A comparison of excess deaths by UK country and region during the first year of the COVID-19 pandemic.

We compare the impact of the first two waves of the COVID-19 pandemic on risk of age-standardized mortality by sex, UK country, and English region. Each wave is defined as lasting 26 weeks and are consecutive beginning in 2020 week 11. The expected rate is estimated from 2015 to 2019 mean and the projected mortality trend from the same period are used to estimate excess mortality. By both measures, excess mortality was highest and lowest in regions of England, London and the South-West, respectively. Excess mortality was consistently higher for males than females.

Epilepsy-related mortality during the COVID-19 pandemic: A nationwide study of routine Scottish data.

OBJECTIVE: To examine whether epilepsy-related deaths increased during the COVID-19 pandemic and if the proportion with COVID-19 listed as the underlying cause is different between people experiencing epilepsy-related deaths and those experiencing deaths unrelated to epilepsy. METHODS: This was a Scotland-wide, population-based, cross-sectional study of routinely-collected mortality data pertaining to March-August of 2020 (COVID-19 pandemic peak) compared to the corresponding periods in 2015-2019. ICD-10-coded causes of death of deceased people of any age were obtained from a national mortality registry of death certificates in order to identify those experiencing epilepsy-related deaths (coded G40-41), deaths with COVID-19 listed as a cause (coded U07.1-07.2), and deaths unrelated to epilepsy (death without G40-41 coded). The number of epilepsy-related deaths in 2020 were compared to the mean observed through 2015-2019 on an autoregressive integrated moving average (ARIMA) model (overall, men, women). Proportionate mortality and odds ratios (OR) for deaths with COVID-19 listed as the underlying cause were determined for the epilepsy-related deaths compared to deaths unrelated to epilepsy, reporting 95% confidence intervals (CIs). RESULTS: A mean number of 164 epilepsy-related deaths occurred through March-August of 2015-2019 (of which a mean of 71 were in women and 93 in men). There were subsequently 189 epilepsy-related deaths during the pandemic March-August 2020 (89 women, 100 men). This was 25 more epilepsy-related deaths (18 women, 7 men) compared to the mean through 2015-2019. The increase in women was beyond the mean year-to-year variation seen in 2015-2019. Proportionate mortality with COVID-19 listed as the underlying cause was similar between people experiencing epilepsy-related deaths (21/189, 11.1%, CI 7.0-16.5%) and deaths unrelated to epilepsy (3,879/27,428, 14.1%, CI 13.7-14.6%), OR 0.76 (CI 0.48-1.20). Ten of 18 excess epilepsy-related deaths in women had COVID-19 listed as an additional cause. CONCLUSIONS: There is little evidence to suggest there have been any major increases in epilepsy-related deaths in Scotland during the COVID-19 pandemic. COVID-19 is a common underlying cause of both epilepsy-related and unrelated deaths.

Trends in infant mortality and stillbirth rates in Scotland by socio-economic position, 2000-2018: a longitudinal ecological study.

BACKGROUND: As Scotland strives to become a country where children flourish in their early years, it is faced with the challenge of socio-economic health inequalities, which are at risk of widening amidst austerity policies. The aim of this study was to explore trends in infant mortality rates (IMR) and stillbirth rates by socio-economic position (SEP) in Scotland, between 2000 and 2018, inclusive. METHODS: Data for live births, infant deaths, and stillbirths between 2000 and 2018 were obtained from National Records of Scotland. Annual IMR and stillbirth rates were calculated and visualised for all of Scotland and when stratified by SEP. Negative binomial regression models were used to estimate the association between SEP and infant mortality and stillbirth events, and to assess for break points in trends over time. The slope (SII) and relative (RII) index of inequality compared absolute and relative socio-economic inequalities in IMR and stillbirth rates before and after 2010. RESULTS: IMR fell from 5.7 to 3.2 deaths per 1000 live births between 2000 and 2018, with no change in trend identified. Stillbirth rates were relatively static between 2000 and 2008 but experienced accelerated reduction from 2009 onwards. When stratified by SEP, inequalities in IMR and stillbirth rates persisted throughout the study and were greatest amongst the sub-group of post-neonates. Although comparison of the SII and RII in IMR and stillbirths before and after 2010 suggested that inequalities remained stable, descriptive trends in mortality rates displayed a 3-year rise in the most deprived quintiles from 2016 onwards. CONCLUSION: Whilst Scotland has experienced downward trends in IMR and stillbirth rates between 2000 and 2018, the persistence of socio-economic inequalities and suggestion that mortality rates amongst the most deprived groups may be worsening warrants further action to improve maternal health and strengthen support for families with young children.

How have changes in death by cause and age group contributed to the recent stalling of life expectancy gains in Scotland? Comparative decomposition analysis of mortality data, 2000-2002 to 2015-2017.

OBJECTIVE: Annual gains in life expectancy in Scotland were slower in recent years than in the previous two decades. This analysis investigates how deaths in different age groups and from different causes have contributed to annual average change in life expectancy across two time periods: 2000-2002 to 2012-2014 and 2012-2014 to 2015-2017. SETTING: Scotland. METHODS: Life expectancy at birth was calculated from death and population counts, disaggregated by 5 year age group and by underlying cause of death. Arriaga's method of life expectancy decomposition was applied to produce estimates of the contribution of different age groups and underlying causes to changes in life expectancy at birth for the two periods. RESULTS: Annualised gains in life expectancy between 2012-2014 and 2015-2017 were markedly smaller than in the earlier period. Almost all age groups saw worsening mortality trends, which deteriorated for most cause of death groups between 2012-2014 and 2015-2017. In particular, the previously observed substantial life expectancy gains due to reductions in mortality from circulatory causes, which most benefited those aged 55-84 years, more than halved. Mortality rates for those aged 30-54 years and 90+ years worsened, due in large part to increases in drug-related deaths, and dementia and Alzheimer's disease, respectively. CONCLUSION: Future research should seek to explain the changes in mortality trends for all age groups and causes. More investigation is required to establish to what extent shortcomings in the social security system and public services may be contributing to the adverse trends and preventing mitigation of the impact of other contributing factors, such as influenza outbreaks.

How bad are life expectancy trends across the UK, and what would it take to get back to previous trends?

BACKGROUND: Within the UK, there has been debate on whether life expectancy is increasing or decreasing in particular single or 3-year periods, but there has been less thinking whether overall trends have changed. This paper considers the extent to which the trends in life expectancy for the UK and its nations have changed before and after 2011. METHODS: We used the Office for National Statistics period life expectancy data for the UK and its nations. We used Lee's approach to project life expectancy based on repeated sampling of year-to-year change in the baseline periods (1990-2011 and 1980-2011) and applied that to 2012 onwards. FINDINGS: Improvements in period life expectancy were substantially and consistently lower between 2012 and 2018 than predicted from the trends from 1980 and, especially, from 1990. By 2018, life expectancy was lower than projected for females and males, respectively, by 1.22 and 1.52 years (England), 1.44 and 0.95 years (Northern Ireland), 1.30 and 1.44 years (Scotland), 1.53 and 1.63 years (Wales) and 1.24 and 1.49 years (UK overall), based on the 1990-2011 baseline period. Using a longer baseline period, which includes the slower rates of improvement during the 1980s, slightly reduces the gap between the current life expectancies and the projected medians. INTERPRETATION: Future academic and policy focus should be on the deviation of the life expectancy trends from the baseline projection rather than on year-to-year variation. Concerted policy focus to return life expectancy to the projected trends is now urgently required.

Recent adverse mortality trends in Scotland: comparison with other high-income countries.

OBJECTIVE: Gains in life expectancy have faltered in several high-income countries in recent years. Scotland has consistently had a lower life expectancy than many other high-income countries over the past 70 years. We aim to compare life expectancy trends in Scotland to those seen internationally and to assess the timing and importance of any recent changes in mortality trends for Scotland. SETTING: Austria, Croatia, Czech Republic, Denmark, England and Wales, Estonia, France, Germany, Hungary, Iceland, Israel, Japan, Korea, Latvia, Lithuania, Netherlands, Northern Ireland, Poland, Scotland, Slovakia, Spain, Sweden, Switzerland and USA. METHODS: We used life expectancy data from the Human Mortality Database (HMD) to calculate the mean annual life expectancy change for 24 high-income countries over 5-year periods from 1992 to 2016. Linear regression was used to assess the association between life expectancy in 2011 and mean life expectancy change over the subsequent 5 years. One-break and two-break segmented regression models were used to test the timing of mortality rate changes in Scotland between 1990 and 2018. RESULTS: Mean improvements in life expectancy in 2012-2016 were smallest among women (<2 weeks/year) in Northern Ireland, Iceland, England and Wales, and the USA and among men (<5 weeks/year) in Iceland, USA, England and Wales, and Scotland. Japan, Korea and countries of Eastern Europe had substantial gains in life expectancy over the same period. The best estimate of when mortality rates changed to a slower rate of improvement in Scotland was the year to 2012 quarter 4 for men and the year to 2014 quarter 2 for women. CONCLUSIONS: Life expectancy improvement has stalled across many, but not all, high-income countries. The recent change in the mortality trend in Scotland occurred within the period 2012-2014. Further research is required to understand these trends, but governments must also take timely action on plausible contributors.

Do socio-economic, behavioural and biological risk factors explain the poor health profile of the UK's sickest city?

BACKGROUND: The extent to which the poor health profile of Glasgow, the city with the highest mortality rates in the UK, can be explained solely by socio-economic factors is unclear. This paper additionally considers behavioural and biological factors as explanations of excess risk. METHODS: Scottish Health Survey data for 2008-09 were analysed using logistic regression models to compare the odds of physical and mental health outcomes, as well as adverse health behaviours, for residents of the Greater Glasgow and Clyde (GGC) conurbation compared with the rest of Scotland. RESULTS: After adjustment for age and sex, significant differences were observed among Glasgow residents for most mental and physical health outcomes, but not for most adverse health behaviours. Adjustment for area and individual-level socio-economic characteristics explained the differences for all outcomes except anxiety, psychological ill-health, heart attack and men being overweight. After additional adjustment for behavioural and biological characteristics, significantly higher odds of anxiety and heart attack remained for residents of the Glasgow area. CONCLUSIONS: Adjusting for area- and individual-level socio-economic conditions explained the excess risk associated with residents of GGC for most (16 out of 18) outcomes; however, significant excess risks for two outcomes remained: anxiety and heart attack. Additional explanations are, therefore, required.