where these deaths occurred, time trends in place of death, and the factors associated with place of death. Hospital was the commonest place of death throughout the study period—48% of cancer deaths occurred in hospital, 24.5% at home, and 16.4% in hospices. The proportion of home deaths increased after 2005 whereas the proportion of hospital deaths declined. The proportion of deaths in hospices also increased over the study period. The most important factor associated with place of death was cancer site. For example, patients who died from a blood (hematological) cancer were more likely to die in hospital than patients with colorectal cancer throughout the study period although the proportion dying at home or in a hospice increased over time. Being single, widowed, or divorced was associated with a higher likelihood of dying in hospital than being married. Being over 75 was associated with a higher likelihood of dying in hospital than being 25–54 although elderly people were more likely to die at home or in a hospice after 2006 than in earlier periods. What Do These Findings Mean? These findings show that the hospital is still the commonest place of death for patients with cancer in England. However, the increase in home and hospice deaths since 2005 suggests that the National End of Life Care Programme has enabled more people to die at their preferred place of death. These findings identify cancer site, marital status, and age as the three most important factors associated with place of death for patients with cancer. Because the study is a large-scale, population-based study, these findings are likely to be generalizable to other high-income settings. However, because the study did not include data on individual patient preferences for place of death, these findings should be applied with care to individual patients. Importantly, these findings indicate that more needs to be done to support people with cancer (and other terminal illnesses) who wish to die at home or in a hospice. Moreover, they identify groups of people—single, widowed or divorced individuals, older people, and people with specific types of cancer—who need extra help to ensure that they are able to choose where they die. Additional Information Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001410. The Cicely Saunders International, a not-for-profit organization, promotes research to improve the care and treatment of all patients with terminal illnesses at home, in hospices and in hospital; its website includes information on end-of-life care and on Cicely Saunders, the founder of the hospice movement in England This study is part of GUIDE_Care, a project initiated by the Cicely Saunders Institute to investigate patterns in place of death and the factors that affect these patterns Information on the National End of Life Care Programme is available The UK National Health Service Choices website provides information (including videos of personal experiences) on end-of-life issues for carers, information on end-of-life care for patients with cancer, and an end-of-life care guide for people approaching the end of their life The US National Cancer Institute has a fact sheet on end-of-life care for people who have cancer and provides information on hospice care and home care for patients with cancer (in English and Spanish) The not-for-profit organization HealthTalkOnline provides personal stories about living with dying The NHS National End of Life Intelligence Network (NEoLCIN) provides information on broad issues about end-of-life care The South West Public Health Observatory (SWPHO) aims to improve the health of the population through producing evidence to inform decision making on health issues at local, regional, and national levels. SWPHO also produces specific end-of-life care resources (e.g., specialised reports, end-of-life care profiles) and disseminates it via the NEoLCIN website

Udgivelsesdato: 2008-Jun-5 BACKGROUND: Comparisons among countries can help to identify opportunities for the reduction of inequalities in health. We compared the magnitude of inequalities in mortality and self-assessed health among 22 countries in all parts of Europe. METHODS: We obtained data on mortality according to education level and occupational class from census-based mortality studies. Deaths were classified according to cause, including common causes, such as cardiovascular disease and cancer; causes related to smoking; causes related to alcohol use; and causes amenable to medical intervention, such as tuberculosis and hypertension. Data on self-assessed health, smoking, and obesity according to education and income were obtained from health or multipurpose surveys. For each country, the association between socioeconomic status and health outcomes was measured with the use of regression-based inequality indexes. RESULTS: In almost all countries, the rates of death and poorer self-assessments of health were substantially higher in groups of lower socioeconomic status, but the magnitude of the inequalities between groups of higher and lower socioeconomic status was much larger in some countries than in others. Inequalities in mortality were small in some southern European countries and very large in most countries in the eastern and Baltic regions. These variations among countries appeared to be attributable in part to causes of death related to smoking or alcohol use or amenable to medical intervention. The magnitude of inequalities in self-assessed health also varied substantially among countries, but in a different pattern. CONCLUSIONS: We observed variation across Europe in the magnitude of inequalities in health associated with socioeconomic status. These inequalities might be reduced by improving educational opportunities, income distribution, health-related behavior, or access to health care.

This article reports social inequalities in mortality in men aged 25-64 years in England and Wales, in the period 2001-03 using unlinked data sources and 2001-04 using linked data sources. It represents the first official analysis of premature mortality by the final version of the National Statistics Socio-economic Classification introduced in 2001, and updates the tradition of decennial reporting of mortality by socio-economic status. These results set a benchmark for inequalities in mortality in men of this age, providing insights into the impacts of different social and occupational circumstances in the early 21st Century and enabling future monitoring. The Office for National Statistics intends to extend this work to examine inequalities to mortality in females of the same age, in causes of death and by Government Office Region.

OBJECTIVE: To assess the association between socioeconomic status and ischaemic heart disease (IHD) mortality in 10 western European populations during the 1990s. DESIGN: Longitudinal study. SETTING: 10 European populations (95,009,822 person years). METHODS: Longitudinal data on IHD mortality by educational level were obtained from registries in Finland, Norway, Denmark, England/Wales, Belgium, Switzerland, Austria, Turin (Italy), Barcelona (Spain), and Madrid (Spain). Age standardised rates and rate ratios (RRs) of IHD mortality by educational level were calculated by using Poisson regression. RESULTS: IHD mortality was higher in those with a lower socioeconomic status than in those with a higher socioeconomic status among men aged 30-59 (RR 1.55, 95% confidence interval (CI) 1.51 to 1.60) and 60 years and over (RR 1.22, 95% CI 1.21 to 1.24), and among women aged 30-59 (RR 2.13, 95% CI 1.98 to 2.29) and 60 years and over (RR 1.36, 95% CI 1.33 to 1.38). Socioeconomic disparities in IHD mortality were larger in the Scandinavian countries and England/Wales, of moderate size in Belgium, Switzerland, and Austria, and smaller in southern European populations among men and younger women (p < 0.0001). For elderly women the north-south gradient was smaller and there was less variation between populations. No socioeconomic disparities in IHD mortality existed among elderly men in southern Europe. CONCLUSIONS: Socioeconomic disparities in IHD mortality were larger in northern than in southern European populations during the 1990s. This partly reflects the pattern of socioeconomic disparities in cardiovascular risk factors in Europe. Population wide strategies to reduce risk factor prevalence combined with interventions targeted at the lower socioeconomic groups can contribute to reduce IHD mortality in Europe

Background: Studies of socioeconomic disparities in patterns of cause of death have been limited to single countries, middle-aged people, men, or broad cause of death groups. We assessed contribution of specific causes of death to disparities in mortality between groups with different levels of education, in men and women, middle-aged and old, in eight western European populations. Methods: We analysed data from longitudinal mortality studies by cause of death, between Jan 1, 1990, and Dec 31, 1997. Data were included for more than 1 million deaths in 51 million person years of observation. Findings: Absolute educational inequalities in total mortality peaked at 2127 deaths per 100 000 person years in men, and at 1588 deaths per 100 000 person years in women aged 75 years and older. In this age-group, rate ratios were greater than 1.00 for total mortality and all specific causes of death, apart form prostate cancer in men and lung cancer in women, showing increased mortality in low versus high eductational groups. In men, cardiovascular diseases accounted for 39% of the difference between low and high eductational groups in total mortality, cancer for 24%, other diseases for 32%, and external causes for 5%. Among women, contributions were 60%, 11%, 30%, and 0%, respectively. The contributions of cerebrovascular disease, other cardiovascular diseases, pneumonia, and COPD strongly increased by age, whereas those of cancer and external causes declined. Although relative inequalities in total mortality were closely similar in all populations, we noted striking differences in the contribution of specific causes to these inequalities. Interpretation: Research needs to be broadened to include older populations, other diseases, and populations from different parts of Europe. Effective interventions should be developed and implemented to reduce exposure to cardiovascular risk factors in low-educational groups.

Little is known about the association between health and the quality of the residential environment. What is known is often based on subjective assessments of the environment rather than on measurements by independent observers. The aim of this study, therefore, was to determine the association between self-reported general health and an objectively assessed measure of the residential environment. We studied over 30,000 residents aged 18 or over living in 777 neighbourhoods in south Wales. Built environment quality was measured by independent observers using a validated tool, the Residential Environment Assessment Tool (REAT), at unit postcode level. UK Census data on each resident, which included responses to a question which assessed self-reported general health, was linked to the REAT score. The Census data also contained detailed information on socio-economic and demographic characteristics of all respondents and was also linked to the Welsh Index of Multiple Deprivation. After adjusting for both the individual characteristics and area deprivation, respondents in the areas of poorest neighbourhood quality were more likely to report poor health compared to those living in areas of highest quality (OR 1.36, 95% confidence interval 1.22-1.49). The particular neighbourhood characteristics associated with poor health were physical incivilities and measures of how well the residents maintained their properties. Measures of green space were not associated with self-reported health. This is the first full population study to examine such associations and the results demonstrate the importance for health of the quality of the neighbourhood area in which people live and particularly the way in which residents behave towards their own and their neighbours' property. A better understanding of causal pathways that allows the development of interventions to improve neighbourhood quality would offer significant potential health gains.

Background The in-hospital death rate from dementia in England is among the highest in Europe. The personal, regional, and temporal factors influencing place of death in dementia are unknown. Methods Office for National Statistics mortality data were used for whole population cross-sectional analysis of deaths from dementia in England, 2001–10. Place of death (home, hospice, care home, hospital) was the outcome variable. Explanatory variables included demographic, social, and regional factors. Multivariable Poisson regression analysis was used to provide an independent relative risk of place of death for each of the variables studied. The change in place of death over time was studied using linear regression. Findings 387 004 deaths were included. Most patients died in care homes (55·3%) or hospital (39·6%). Home deaths (4·8%) and hospice deaths (0·3%) were rare. Hospital deaths were less likely with increasing affluence (relative risk [RR] 0·83, 95% CI 0·81–0·85), and increasing provision of a care-home bed (0·61, 95% CI 0·58–0·63). Lack of social support (marital status) reduced home deaths (RRs 0·45–0·60). Hospice deaths were increased in areas with greater hospice bed provision (RR 4·23, 95% CI 2·14–8·35) and in patients whose underlying cause of death was cancer (19·0, 95% CI 16·2–22·3). Deaths in care homes were more common with increasing affluence (RR 1·28, 95% CI 1·24–1·32) and increased provision of a care-home bed (2·02, 95% CI 1·97–2·08). Time-trend analysis showed a recent decrease in hospital deaths and reciprocal increase in care-home deaths. Interpretation Governments and policy makers recognise the urgent need for public health planning in dementia. Reducing the number of deaths in hospital, and increasing those at home, in dementia has both societal and economic benefits. Social support, deprivation, and service provision are key targets for policy. Funding National Institute for Health Research.

The contribution of different general practitioner characteristics, views, and experiences to the likelihood of their providing child health surveillance (CHS) was determined and their perceived training needs discovered. Family health service authority administrative data on the study population was combined with a postal questionnaire survey. Subjects were all general practitioners in three district health authorities in the North West Thames region. There were striking differences between districts in the proportion of practitioners undertaking CHS. General practitioners with paediatric training were three times more likely to do CHS. Women doctors were twice as likely to do CHS as men. The personal views of general practitioners were significantly associated with whether or not they undertook CHS. The CHS fee did not appear to be the major motivating factor. There was considerable demand for further training. The proportion of general practitioners undertaking CHS is likely to increase with the proportion of women and vocationally trained doctors. More local training is wanted, both by general practitioners already doing CHS and by those who would like to do it. Health authorities need to ensure that such training is convenient and continuing.

OBJECTIVE--To describe the views of general practitioners, health visitors, and clinical medical officers on child health surveillance, recent changes, perceptions of each other's roles, and attitudes to audit. DESIGN--Postal questionnaire survey. SETTING--Three health districts in North West Thames health region. SUBJECTS--All 602 general practitioners, 272 health visitors, and 42 clinical medical officers in these districts. MAIN MEASURES--Attitudes to and perceptions of child health surveillance and audit. Questionnaires were completed by 440 general practitioners (response rate 73%), 164 health visitors (60%), and 39 clinical medical officers (93%). RESULTS--Attitudes to child health surveillance were less positive among general practitioners than health visitors or clinical medical officers. Few respondents agreed that child health surveillance was a cost effective use of general practitioners' time (general practitioners 28%, 113/407; health visitors 28%, 40/145; clinical medical officers 39%, 15/39) and most thought that health visitors should carry out more of the doctors' examinations (68%, 262/387; 65%, 89/136; 66%, 25/38). General practitioners thought that clinical medical officers were less supportive than other relevant groups of their doing more child health surveillance. Most (72%, 105/146) health visitors thought that the 1990 contract had reduced parental choice of where to attend for child health surveillance. General practitioners were less enthusiastic than health visitors about most forms of clinical audit. CONCLUSIONS--Despite reservations about the impact of recent changes all groups were willing to explore innovative ways of delivering child health surveillance. IMPLICATIONS--There is scope for health visitors to increase their responsibilities and for more varied relationships between general practitioners and community child health doctors.