Background Elevated standardised mortality ratio of cardiovascular diseases (CVD) in patients with brain tumours may result from differences in the CVD incidences and cardiovascular risk factors. We compared the risk of CVD among patients with a primary malignant or non-malignant brain tumour to a matched general population cohort, accounting for other co-morbidities. Methods Using data from the Secured Anonymised Information Linkage (SAIL) Databank in Wales (United Kingdom), we identified all adults aged ≥ 18 years in the primary care database with first diagnosis of malignant or non-malignant brain tumour identified in the cancer registry in 2000–2014 and a matched cohort (case-to-control ratio 1:5) by age, sex and primary care provider from the general population without any cancer diagnosis. Outcomes included fatal and non-fatal major vascular events (stroke, ischaemic heart disease, aortic and peripheral vascular diseases) and venous thromboembolism (VTE). We used multivariable Cox models adjusted for clinical risk factors to compare risks, stratified by tumour behaviour (malignant or non-malignant) and follow-up period. Results There were 2869 and 3931 people diagnosed with malignant or non-malignant brain tumours, respectively, between 2000 and 2014 in Wales. They were matched to 33,785 controls. Within the first year of tumour diagnosis, malignant tumour was associated with a higher risk of VTE (hazard ratio [HR] 21.58, 95% confidence interval 16.12–28.88) and stroke (HR 3.32, 2.44–4.53). After the first year, the risks of VTE (HR 2.20, 1.52–3.18) and stroke (HR 1.45, 1.00–2.10) remained higher than controls. Patients with non-malignant tumours had higher risks of VTE (HR 3.72, 2.73–5.06), stroke (HR 4.06, 3.35–4.93) and aortic and peripheral arterial disease (HR 2.09, 1.26–3.48) within the first year of diagnosis compared with their controls. Conclusions The elevated CVD and VTE risks suggested risk reduction may be a strategy to improve life quality and survival in people with a brain tumour.

Introduction: Glioma is the most common malignant type of brain tumours. Glioma patients are at higher risk for cerebrovascular mortality compared to the general population and other cancer types. Whether the risk differs by the grade, a marker of aggressiveness in gliomas, remains unclear. Methods: Using the US National Cancer Institute’s Surveillance Epidemiology and End Results program, we identified adult patients with a primary diagnosis of malignant gliomas in 2000 to 2018 (N=72,252). Age-, sex-, and calendar-year- adjusted standardized mortality ratios (SMRs) were calculated for cerebrovascular mortality comparing glioma patients with the general population. Gliomas were classified into four grades based on WHO definition in which increasing grade indicates the higher degrees of invasiveness. Hazard ratio (HR) and 95% confidence interval (CI) were calculated using Cox regression model to examine cerebrovascular mortality in patients with different grades of gliomas. Results: Over 80% of patients were diagnosed with high grade gliomas (Grade 3 & 4). Patients with gliomas in all grades had excess cerebrovascular mortality compared with the general population (SMRs 2.64-4.18, p<0.001). Younger patients (< 50 years) with glioblastoma (Grade 4), the most aggressive type, had substantially greater risk (SMR 12.73, p<0.001) than the general population compared to those with lower grades (SMR 7.14 & 6.31 in Grade 2 & 3, p<0.001). In grade 4, Hispanic patients had highest risk (SMR 6.23, p<0.001) than other ethnic groups (SMR 3.67 & 4.92 in White and Black respectively, p<0.001). In case-only analysis, patients with Grade 4 were significantly associated with increased cerebrovascular mortality compared to the lower grade (HR=1.41, 95% CI 1.01-1.97, p<0.01) after adjustment of socio-demographic and treatment (surgery, radiation and chemotherapy) characteristics. Conclusions: The findings of higher grades of gliomas associated with cerebrovascular mortality support further research to understand the role of aggressiveness and other risk factors in brain cancer-associated fatal stroke.

Routine reporting of descriptive population-based brain tumor epidemiological data is important for evaluating incidence trends, providing clues for putative risk factors, benchmarking outcomes, and stimulating research into the causes of this deadly disease. We propose to standardize reporting of cancer registry data for brain tumors in the United Kingdom through researcher-led collaborations. Interpretation of incidence trends needs to account for changing diagnostic practice. In the United Kingdom, reports from government agencies do not provide epidemiological data of brain tumor subtypes beyond the overall burden of these tumors. Using the Welsh cancer registry, we have demonstrated that separate reporting of histologically confirmed tumors enhances the interpretation of age- and sex-adjusted brain tumor incidence trends because only patients undergoing surgery would have a histological diagnosis of disease. Wanis et al1 reported on English brain tumor cancer registry data from 1995 to 2017 and observed similar patterns as we described for Wales.2 One exception was that Wanis et al did not report results by histological diagnosis, which we propose should become a standard analysis to document trends accounting for changing diagnostic practice. We have already been in touch with the authors to discuss collaborative analyses to standardize reporting of brain tumor incidence data from Wales, Scotland, and England, with the aim of providing a comprehensive and clinically informed UK-wide picture of brain and CNS tumor incidence trends, similar to the annual publication from the Central Brain Tumor Registry of the United States (CBTRUS).3

Abstract Aims There is limited evidence on cerebrovascular risks in glioblastoma and meningioma patients. We aimed to compare cerebrovascular risks of these patients with the general population. Method We used population-based routine healthcare and administrative data linkage in this matched cohort study. Cases were adult glioblastoma and meningioma patients diagnosed in Wales 2000-2014 identified in the cancer registry. Controls from cancer-free general population were matched to cases (5:1 ratio) on age (±5 years), sex and GP practice. Factors included in multivariable models were age, sex, index of multiple deprivation, hypertension, diabetes, high cholesterol, history of cardiovascular disease, and medications for cardiovascular diseases. Outcomes were fatal and non-fatal haemorrhagic and ischaemic stroke. We used flexible parametric models adjusting for confounders to calculate the hazard ratios (HR). Results Final analytic population was 16,921 participants, of which 1,340 had glioblastoma and 1,498 had meningioma. The median follow-up time was 0.5 year for glioblastoma patients, 4.9 years for meningioma patients, and 6.6 years for controls. The number of haemorrhage and ischaemic stroke was 154 and 374 in the glioblastoma matched cohort, respectively, and 180 and 569 in the meningioma matched cohort, respectively. The adjusted HRs for haemorrhagic and ischaemic stroke were 3.74 (95%CI 1.87-6.57) and 5.62 (95%CI 2.56-10.42) in glioblastoma patients, respectively, and were 2.42 (95%CI 1.58-3.52) and 1.86 (95%CI 1.54-2.23) in meningioma patients compared with their controls. Conclusion Glioblastoma and meningioma patients had higher cerebrovascular risks; these risks were even higher for glioblastoma patients. Further assessment of these potentially modifiable risks may improve survivorship.

Background. Patients with central nervous system (CNS) tumors may be at risk of dying from cardiovascular disease (CVD). We examined CVD mortality risk in patients with different histological subtypes of CNS tumors. Methods: We analyzed UK(Wales)-based Secure Anonymized Information Linkage (SAIL) for 8743 CNS tumors patients diagnosed in 2000-2015, and US-based National Cancer Institute's Surveillance, Epidemiology, and End Results (SEER) for 163,183 patients in 2005-2015. We calculated age-, sex-, and calendar-year- adjusted standardized mortality ratios (SMRs) for CVD comparing CNS tumor patients to Wales and US residents. We used Cox regression models to examine factors associated with CVD mortality among CNS tumor patients. Results. CVD was the second leading cause of death for CNS tumor patients in SAIL (UK) and SEER (US). Patients with CNS tumors had higher CVD mortality than the general population (SAIL SMR = 2.64, 95% CI = 2.39-2.90, SEER SMR = 1.38, 95% CI = 1.35-1.42). Malignant CNS tumor patients had over 2-fold higher mortality risk in US and UK cohorts. SMRs for nonmalignant tumors were almost 2-fold higher in SAIL than in SEER. CVD mortality risk particularly cerebrovascular disease was substantially greater in patients diagnosed at age younger than 50 years, and within the first year after their cancer diagnosis (SAIL SMR = 2.98, 95% CI = 2.39-3.66, SEER SMR = 2.14, 95% CI = 2.03-2.25). Age, sex, race/ethnicity in USA, deprivation in UK and no surgery were associated with CVD mortality. Conclusions. Patients with CNS tumors had higher risk for CVD mortality, particularly from cerebrovascular disease compared to the general population, supporting further research to improve mortality outcomes.

Abstract Background Accumulating data show cardiovascular disease (CVD) is a major cause of death in many cancer patients supporting cardio-oncology epidemiology and clinical studies. Although rare, patients diagnosed with brain and central nervous system (CNS) tumours have significant morbidity and mortality. Whether CVD is a major cause of death and if this differs by malignancy has not been comprehensively assessed. Methods We aimed to examine the risk of CVD mortality in patients diagnosed with malignant and non-malignant CNS tumours using cancer registry data in the UK and US. Analyses were conducted using Wales Cancer Registry, UK (Secure Anonymised Information Linkage, SAIL) for 8,743 patients diagnosed from 2000-2015 (54.9% of which died); and the US National Cancer Institute's Surveillance, Epidemiology, and End Results (SEER) for 188,526 patients diagnosed from 2005-2015 (40.0% of which died). Standardized mortality ratios (SMRs) and 95% confidence intervals (CI) were calculated for CVD cause of death (heart disease, cerebrovascular disease, hypertension, atherosclerosis, and aortic aneurysm/dissection) and adjusted for age, sex and calendar year compared to all Welsh and US residents. SMRs were stratified by tumour types (malignant and non-malignant tumours) and main histologic types (glioma and meningioma). Results CVD is the second major cause of death for CNS tumour patients in SAIL and SEER (9.5% & 12.1%, respectively). Patients with malignant and non-malignant CNS tumours had excess CVD mortality compared with the general population (SAIL SMR=2.64, 95% CI=2.39-2.90, SEER SMR=1.38, 95% CI=1.35-1.42). Patients were more likely to die of CVD compared to the general population regardless of whether they were diagnosed with non-malignant meningiomas subtypes (SAIL SMR=3.13, 95%CI=2.73-3.57; SEER SMR=1.36, 95%CI=1.32-1.40) or malignant gliomas (SAIL SMR=2.08, 95%CI=1.46-2.88; SEER SMR=2.21, 95%CI=2.05-2.38). Patients diagnosed younger than 50 years of age had excess risk from CVD mortality compared to general population than those diagnosed at older ages (SAIL SMR=4.58, 95%CI=2.38-7.84, SEER SMR 2.03-95%CI=1.79-2.03). Patients had greater risk of CVD mortality within the first year after CNS tumour diagnosis in both SAIL and SEER (SMR=2.98, 95% CI=2.39-3.66 & SMR=2.14 95%CI=2.03-2.25, respectively). Conclusion CVD mortality is high among patients diagnosed with CNS tumours compared to general population. Cross national datasets for different histologic types of CNS tumours could help define high risk groups that may be targeted for future prevention and clinical studies to clarify the aetiology of CVD among CNS cancer patients. Citation Format: KAI JIN, Paul Brennan, Michael Poon, Cathie Sudlow, Jonine FIGUEROA. High cardiovascular disease mortality after central nervous system tumor diagnosis: Evidence from UK and USA population-based study [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr LB084.

Background. Increasing incidence of central nervous system (CNS) tumors has been noted in some populations. However, the influence of changing surgical and imaging practices has not been consistently accounted for. Methods. We evaluated average annual percentage change (AAPC) in age- and gender-stratified incidence of CNS tumors by tumor subtypes and histological confirmation in Wales, United Kingdom (1997-2015) and the United States (2004-2015) using joinpoint regression. Findings. In Wales, the incidence of histologically confirmed CNS tumors increased more than all CNS tumors (AAPC 3.62% vs 1.63%), indicating an increasing proportion undergoing surgery. Grade II and III glioma incidence declined significantly (AAPC -3.09% and -1.85%, respectively) but remained stable for those with histological confirmation. Grade IV glioma incidence increased overall (AAPC 3.99%), more markedly for those with histological confirmation (AAPC 5.36%), suggesting reduced glioma subtype misclassification due to increased surgery. In the United States, the incidence of CNS tumors increased overall but was stable for histologically confirmed tumors (AAPC 1.86% vs 0.09%) indicating an increase in patients diagnosed without surgery. An increase in grade IV gliomas (AAPC 0.28%) and a decline in grade II gliomas (AAPC -3.41%) were accompanied by similar changes in those with histological confirmation, indicating the overall trends in glioma subtypes were unlikely to be caused by changing diagnostic and clinical management. Conclusions. Changes in clinical practice have influenced the incidence of CNS tumors in the United Kingdom and the United States. These should be considered when evaluating trends and in epidemiological studies of putative risk factors for CNS tumors.

BACKGROUND:Physical activity (PA) levels vary across specific population groups, contributing to health inequalities. Little is known about how local authority leisure centers contribute to population PA and whether this differs by age, sex, or socioeconomic group.METHODS:The authors calculated weekly leisure center-based moderate/vigorous PA for 20,904 registered adult users of local authority leisure facilities in Northumberland, United Kingdom, between July 2018 and June 2019, using administrative data. The authors categorized activity levels (<30, 30-149, and ≥150 min/wk) and used ordinal regression to examine predictors for activity category achieved.RESULTS:Registered users were mainly female (58.7%), younger (23.9% of users aged 18-29 y vs 10.1% of those aged 70+ y), and from the 2 most affluent socioeconomic quintiles (53.7%). Median weekly moderate/vigorous leisure center-based activity was 55 minutes per week (interquartile range: 30-99). Being female (odds ratio: 2.09; 95% confidence interval, 1.95-2.35), older (odds ratio: 1.14; 95% confidence interval, 1.11-1.16), and using a large facility (odds ratio: 1.21; 95% confidence interval, 1.03-1.42) were positive predictors of leisure center-based PA.CONCLUSION:Older adults and females were more likely to be active and achieve the recommended PA levels through usage of the centers. Widespread use of this novel measure of leisure center-based activity would improve the understanding of how local authority leisure centers can address physical inactivity and its associated inequalities.

Physical activity referral schemes (PARS) are a popular physical activity (PA) intervention in the UK. Little is known about the type, intensity and duration of PA undertaken during and post PARS. We calculated weekly leisure centre-based moderate/vigorous PA for PARS participants (n = 448) and PARS completers (n = 746) in Northumberland, UK, between March 2019–February 2020 using administrative data. We categorised activity levels (<30 min/week, 30–149 min/week and ≥150 min/week) and used ordinal regression to examine predictors for activity category achieved. PARS participants took part in a median of 57.0 min (IQR 26.0–90.0) and PARS completers a median of 68.0 min (IQR 42.0–100.0) moderate/vigorous leisure centre-based PA per week. Being a PARS completer (OR: 2.14, 95% CI: 1.61–2.82) was a positive predictor of achieving a higher level of physical activity category compared to PARS participants. Female PARS participants were less likely (OR: 0.65, 95% CI: 0.43–0.97) to achieve ≥30 min of moderate/vigorous LCPA per week compared to male PARS participants. PARS participants achieved 38.0% and PARS completers 45.3% of the World Health Organisation recommended ≥150 min of moderate/vigorous weekly PA through leisure centre use. Strategies integrated within PARS to promote PA outside of leisure centre-based activity may help participants achieve PA guidelines.

Understanding the trends in causes of death for different diseases during the current COVID-19 pandemic is important to determine whether there are excess deaths beyond what is normally expected. Using the most recent report from National Records Scotland (NRS) on 29 April 2020, we examined the percentage difference in crude numbers of deaths in 2020 compared to the average for 2015-2019 by week of death within calendar year. To determine if trends were similar, suggesting underreporting/underdiagnosed COVID-19 related deaths, we also looked at the trends in % differences for cardiovascular disease deaths. From the first 17 weeks’ of data, we found a peak in excess deaths at week 14 of 2020, about four weeks after the first case in Scotland was detected on 1 March 2020-- but by week 17 these excesses had returned to normal levels, 4 weeks after lockdown in the UK began. Similar observations were seen for cardiovascular disease-related deaths. These observations suggest that the short-term increase in excess cancer and cardiovascular deaths might be associated with undetected/unconfirmed deaths related to COVID-19. Both of these conditions make patients more susceptible to infection and lack of widespread access to testing for COVID-19 are likely to have resulted in under-estimation of COVID-19 mortality. These data further suggest that the cumulative toll of COVID-19 on mortality is likely undercounted. More detailed analysis is needed to determine if these excesses were directly or indirectly related to COVID-19. Disease specific mortality will need constant monitoring for the foreseeable future as changes occur in increasing capacity and access to testing, reporting criteria, changes to health services and different measures are implemented to control the spread of the COVID-19. Multidisciplinary, multi-institutional, national and international collaborations for complementary and population specific data analysis is required to respond and mitigate adverse effects of the COVID-19 pandemic and to inform planning for future pandemics.

Understanding the trends in causes of death for different diseases during the current COVID-19 pandemic is important to determine whether there are excess deaths beyond what is normally expected. Using the most recent report from National Records Scotland (NRS) on 29 April 2020, we examined the percentage difference in crude numbers of deaths in 2020 compared to the average for 2015-2019 by week of death within calendar year. To determine if trends were similar, suggesting underreporting/underdiagnosed COVID-19 related deaths, we also looked at the trends in % differences for cardiovascular disease deaths. From the first 17 weeks&#x27; of data, we found a peak in excess deaths between weeks 14 of 2020, about four weeks after the first case in Scotland was detected on 1 March 2020-- but by week 17 these excesses had diminished around the time lockdown in the UK began. Similar observations were seen for cardiovascular disease-related deaths. These observations suggest that the short-term increase in excess cancer and cardiovascular deaths might be associated with undetected/unconfirmed deaths related to COVID-19. Both of these conditions make patients more susceptible to infection and lack of widespread access to testing for COVID-19 are likely to have resulted in under-estimation of COVID-19 mortality. These data further suggest that the cumulative toll of COVID-19 on mortality is likely undercounted. More detailed analysis is needed to determine if these excesses were directly or indirectly related to COVID-19. Disease specific mortality will need constant monitoring for the foreseeable future as changes occur in increasing capacity and access to testing, reporting criteria, changes to health services and different measures are implemented to control the spread of the COVID-19. Multidisciplinary, multi-institutional, national and international collaborations for complementary and population specific data analysis is required to respond and mitigate adverse effects of the COVID-19 pandemic and to inform planning for future pandemics.

Conservation planning is the primary tool the USDA Natural Resources Conservation Service (NRCS) uses to help farmers manage and protect the nation’s soil, water, air, plant, animal, energy, and human natural resources on privately owned lands. While research studies have investigated a multitude of factors that could possibly influence farmer adoption of conservation practices, no recent research exists examining the relationship between having an NRCS conservation plan and the likelihood of applying conservation practices on the ground. This is surprising given that conservation planning is considered to be the foundation for USDA’s technical and financial assistance to agricultural landowners, and recently both the updated NRCS Strategic Plan and the National Conservation Planning Partnership emphasized the need to enhance and expand conservation planning. In this study we analyzed data from 792 respondents of the 2015 and 2016 collection periods of a panel survey of Iowa farmers to examine the relationship between having an NRCS conservation plan and farmers’ implementation of 10 soil and water conservation practices in four categories: (1) soil health, (2) nitrogen (N) management, (3) structural practices, and (4) cropland converted to perennial crops. The results indicate that farmers who reported having an NRCS conservation plan are significantly more likely to have implemented two conservation practices: no-till and terraces. In addition, there was a significant relationship between the number of times a farmer visited a USDA Service Center for conservation and the likelihood they implemented 5 of the 10 selected practices, particularly in the soil health and structural practice categories. These results suggest that it is not the plan itself, but rather the sustained interaction with natural resource professionals, that makes a difference in the use of conservation practices. Implications of the study results for NRCS conservation planning moving forward in the future are discussed.

AIMSEvidence from longitudinal studies on the influence of area deprivation in cardiac mortality is limited. We aimed to examine the impact of area deprivation on cardiac mortality in a large representative Scottish population. We also examined differences between women and men.METHODS AND RESULTSRetrospective analysis was performed by using linked data from Scottish Longitudinal Study from 1991 to 2010. The main exposure variable was socioeconomic status using the Carstairs deprivation scores, a composite score of area-level factors. Cox proportional-hazards models were constructed to evaluate the hazard ratios (HRs) and 95% confidence intervals (CIs) for cardiac mortality and all-cause mortality associated with area-based deprivation. Subgroup analyses were stratified by sex. In a representative population of 217 965 UK adults, a total of 58 770 deaths occurred over a median of 10 years of follow-up period. The risk of cardiac mortality and all-cause mortality showed a consistent graded increased across the deprived groups. Compared to the least deprived group, the adjusted HR of cardiac mortality in the most deprived group was 1.27 (1.15-1.39, P < 0.000). There was strong evidence that women from more deprived areas had significantly higher cardiac death risk than those from the least deprived areas (HR 1.42, 95% CI 1.22-1.65), while this observation was not strong in men with same background.CONCLUSIONOur study demonstrated area deprivation was the strong predictor of long-term cardiac mortality and all-cause mortality. The inequalities were substantially greater in women from more deprived areas than men from the same background.

Aim: We aimed to describe trends of excess mortality in the United Kingdom (UK) stratified by nation and cause of death, and to develop an online tool for reporting the most up to date data on excess mortality. Methods: Population statistics agencies in the UK including the Office for National Statistics (ONS), National Records of Scotland (NRS), and Northern Ireland Statistics and Research Agency (NISRA) publish weekly data on deaths. We used mortality data up to 22nd May in the ONS and the NISRA and 24th May in the NRS. Crude mortality for non-COVID deaths (where there is no mention of COVID-19 on the death certificate) calculated. Excess mortality defined as difference between observed mortality and expected average of mortality from previous 5 years. Results: There were 56,961 excess deaths and 8,986 were non-COVID excess deaths. England had the highest number of excess deaths per 100,000 population (85) and Northern Ireland the lowest (34). Non-COVID mortality increased from 23rd March and returned to the 5-year average on 10th May. In Scotland, where underlying cause mortality data besides COVID-related deaths was available, the percentage excess over the 8-week period when COVID-related mortality peaked was: dementia 49%, other causes 21%, circulatory diseases 10%, and cancer 5%. We developed an online tool (TRACKing Excess Deaths - TRACKED) to allow dynamic exploration and visualisation of the latest mortality trends. Conclusions: Continuous monitoring of excess mortality trends and further integration of age- and gender-stratified and underlying cause of death data beyond COVID-19 will allow dynamic assessment of the impacts of indirect and direct mortality of the COVID-19 pandemic.

Aim: We aimed to describe trends of excess mortality in the United Kingdom (UK) stratified by nation and cause of death, and to develop an online tool for reporting the most up to date data on excess mortality. Methods: Population statistics agencies in the UK including the Office for National Statistics (ONS), National Records of Scotland (NRS), and Northern Ireland Statistics and Research Agency (NISRA) publish weekly data on deaths. We used mortality data up to 22nd May in the ONS and the NISRA and 24th May in the NRS. Crude mortality for non-COVID deaths (where there is no mention of COVID-19 on the death certificate) calculated. Excess mortality defined as difference between observed mortality and expected average of mortality from previous 5 years. Results: There were 56,961 excess deaths and 8,986 were non-COVID excess deaths. England had the highest number of excess deaths per 100,000 population (85) and Northern Ireland the lowest (34). Non-COVID mortality increased from 23rd March and returned to the 5-year average on 10th May. In Scotland, where underlying cause mortality data besides COVID-related deaths was available, the percentage excess over the 8-week period when COVID-related mortality peaked was: dementia 49%, other causes 21%, circulatory diseases 10%, and cancer 5%. We developed an online tool (TRACKing Excess Deaths - TRACKED) to allow dynamic exploration and visualisation of the latest mortality trends. Conclusions: Continuous monitoring of excess mortality trends and further integration of age- and gender-stratified and underlying cause of death data beyond COVID-19 will allow dynamic assessment of the impacts of indirect and direct mortality of the COVID-19 pandemic.

Background: We aimed to describe trends of excess mortality in the United Kingdom (UK) stratified by nation and cause of death, and to develop an online tool for reporting the most up to date data on excess mortality Methods: Population statistics agencies in the UK including the Office for National Statistics (ONS), National Records of Scotland (NRS), and Northern Ireland Statistics and Research Agency (NISRA) publish weekly mortality data. We used mortality data up to 22nd May in the ONS and the NISRA and 24th May in the NRS. The main outcome measures were crude mortality for non-COVID deaths (where there is no mention of COVID-19 on the death certificate) calculated, and excess mortality defined as difference between observed mortality and expected average of mortality from previous 5 years. Results: There were 56,961 excess deaths, of which 8,986 were non-COVID excess deaths. England had the highest number of excess deaths per 100,000 population (85) and Northern Ireland the lowest (34). Non-COVID mortality increased from 23rd March and returned to the 5-year average on 10th May. In Scotland, where underlying cause mortality data besides COVID-related deaths was available, the percentage excess over the 8-week period when COVID-related mortality peaked was: dementia 49%, other causes 21%, circulatory diseases 10%, and cancer 5%. We developed an online tool (TRACKing Excess Deaths - TRACKED) to allow dynamic exploration and visualisation of the latest mortality trends. Conclusions: Continuous monitoring of excess mortality trends and further integration of age- and gender-stratified and underlying cause of death data beyond COVID-19 will allow dynamic assessment of the impacts of indirect and direct mortality of the COVID-19 pandemic.

Background: We aimed to describe trends of excess mortality in the United Kingdom (UK) stratified by nation and cause of death, and to develop an online tool for reporting the most up to date data on excess mortality Methods: Population statistics agencies in the UK including the Office for National Statistics (ONS), National Records of Scotland (NRS), and Northern Ireland Statistics and Research Agency (NISRA) publish weekly mortality data We used mortality data up to 22nd May in the ONS and the NISRA and 24th May in the NRS The main outcome measures were crude mortality for non-COVID deaths (where there is no mention of COVID-19 on the death certificate) calculated, and excess mortality defined as difference between observed mortality and expected average of mortality from previous 5 years Results: There were 56,961 excess deaths, of which 8,986 were non-COVID excess deaths England had the highest number of excess deaths per 100,000 population (85) and Northern Ireland the lowest (34) Non-COVID mortality increased from 23rd March and returned to the 5-year average on 10th May In Scotland, where underlying cause mortality data besides COVID-related deaths was available, the percentage excess over the 8-week period when COVID-related mortality peaked was: dementia 49%, other causes 21%, circulatory diseases 10%, and cancer 5% We developed an online tool (TRACKing Excess Deaths - TRACKED) to allow dynamic exploration and visualisation of the latest mortality trends Conclusions: Continuous monitoring of excess mortality trends and further integration of age- and gender-stratified and underlying cause of death data beyond COVID-19 will allow dynamic assessment of the impacts of indirect and direct mortality of the COVID-19 pandemic

Introduction: Socioeconomic status is a strong contributor to disparities in cardiac outcomes. However, little is known about the impact of area deprivation on cardiac mortality among young people....