Population vulnerability to COVID-19 in Europe: A burden of disease analysis

Background: Evidence has emerged showing that elderly people and those with pre-existing chronic health conditions may be at higher risk of developing severe health consequences from COVID-19. In Europe, this is of particular relevance with ageing populations living with non-communicable diseases, multi-morbidity and frailty. Published estimates of Years Lived with Disability (YLD) from the Global Burden of Disease (GBD) study help to characterise the extent of these effects. Our aim was to identify the countries across Europe that have populations at highest risk from COVID-19 by using estimates of population age structure and YLD for health conditions linked to severe illness from COVID-19. Methods: Population and YLD estimates from GBD 2017 were extracted for 45 countries in Europe. YLD was restricted to a list of specific health conditions associated with being at risk of developing severe consequences from COVID-19 based on guidance from the United Kingdom Government. This guidance also identified individuals aged 70 years and above as being at higher risk of developing severe health consequences. Study outcomes were defined as: (i) proportion of population aged 70 years and above; and (ii) rate of YLD for COVID-19 vulnerable health conditions across all ages. Bivariate groupings were established for each outcome and combined to establish overall population-level vulnerability. Results: Countries with the highest proportions of elderly residents were Italy, Greece, Germany, Portugal and Finland. When assessments of population-level YLD rates for COVID-19 vulnerable health conditions were made, the highest rates were observed for Bulgaria, Czechia, Croatia, Hungary and Bosnia and Herzegovina. A bivariate analysis indicated that the countries at high-risk across both measures of vulnerability were: Bulgaria; Portugal; Latvia; Lithuania; Greece; Germany; Estonia; and Sweden. Conclusion: Routine estimates of population structures and non-fatal burden of disease measures can be usefully combined to create composite indicators of vulnerability for rapid assessments, in this case to severe health consequences from COVID-19. Countries with available results for sub-national regions within their country, or national burden of disease studies that also use sub-national levels for burden quantifications, should consider using non-fatal burden of disease estimates to estimate geographical vulnerability to COVID-19

Global, regional, and national age-sex-specific mortality and life expectancy, 1950–2017: a systematic analysis for the Global Burden of Disease Study 2017

BACKGROUND: Assessments of age-specific mortality and life expectancy have been done by the UN Population Division, Department of Economics and Social Affairs (UNPOP), the United States Census Bureau, WHO, and as part of previous iterations of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD). Previous iterations of the GBD used population estimates from UNPOP, which were not derived in a way that was internally consistent with the estimates of the numbers of deaths in the GBD. The present iteration of the GBD, GBD 2017, improves on previous assessments and provides timely estimates of the mortality experience of populations globally. METHODS: The GBD uses all available data to produce estimates of mortality rates between 1950 and 2017 for 23 age groups, both sexes, and 918 locations, including 195 countries and territories and subnational locations for 16 countries. Data used include vital registration systems, sample registration systems, household surveys (complete birth histories, summary birth histories, sibling histories), censuses (summary birth histories, household deaths), and Demographic Surveillance Sites. In total, this analysis used 8259 data sources. Estimates of the probability of death between birth and the age of 5 years and between ages 15 and 60 years are generated and then input into a model life table system to produce complete life tables for all locations and years. Fatal discontinuities and mortality due to HIV/AIDS are analysed separately and then incorporated into the estimation. We analyse the relationship between age-specific mortality and development status using the Socio-demographic Index, a composite measure based on fertility under the age of 25 years, education, and income. There are four main methodological improvements in GBD 2017 compared with GBD 2016: 622 additional data sources have been incorporated; new estimates of population, generated by the GBD study, are used; statistical methods used in different components of the analysis have been further standardised and improved; and the analysis has been extended backwards in time by two decades to start in 1950. FINDINGS: Globally, 18·7% (95% uncertainty interval 18·4–19·0) of deaths were registered in 1950 and that proportion has been steadily increasing since, with 58·8% (58·2–59·3) of all deaths being registered in 2015. At the global level, between 1950 and 2017, life expectancy increased from 48·1 years (46·5–49·6) to 70·5 years (70·1–70·8) for men and from 52·9 years (51·7–54·0) to 75·6 years (75·3–75·9) for women. Despite this overall progress, there remains substantial variation in life expectancy at birth in 2017, which ranges from 49·1 years (46·5–51·7) for men in the Central African Republic to 87·6 years (86·9–88·1) among women in Singapore. The greatest progress across age groups was for children younger than 5 years; under-5 mortality dropped from 216·0 deaths (196·3–238·1) per 1000 livebirths in 1950 to 38·9 deaths (35·6–42·83) per 1000 livebirths in 2017, with huge reductions across countries. Nevertheless, there were still 5·4 million (5·2–5·6) deaths among children younger than 5 years in the world in 2017. Progress has been less pronounced and more variable for adults, especially for adult males, who had stagnant or increasing mortality rates in several countries. The gap between male and female life expectancy between 1950 and 2017, while relatively stable at the global level, shows distinctive patterns across super-regions and has consistently been the largest in central Europe, eastern Europe, and central Asia, and smallest in south Asia. Performance was also variable across countries and time in observed mortality rates compared with those expected on the basis of development. INTERPRETATION: This analysis of age-sex-specific mortality shows that there are remarkably complex patterns in population mortality across countries. The findings of this study highlight global successes, such as the large decline in under-5 mortality, which reflects significant local, national, and global commitment and investment over several decades. However, they also bring attention to mortality patterns that are a cause for concern, particularly among adult men and, to a lesser extent, women, whose mortality rates have stagnated in many countries over the time period of this study, and in some cases are increasing

Global, regional, and national burden of suicide mortality 1990 to 2016: Systematic analysis for the Global Burden of Disease Study 2016

Objectives To use the estimates from the Global Burden of Disease Study 2016 to describe patterns of suicide mortality globally, regionally, and for 195 countries and territories by age, sex, and Socio-demographic index, and to describe temporal trends between 1990 and 2016. Design Systematic analysis. Main outcome measures Crude and age standardised rates from suicide mortality and years of life lost were compared across regions and countries, and by age, sex, and Socio-demographic index (a composite measure of fertility, income, and education). Results The total number of deaths from suicide increased by 6.7 (95 uncertainty interval 0.4 to 15.6) globally over the 27 year study period to 817 000 (762 000 to 884 000) deaths in 2016. However, the age standardised mortality rate for suicide decreased by 32.7 (27.2 to 36.6) worldwide between 1990 and 2016, similar to the decline in the global age standardised mortality rate of 30.6. Suicide was the leading cause of age standardised years of life lost in the Global Burden of Disease region of high income Asia Pacific and was among the top 10 leading causes in eastern Europe, central Europe, western Europe, central Asia, Australasia, southern Latin America, and high income North America. Rates for men were higher than for women across regions, countries, and age groups, except for the 15 to 19 age group. There was variation in the female to male ratio, with higher ratios at lower levels of Socio-demographic index. Women experienced greater decreases in mortality rates (49.0, 95 uncertainty interval 42.6 to 54.6) than men (23.8, 15.6 to 32.7). Conclusions Age standardised mortality rates for suicide have greatly reduced since 1990, but suicide remains an important contributor to mortality worldwide. Suicide mortality was variable across locations, between sexes, and between age groups. Suicide prevention strategies can be targeted towards vulnerable populations if they are informed by variations in mortality rates. © Published by the BMJ Publishing Group Limited

Certainty of the Global Burden of Disease 2019 modelled prevalence estimates for musculoskeletal conditions: A meta-epidemiological study

To describe and assess the risk of bias of the primary input studies that underpinned the Global Burden of Disease Study (GBD) 2019 modelled prevalence estimates of low back pain (LBP), neck pain (NP), and knee osteoarthritis (OA), from Australia, Brazil, Canada, Spain, and Switzerland. To evaluate the certainty of the GBD modelled prevalence evidence. Primary studies were identified using the GBD Data Input Sources Tool and their risk of bias was assessed using a validated tool. We rated the certainty of modelled prevalence estimates based on the GRADE Guidelines 30-the GRADE approach for modelled evidence. Seventy-two primary studies (LBP: 67, NP: 2, knee OA: 3) underpinned the GBD estimates. Most studies had limited representativeness of their study populations, used suboptimal case definitions and applied assessment instruments with unknown psychometric properties. The certainty of modelled prevalence estimates was low, mainly due to risk of bias and indirectness. Beyond the risk of bias of primary input studies for LBP, NP, and knee OA in GBD 2019, the certainty of country-specific modelled prevalence estimates still have room for&nbsp;improvement.</p

Investigating years of life lost in Belgium, 2004-2019: A comprehensive analysis using a probabilistic redistribution approach

INTRODUCTION: Information on years of life lost (YLL) due to premature mortality is instrumental to assess the fatal impact of disease and necessary for the calculation of Belgian disability-adjusted life years (DALYs). This study presents a novel method to reallocate causes of death&nbsp;data. MATERIALS AND METHODS: Causes of death data are provided by Statistics Belgium (Statbel). First, the specific ICD-10 codes that define the underlying cause of death are mapped to the GBD cause list. Second, ill-defined deaths (IDDs) are redistributed to specific ICD-10 codes. A four-step probabilistic redistribution was developed to fit the Belgian context: redistribution using predefined ICD codes, redistribution using multiple causes of death data, internal redistribution, and redistribution to all causes. Finally, we used the GBD 2019 reference life table to calculate Standard Expected Years of Life Lost (SEYLL). RESULTS: In Belgium, between 2004 and 2019, IDDs increased from 31 to 34% of all deaths. The majority was redistributed using predefined ICD codes (14-15%), followed by the redistribution using multiple causes of death data (10-12%). The total number of SEYLL decreased from 1.83 to 1.73&nbsp;million per year. In 2019, the top cause of SEYLL was lung cancer with a share of 8.5%, followed by ischemic heart disease (8.1%) and Alzheimer&#8217;s disease and other dementias (5.7%). All results are available in an online tool https://burden.sciensano.be/shiny/mortality2019/ . CONCLUSION: The redistribution process assigned a specific cause of death to all deaths in Belgium, making it possible to investigate the full mortality burden for the first time. A large number of estimates were produced to estimate SEYLL by age, sex, and region for a large number of causes of death and every year between 2004 and 2019. These estimates are important stepping stones for future investigations on Disability-Adjusted Life Years (DALYs) in&nbsp;Belgium.</p

Risk factors and their contribution to population health in the European Union (EU-28) countries in 2007 and 2017

Background The Global Burden of Disease (GBD) study has generated a wealth of data on death and disability outcomes in Europe. It is important to identify the disease burden that is attributable to risk factors and, therefore, amenable to interventions. This paper reports the burden attributable to risk factors, in deaths and disability-adjusted life years (DALYs), in the 28 European Union (EU) countries, comparing exposure to risks between them, from 2007 to&nbsp;2017. Methods Retrospective descriptive study, using secondary data from the GBD 2017 Results Tool. For the EU-28 and each country, attributable (all-cause) age-standardized death and DALY rates, and summary exposure values are&nbsp;reported. Results In 2017, behavioural and metabolic risk factors showed a higher attributable burden compared with environmental risks, with tobacco, dietary risks and high systolic blood pressure standing out. While tobacco and air quality improved significantly between 2007 and 2017 in both exposure and attributable burden, others such as childhood maltreatment, drug use or alcohol use did not. Despite significant heterogeneity between EU countries, the EU-28 burden attributable to risk factors decreased in this&nbsp;period. Conclusion Accompanying the improvement of population health in the EU-28, a comparable trend is visible for attributable burden due to risk factors. Besides opportunities for mutual learning across countries with different disease/risk factors patterns, good practices (i.e. tobacco control in Sweden, air pollution mitigation in Finland) might be followed. On the opposite side, some concerning cases must be highlighted (i.e. tobacco in Bulgaria, Latvia and Estonia or drug use in Czech&nbsp;Republic).</p

Population vulnerability to COVID-19 in Europe: a burden of disease analysis

Background Evidence has emerged showing that elderly people and those with pre-existing chronic health conditions may be at higher risk of developing severe health consequences from COVID-19. In Europe, this is of particular relevance with ageing populations living with non-communicable diseases, multi-morbidity and frailty. Published estimates of Years Lived with Disability (YLD) from the Global Burden of Disease (GBD) study help to characterise the extent of these effects. Our aim was to identify the countries across Europe that have populations at highest risk from COVID-19 by using estimates of population age structure and YLD for health conditions linked to severe illness from COVID-19. Methods Population and YLD estimates from GBD 2017 were extracted for 45 countries in Europe. YLD was restricted to a list of specific health conditions associated with being at risk of developing severe consequences from COVID-19 based on guidance from the United Kingdom Government. This guidance also identified individuals aged 70 years and above as being at higher risk of developing severe health consequences. Study outcomes were defined as: (i) proportion of population aged 70 years and above; and (ii) rate of YLD for COVID-19 vulnerable health conditions across all ages. Bivariate groupings were established for each outcome and combined to establish overall population-level&nbsp;vulnerability. Results Countries with the highest proportions of elderly residents were Italy, Greece, Germany, Portugal and Finland. When assessments of population-level YLD rates for COVID-19 vulnerable health conditions were made, the highest rates were observed for Bulgaria, Czechia, Croatia, Hungary and Bosnia and Herzegovina. A bivariate analysis indicated that the countries at high-risk across both measures of vulnerability were: Bulgaria; Portugal; Latvia; Lithuania; Greece; Germany; Estonia; and&nbsp;Sweden. Conclusion Routine estimates of population structures and non-fatal burden of disease measures can be usefully combined to create composite indicators of vulnerability for rapid assessments, in this case to severe health consequences from COVID-19. Countries with available results for sub-national regions within their country, or national burden of disease studies that also use sub-national levels for burden quantifications, should consider using non-fatal burden of disease estimates to estimate geographical vulnerability to COVID-19.</p

Erratum: Population vulnerability to COVID-19 in Europe: a burden of disease analysis (Archives of Public Health (2020) 78 (47) DOI: 10.1186/s13690-020-00433-y)

Following publication of the original article [1], the authors identified an error in the author name of Brecht Devleesschauwer. The incorrect author name is: Brecht Devleeschauwer The correct author name is: Brecht Devleesschauwer The author group has been updated above and the original article [1] has been corrected