Kim Moesgaard Iburg

Background: It is important to understand the effects of population ageing on disease burden and explore conditions that drive poor health in later life to prevent or manage these. We examined the development of disease burden and its components for major disease groups among older adults in Europe over the last 30 years. Methods: Using data from the Global Burden of Disease 2019 Study, we analyzed burden of disease trends between 1990 and 2019 measured by years of life lost (YLL), years lived with disability (YLD) and disability-adjusted life years (DALYs) among older adults (65+ years) in Western, Central and Eastern Europe using cause groups for diseases and injuries. Results: Between 1990 and 2019, the crude numbers of DALYs for all causes increased substantially among older Western Europeans. In Eastern Europe, the absolute DALYs also increased from 1990 to 2005 but then decreased between 2006 and 2013. However, DALY rates declined for all European regions over time, with large differences in the magnitude by region and gender. Changes in the YLL rate were mainly driven by the contribution of cardiovascular diseases. Conclusions: This study found an increased overall absolute disease burden among older Europeans between 1990 and 2019. The demographic change that has taken place in Eastern European countries implies a potential problem of directed resource allocation to the health care sector. Furthermore, the findings highlight the potential health gains through directing resources to health promotion and treatment to reduce YLDs and to prevent YLLs, primarily from cardiovascular diseases.

Background: The provision of different types of mortality metrics (e.g., mortality rate ratios [MRRs] and life expectancy) allows the research community to access a more informative set of health metrics. The aim of this study was to provide a panel of mortality metrics associated with a comprehensive range of disorders and to design a web page to visualize all results. Methods and findings: In a population-based cohort of all 7,378,598 persons living in Denmark at some point between 2000 and 2018, we identified individuals diagnosed at hospitals with 1,803 specific categories of disorders through the International Classification of Diseases-10th Revision (ICD-10) in the National Patient Register. Information on date and cause of death was obtained from the Registry of Causes of Death. For each of the disorders, a panel of epidemiological and mortality metrics was estimated, including incidence rates, age-of-onset distributions, MRRs, and differences in life expectancy (estimated as life years lost [LYLs]). Additionally, we examined models that adjusted for measures of air pollution to explore potential associations with MRRs. We focus on 39 general medical conditions to simplify the presentation of results, which cover 10 broad categories: circulatory, endocrine, pulmonary, gastrointestinal, urogenital, musculoskeletal, hematologic, mental, and neurologic conditions and cancer. A total of 3,676,694 males and 3,701,904 females were followed up for 101.7 million person-years. During the 19-year follow-up period, 1,034,273 persons (14.0%) died. For 37 of the 39 selected medical conditions, mortality rates were larger and life expectancy shorter compared to the Danish general population. For these 37 disorders, MRRs ranged from 1.09 (95% confidence interval [CI]: 1.09 to 1.10) for vision problems to 7.85 (7.77 to 7.93) for chronic liver disease, while LYLs ranged from 0.31 (0.14 to 0.47) years (approximately 16 weeks) for allergy to 17.05 (16.95 to 17.15) years for chronic liver disease. Adjustment for air pollution had very little impact on the estimates; however, a limitation of the study is the possibility that the association between the different disorders and mortality could be explained by other underlying factors associated with both the disorder and mortality. Conclusions: In this study, we show estimates of incidence, age of onset, age of death, and mortality metrics (both MRRs and LYLs) for a comprehensive range of disorders. The interactive data visualization site (https://nbepi.com/atlas) allows more fine-grained analysis of the link between a range of disorders and key mortality estimates.

Objectives: Work-related stress and certain lifestyles have been associated with sickness absence among employees. We analysed relations between stress and lifestyles (as risk factors) and short-term sickness absence among employees of a large Danish industrial company. Moreover, we analysed the impact of risk factors on short-term sickness absence. Methods: A self-administered questionnaire was completed by 7753 employees (67% response rate). Relations between risk factors (dyssomnia, low physical activity, alcohol, smoking, unhealthy food habits, overweight and stress) and short-term sickness absence were analysed by calculating etiologic fractions and binary logistic regression. Relations between the number of risk factors and short-term sickness absence were also analysed. Finally, the cost of short-term sickness absence from risk factors was estimated to illustrate the potential savings in avoided loss of productivity that could be gained from intervention programmes. Results: Stress, overweight, smoking and dyssomnia are significantly related to short-term sickness absence. Etiologic fractions revealed that these factors were associated with between 29.8% and 37.8% of short-term sickness absence. The number of risk factors was also related to the risk and length of sickness absence. Conclusions: This study identified risk factors that could be addressed by intervention programmes to reduce short-term sickness absence. Based on the results, focus on the risk factors that account for most short-term sickness absence and reduction of the number of risk factors could potentially reduce short-term sickness absence. A 30% reduction is equivalent to an avoidance of a loss of productivity of 4.5%, corresponding to €9.4 million per year.

Many countries have used the new ANACONDA (Analysis of Causes of National Death for Action) tool to assess the quality of their cause of death data (COD), but no cross-country analysis has been done to verify how different or similar patterns of diagnostic errors and data quality are in countries or how they are related to the local cultural or epidemiological environment or to levels of development. Our objective is to measure whether the usability of COD data and the patterns of unusable codes are related to a country’s level of socio-economic development. We have assessed the quality of 20 national COD datasets from the WHO Mortality Database by assessing their completeness of COD reporting and the extent, pattern and severity of garbage codes, i.e. codes that provide little or no information about the true underlying COD. Garbage codes were classified into four groups based on the severity of the error in the code. The Vital Statistics Performance Index for Quality (VSPI(Q)) was used to measure the overall quality of each country’s mortality surveillance system. The proportion of ‘garbage codes’ varied from 7 to 66% across the 20 countries. Countries with a high SDI generally had a lower proportion of high impact (i.e. more severe) garbage codes than countries with low SDI. While the magnitude and pattern of garbage codes differed among countries, the specific codes commonly used did not. There is an inverse relationship between a country’s socio-demographic development and the overall quality of its cause of death data, but with important exceptions. In particular, some low SDI countries have vital statistics systems that are as reliable as more developed countries. However, in low-income countries, where most people die at home, the proportion of unusable codes often exceeds 50%, implying that half of all cause-specific mortality data collected is of little or no use in guiding public policy. Moreover, the cause of death pattern identified from the data is likely to seriously under-represent the true extent of the leading causes of death in the population, with very significant consequences for health priority setting. Garbage codes are prevalent at all ages, contrary to expectations. Further research into effective strategies deployed in these countries to improve data quality can inform efforts elsewhere to improve COD reporting systems.

Background: The need to monitor the Sustainable Development Goals (SDGs) and to have access to reliable and timely mortality data has created a strong demand in countries for tools that can assist them in this. ANACONDA (Analysis of National Causes of Death for Action) is a new tool developed for this purpose which allows countries to assess how accurate their mortality and cause of death are. Applying ANACONDA will increase confidence and capacity among data custodians in countries about their mortality data and will give them insight into quality problems that will assist the improvement process. Methods: ANACONDA builds on established epidemiological and demographic concepts to operationalise a series of 10 steps and numerous sub-steps to perform data checks. Extensive use is made of comparators to assess the plausibility of national mortality and cause of death statistics. The tool calculates a composite Vital Statistics Performance Index for Quality (VSPI(Q)) to measure how fit for purpose the data are. Extracts from analyses of country data are presented to show the types of outputs. Results: Each of the 10 steps provides insight into how well the current data is describing different aspects of the mortality situation in the country, e.g. who dies of what, the completeness of the reporting, and the amount and types of unusable cause of death codes. It further identifies the exact codes that should not be used by the certifying physicians and their frequency, which makes it possible to institute a focused correction procedure. Finally, the VSPI(Q) allows periodic monitoring of data quality improvements and identifies priorities for action to strengthen the Civil Registration and Vital Statistics (CRVS) system. Conclusions: ANACONDA has demonstrated the potential to dramatically improve knowledge about disease patterns as well as the functioning of CRVS systems and has served as a platform for galvanising wider CRVS reforms in countries.

Objectives To assess the policy utility of national cause of death (COD) data of six high-income countries with highly developed health information systems. Methods National COD data sets from Australia, Canada, Denmark, Germany, Japan and Switzerland for 2015 or 2016 were assessed by applying the ANACONDA software tool. Levels, patterns and distributions of unusable and insufficiently specified “garbage” codes were analysed. Results The average proportion of unusable COD was 18% across the six countries, ranging from 14% in Australia and Canada to 25% in Japan. Insufficiently specified codes accounted for a further 8% of deaths, on average, varying from 6% in Switzerland to 11% in Japan. The most commonly used garbage codes were Other ill-defined and unspecified deaths (R99), Heart failure (I50.9) and Senility (R54). Conclusions COD certification errors are common, even in countries with very advanced health information systems, greatly reducing the policy value of mortality data. All countries should routinely provide certification training for hospital interns and raise awareness among doctors of their public health responsibility to certify deaths correctly and usefully for public health policy.

Background: While the system of registration of mortality and cause of death (COD) in Greenland was established several decades ago, reporting procedures follow a complicated administrative process. Timely and reliable reporting on mortality and COD is of high importance for the usability of the collected data for research, health planning and decision making. Methods: COD data collected by the Chief Medical Office in Greenland from 2006 to 2015 (4490 registered deaths) were analysed with the software Analysis of National Causes of Death for Action (ANACONDA) v4.0. Unusable or insufficiently specified ICD codes are identified. The Vital Statistics Performance Index for Quality (VSPI(Q)) is estimated for the overall quality conclusions of the register’s usability. Results: Sixty-eight per cent of the input data for Greenland was coded with a usable underlying COD, 24% with an unusable cause and 8% of deaths with an insufficiently specified cause. Almost 700 deaths were coded to an unusable code of ‘very high impact’. The most prevalent unusable underlying causes were other ill-defined and unspecified causes, including no death certificate available, followed by senility, heart failure, sepsis and shock and cardiac arrest. The VSPI(Q) score was 66%, representing medium quality. Conclusions: In the 10 years’ worth of data analysed, the true underlying COD in many cases was unknown. Several likely explanations for this include lack of systematic COD training for physicians, logistic and capacity challenges in Greenland that potentially could reduce the quality of the collected data and its usability in providing essential information about the true pattern of mortality in Greenland.

Background. Alcohol misuse is a global public health priority, with a variation in prevalence and impact between countries. Alcohol misuse in adolescence is associated with adverse psychological, social and physical health. Adolescents in Denmark have higher alcohol consumption and problematic alcohol use than adolescents in other European countries. Associations between social determinants of health (SDH), psycho-social factors and alcohol consumption are complex and influenced by national context and cultures. This study explored these associations in Danish adolescents. Method. The European School Survey Project on Alcohol and Other Drugs (ESPAD) survey collects data on alcohol and substance use among 15–16-year-old European students. Data contributed by Danish students to the 2011 survey were analyzed. The outcomes of interest were alcohol consumption (any, intoxication and problematic). Health literacy was not directly measured, so self-described educational performance and knowledge about alcohol were used as proxies for health literacy. Exploratory factors thus included socio-demographic, health literacy-related (knowledge about alcohol, educational performance) and psycho-social factors, as well as expectancies of the effect of alcohol (both positive and negative) and self-reported health. Univariate and multivariate logistic regression analyses were undertaken. Results. Of the 2768 adolescents who participated in the survey, 2026 (80%) consumed alcohol during the last 30 days, 978 (38%) were intoxicated at least once during the last 30 days, and 1050 (41%) experienced at least one problem because of alcohol use during the last 12 months. Multivariable analysis showed that the factors associated with higher alcohol intake were gender, poor relationships with parents, expectancies of the impact of alcohol (both positive and negative), and the influence of peers and their alcohol use. Higher school performance was related to lower alcohol consumption. Low socio-demographic status was not associated with higher alcohol consumption. Conclusions. This study confirmed the high levels of alcohol intake, intoxication, and problem drinking amongst the Danish students in the survey and the complexity of the socio-demographic, psychosocial, health literacy-related, and environmental factors associated with alcohol behaviours. Approaches to addressing the issue of alcohol use in Danish adolescents will need to be multi-factorial, including supporting students to develop alcohol-related health literacy skills to enable them to make informed choices.