Risk of death due to COVID-19 among current and former smokers in the Netherlands: a population-based quasi-cohort study

BACKGROUND

Research on smoking as a risk factor for death due to COVID-19 remains inconclusive, with different studies demonstrating either an increased or decreased risk of COVID-19 death among smokers. To investigate this controversy, this study uses data from the Netherlands to assess the relationship between smoking and death due to COVID-19.

METHODS

In this population-based quasi-cohort study, we linked pseudonymized individual data on smoking status from the 2016 and 2020 'Health Monitor Adults and Elderly' in the Netherlands (n = 914 494) to data from the cause-of-death registry (n = 2962). Death due to COVID-19 in 2020 or 2021 was taken as the main outcome. Poisson regression modelling was used to calculate relative risks (RRs) and 95% CIs of death due to COVID-19 for current and former smokers compared with never smokers while adjusting for relevant confounders (age, sex, educational level, body mass index and perceived health).

RESULTS

Former smokers had a higher risk of death due to COVID-19 compared with never smokers across unadjusted (RR, 2.22; 95% CI, 2.04-2.42), age-sex-adjusted (RR, 1.38; 95% CI, 1.22-1.55) and fully adjusted (RR, 1.30; 95% CI, 1.16-1.45) models. Current smokers had a slightly higher risk of death due to COVID-19 compared with never smokers after adjusting for age and sex (RR, 1.21; 95% CI, 1.00-1.48) and after full adjustment (RR, 1.08; 95% CI, 0.90-1.29), although the results were statistically non-significant.

CONCLUSIONS

People with a history of smoking appear to have a higher risk of death due to COVID-19. Further research is needed to investigate which underlying mechanisms may explain this.

Societal costs of sepsis in the Netherlands

BACKGROUND

Sepsis is a life-threatening syndrome characterized by acute loss of organ function due to infection. Sepsis survivors are at risk for long-term comorbidities, have a reduced Quality of Life (QoL), and are prone to increased long-term mortality. The societal impact of sepsis includes its disease burden and indirect economic costs. However, these societal costs of sepsis are not fully understood. This study assessed sepsis's disease-related and indirect economic costs in the Netherlands.

METHODS

Sepsis prevalence, incidence, sepsis-related mortality, hospitalizations, life expectancy, QoL population norms, QoL reduction after sepsis, and healthcare use post-sepsis were obtained from previous literature and Statistics Netherlands. We used these data to estimate annual Quality-adjusted Life Years (QALYs), productivity loss, and increase in healthcare use post-sepsis. A sensitivity analysis was performed to analyze the burden and indirect economic costs of sepsis under alternative assumptions, resulting in a baseline, low, and high estimated burden. The results are presented as a baseline (low-high burden) estimate.

RESULTS

The annual disease burden of sepsis is approximately 57,304 (24,398-96,244; low-high burden) QALYs. Of this, mortality accounts for 26,898 (23,166-31,577) QALYs, QoL decrease post-sepsis accounts for 30,406 (1232-64,667) QALYs. The indirect economic burden, attributed to lost productivity and increased healthcare expenditure, is estimated at €416.1 (147.1-610.7) million utilizing the friction cost approach and €3.1 (0.4-5.7) billion using the human capital method. Cumulatively, the combined disease and indirect economic burdens range from €3.8 billion (friction method) to €6.5 billion (human capital method) annually within the Netherlands.

CONCLUSIONS

Sepsis and its complications pose a substantial disease and indirect economic burden to the Netherlands, with an indirect economic burden due to production loss that is potentially larger than the burden due to coronary heart disease or stroke. Our results emphasize the need for future studies to prevent sepsis, saving downstream costs and decreasing the economic burden.

Infographics and the knowledge translation framework

The concept of Knowledge Translation (KT) can be used to narrow the gap between knowledge producers, such as researchers, and knowledge users, such as policy makers. KT is the process in which complex research and data are translated into more easily to understand understood content to support evidence-informed policy making. KT covers a wide variety of activities including knowledge dissemination, two-way exchange process between researchers and knowledge users, and communication. The nature of these activities can be classified in four models of interaction, Push, Pull, Exchange and Integration. Especially, the push model is applied when potential users are still unaware that they should be considering information on a certain topic, which is often the case for Burden of Disease (BoD) results. Next to push method as such policy briefings and health status reports, a product focusing on visualization might be more effective. A visualized product that has gained popularity is the infographic as a collection of imagery, charts, and minimal text that gives an easy-to-understand overview of a topic. Also regarding BOD, with its complex methodology and large amounts of data and information, infographics can be an efficient tool for KT. However, the use of infographics for BoD is still rather limited and could benefit from effective data visualization techniques applied in other fields within public health. Though communication through an infographic can be rather powerful, one has to be aware that the interpretation of the infographic by the receptor can also result in less-balanced messages. In this presentation, the concept of KT will be linked to visualization techniques as infographics using good and bad examples from BoD and beyond.

Dutch DALYS: The Dutch National Burden of Disease study

The Netherlands National Institute for Public health and the Environment published for more than 25 years their National Burden of Disease estimates (Dutch DALYs). This is done as part of their Public health Status and Foresight study which is commissioned by the Ministry of Health. In these 25 years, the translation of knowledge resulting from the Burden of Disease study has been progressed over the years. The knowledge translation has both pull and push elements. Various stakeholders are consulted for example to select health conditions and relevant risk factors, to better interpret input data and to compare results with other burden of disease results. As push elements, website, concise reporting and visualization techniques such as infographics are being used. Burden of disease results are being used in several Dutch policy documents. Policy goals to reduce avoidable disease burden is based on the results of the Dutch DALY studies. In addition, the allocation of disease burden to underlying risk factors receives substantial attention from policy maker to prioritize policies on prevention. It is also used by other organizations to advocate specific issues, such as cardiovascular diseases. However, policy makers still have difficulties interpreting a complex metric as the Disability-Adjusted Life Year (DALY). In the Netherlands, the uptake by policy makers of burden of disease results has increased strongly over the years and forms by now an essential aspect of public health reporting. However, improving understanding of the DALY concept, for example by using complementary metrics such as the healthy life expectancy, could stimulate its use further. Also, the allocation to risk factors is used frequently. Policy makers indicated that a better link of risk factors to policy interventions, is a valuable next step.

Dutch DALYs, current and future burden of disease in the Netherlands

BACKGROUND

The Disability Adjusted Life Year (DALY) is a measure to prioritize in the public health field. In the Netherlands, the DALY estimates are calculated since 1997 and are included in the Public Health Status and Foresight studies which is an input for public health priority setting and policy making. Over these 20 years, methodological advancements have been made, including accounting for multimorbidity and performing projections for DALYs into the future. Most important methodological choices and improvements are described and results are presented.

METHODS

The DALY is composed of the two components years of life lost (YLL) due to premature mortality and years lost due to disability (YLD). Both the YLL and the YLD are distinguished by sex, age and health condition, allowing aggregation to the ICD-10 chapters. The YLD is corrected for multimorbidity, assuming independent occurrence of health conditions and a multiplicative method for the calculation of combined disability weights. Future DALYs are calculated based on projections for causes of death, and prevalence and incidence.

RESULTS

The results for 2015 show that cancer is the ICD-10 chapter with the highest disease burden, followed by cardiovascular diseases and mental disorders. For the individual health conditions, coronary heart disease had the highest disease burden in 2015. In 2040, we see a strong increase in disease burden of dementia and arthrosis. For dementia this is due to a threefold increase in dementia as a cause of death, while for arthrosis this is mainly due to the increase in prevalence.

CONCLUSIONS

To calculate the DALY requires a substantial amount of data, methodological choices, interpretation and presentation of results, and the personnel capacity to carry out all these tasks. However, doing a National Burden of Disease study, and especially doing that for more than 20 years, proved to have an enormous additional value in population health information and thus supports better public health policies.

Knowledge translation and health policy for burden of disease

A key goal of most Burden of Disease (BoD) studies is to support public health policies. However, while the concepts of BoD and Disability Adjusted Life years have been introduced more than 25 years, BoD researchers are still struggling to find better ways to translate their findings and communicate them to the relevant decision makers and other stakeholders.

To address this gap, the burden-eu COST Action aims to generate better guidance of the use of BoD metrics in policy-making processes. In collaboration with experts in knowledge translation and risk communication, the Action will compile good practices in knowledge translation and develop a roadmap to integrate knowledge translation in national BOD studies. To support these objectives, collaborations have been established with knowledge translation experts from the European Observatory on Health Systems and Policies, the WHO Regional Office for Europe, and the European Public Health Association.

During an initial meeting of the “knowledge translation” working group, 29 participants identified elements in the pathway from evidence generation to practice that need to be addressed. Building on the outcomes of this meeting and the inputs from the knowledge translation experts, this presentation will introduce the knowledge translation framework, and address some of the challenges in identifying best routes to reach out to the public and policy-makers. Specific emphasis will be placed in profiling the context, actors and processes of each country within the policy triangle, and drawing on best and worst example case studies. Additionally, the process will be discussed to co-create a toolkit or guide for using BoD evidence in policy and practice. The session will conclude with an interaction with the audience to learn about the perceived barriers for implementing knowledge translation within the BoD framework.

Forecasting health prior to state pension age – projections for the Netherlands 2040

Objectives

In many Western societies, the state pension age is being raised to stimulate prolonged working. In the Netherlands, the raise of the state pension age is linked to the remaining life expectancy at age 65 with a factor of 2/3rd, and is expected to be 68 years in 2040. It is not yet well understood whether health of the 60+ permits this increase. In this study, health of Dutch adults aged 60 to 68 is forecasted up to 2040.

Methods

Data are from the Dutch Health Interview Survey (HIS) 1990-2017 (N≈280.000) and the Dutch Public Health Monitor (PHM) 2016 (N≈460.000). Health is operationalized using binomial scores of 1) self-rated health and 2) limitations in hearing, seeing or mobility. Categories are: good health (healthy on both items), moderate health (healthy on one item) and poor health (unhealthy on both items). First, based on the HIS, health status in 5-year age categories was modelled up to 2040 using logistic regression analysis in R. Second, the growth factor from 2016 to 2040 was applied to the health level from the PHM 2016.

Results

In 2016, 63% of men aged 60-65 had good health, 25% had moderate health and 12% had poor health. Among women, this distribution was 64%, 22% and 14%, respectively. In 2040, the health distribution among men aged 60-68 is estimated to be 63-71% in good health, 17-28% in moderate health and 9-12% in poor health. Among women this is estimated to be 64-69%, 17-24% and 12-14%, respectively.

Conclusions

Health of Dutch cohorts nearing the state pension age in the future is estimated to remain the same or improve up to 2040. This development in health is not an obstacle to raising the state pension age. However, due to the increasing state pension age and the baby boom generation reaching age 60+ in the coming years, the absolute number of people aged 60+ in poor and moderate health that participates in labor will increase. Policy aiming at sustainable employability will therefore become increasingly important.

Key messages

Health of Dutch cohorts nearing the state pension age is estimated to remain the same or improve in the future. The development in health is not an obstacle to raising the state pension age. Although health is estimated to remain the same or improve, the absolute number of people aged 60+ in poor and moderate health that participate in labor will increase due to an aging population.

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.

Quantitative Health Impact Assessment Methodology for Societal Initiatives: A Scoping Review

Background

Promoting health rather than treating disease is gaining popularity and promotion initiatives are increasingly situated in the societal domain. In this scoping review, the literature on quantitative health impact assessment (HIA) practice and methodology is explored in order to provide an overview of methods that have been used or proposed for estimating societal initiatives’ health outcomes.

Methods

Systematic searches were done in PubMed and Web of Science in order to identify relevant literature. A set of selection criteria ensured that studies held useful quantitative HIA methodology and a societal approach. Reference lists of all selected studies were then examined for other studies. After literature selection, quantifiable features of interest were recorded and general observations on the composition of the current literature were made.

Results

The literature selection process yielded 54 included studies, most of which focus on lifestyle-related determinants. Of different health outcome measurements, deaths (averted) was most frequently used, followed by life years and quality- and disability-adjusted life years. Equity is frequently mentioned, but not often estimated. Most studies made estimates based on simulation models, notably with Monte Carlo, Markov and system dynamics models (simulation period mean 46 years; median 50 years). Inputs for the models such as relative risks, transition probabilities and price elasticities were taken from census and register data, survey data, evidence from previous (scientific) studies and outcomes from stakeholder sessions.

Conclusions

HIA holds a wide range of practices with some overlap. Different methods’ strengths and weaknesses partly depend on the phenomenon of interest. Some policy types have standard approaches, but there is no one universal optimal method and therefore having a grasp of multiple methods is useful. Furthermore, estimating health effect distributions could make an important addition to HIA.

Key messages

Quantitative HIA can be conducted using various methodological bases and most studies use some form of simulation modelling. Different simulation methods are distinct, but do show some overlap. Quantitative HIA topics often relate to individual behaviour (micro-level proximal determinants). There is room for HIA method development for determinants with indirect connections to the individual.

The Dutch Public Health Foresight Study 2018: an example of a comprehensive foresight exercise

Background

The use of foresight studies is common in some policy fields, but not in public health. Interest in such studies is growing. This paper gives a general overview of the Dutch Public Health Foresight Study (PHFS) 2018, providing insight into what performing a broad scenario exercise in the field of public health entails and its societal impacts.

Methods

The aim of the PHFS-2018 was: (a) to show how public health and healthcare in the Netherlands will develop over the next 25 years if we pursue our current course and detect ‘new’ developments; (b) to give options for dealing with the major future societal challenges. Part a was addressed by means of a quantitative business-as-usual scenario exercise complemented with qualitative thematic studies, and part b by elaborating courses of action for three key challenges, based on stakeholder consultation. Typical aspects of the PHFS methods are a multidisciplinary, participatory and conceptual approach and using a broad definition of health.

Results

The PHFS-2018 is the basis for the upcoming National Health Policy Memorandum and the Trend Scenario is the baseline for the National Prevention Agreement. Unexpectedly, the findings about increasing mental pressure in young people received most attention. There still is room for expanding use of the study to its full potential.

Conclusions

Long-term thinking could be stimulated by using back casting techniques and stronger involvement of policy-makers in the elaboration of options for action. Lessons learned from developing intersectoral policy at the local level could be applied at the national level.

Global, regional, and national life expectancy, all-cause mortality, and cause-specific mortality for 249 causes of death, 1980-2015: a systematic analysis for the Global Burden of Disease Study 2015

BACKGROUND

Improving survival and extending the longevity of life for all populations requires timely, robust evidence on local mortality levels and trends. The Global Burden of Disease 2015 Study (GBD 2015) provides a comprehensive assessment of all-cause and cause-specific mortality for 249 causes in 195 countries and territories from 1980 to 2015. These results informed an in-depth investigation of observed and expected mortality patterns based on sociodemographic measures.

METHODS

We estimated all-cause mortality by age, sex, geography, and year using an improved analytical approach originally developed for GBD 2013 and GBD 2010. Improvements included refinements to the estimation of child and adult mortality and corresponding uncertainty, parameter selection for under-5 mortality synthesis by spatiotemporal Gaussian process regression, and sibling history data processing. We also expanded the database of vital registration, survey, and census data to 14 294 geography-year datapoints. For GBD 2015, eight causes, including Ebola virus disease, were added to the previous GBD cause list for mortality. We used six modelling approaches to assess cause-specific mortality, with the Cause of Death Ensemble Model (CODEm) generating estimates for most causes. We used a series of novel analyses to systematically quantify the drivers of trends in mortality across geographies. First, we assessed observed and expected levels and trends of cause-specific mortality as they relate to the Socio-demographic Index (SDI), a summary indicator derived from measures of income per capita, educational attainment, and fertility. Second, we examined factors affecting total mortality patterns through a series of counterfactual scenarios, testing the magnitude by which population growth, population age structures, and epidemiological changes contributed to shifts in mortality. Finally, we attributed changes in life expectancy to changes in cause of death. We documented each step of the GBD 2015 estimation processes, as well as data sources, in accordance with Guidelines for Accurate and Transparent Health Estimates Reporting (GATHER).

FINDINGS

Globally, life expectancy from birth increased from 61·7 years (95% uncertainty interval 61·4-61·9) in 1980 to 71·8 years (71·5-72·2) in 2015. Several countries in sub-Saharan Africa had very large gains in life expectancy from 2005 to 2015, rebounding from an era of exceedingly high loss of life due to HIV/AIDS. At the same time, many geographies saw life expectancy stagnate or decline, particularly for men and in countries with rising mortality from war or interpersonal violence. From 2005 to 2015, male life expectancy in Syria dropped by 11·3 years (3·7-17·4), to 62·6 years (56·5-70·2). Total deaths increased by 4·1% (2·6-5·6) from 2005 to 2015, rising to 55·8 million (54·9 million to 56·6 million) in 2015, but age-standardised death rates fell by 17·0% (15·8-18·1) during this time, underscoring changes in population growth and shifts in global age structures. The result was similar for non-communicable diseases (NCDs), with total deaths from these causes increasing by 14·1% (12·6-16·0) to 39·8 million (39·2 million to 40·5 million) in 2015, whereas age-standardised rates decreased by 13·1% (11·9-14·3). Globally, this mortality pattern emerged for several NCDs, including several types of cancer, ischaemic heart disease, cirrhosis, and Alzheimer's disease and other dementias. By contrast, both total deaths and age-standardised death rates due to communicable, maternal, neonatal, and nutritional conditions significantly declined from 2005 to 2015, gains largely attributable to decreases in mortality rates due to HIV/AIDS (42·1%, 39·1-44·6), malaria (43·1%, 34·7-51·8), neonatal preterm birth complications (29·8%, 24·8-34·9), and maternal disorders (29·1%, 19·3-37·1). Progress was slower for several causes, such as lower respiratory infections and nutritional deficiencies, whereas deaths increased for others, including dengue and drug use disorders. Age-standardised death rates due to injuries significantly declined from 2005 to 2015, yet interpersonal violence and war claimed increasingly more lives in some regions, particularly in the Middle East. In 2015, rotaviral enteritis (rotavirus) was the leading cause of under-5 deaths due to diarrhoea (146 000 deaths, 118 000-183 000) and pneumococcal pneumonia was the leading cause of under-5 deaths due to lower respiratory infections (393 000 deaths, 228 000-532 000), although pathogen-specific mortality varied by region. Globally, the effects of population growth, ageing, and changes in age-standardised death rates substantially differed by cause. Our analyses on the expected associations between cause-specific mortality and SDI show the regular shifts in cause of death composition and population age structure with rising SDI. Country patterns of premature mortality (measured as years of life lost [YLLs]) and how they differ from the level expected on the basis of SDI alone revealed distinct but highly heterogeneous patterns by region and country or territory. Ischaemic heart disease, stroke, and diabetes were among the leading causes of YLLs in most regions, but in many cases, intraregional results sharply diverged for ratios of observed and expected YLLs based on SDI. Communicable, maternal, neonatal, and nutritional diseases caused the most YLLs throughout sub-Saharan Africa, with observed YLLs far exceeding expected YLLs for countries in which malaria or HIV/AIDS remained the leading causes of early death.

INTERPRETATION

At the global scale, age-specific mortality has steadily improved over the past 35 years; this pattern of general progress continued in the past decade. Progress has been faster in most countries than expected on the basis of development measured by the SDI. Against this background of progress, some countries have seen falls in life expectancy, and age-standardised death rates for some causes are increasing. Despite progress in reducing age-standardised death rates, population growth and ageing mean that the number of deaths from most non-communicable causes are increasing in most countries, putting increased demands on health systems.

FUNDING

Bill & Melinda Gates Foundation.

Accounting for multimorbidity can affect the estimation of the Burden of Disease: a comparison of approaches

Background

Various Burden of Disease (BoD) studies do not account for multimorbidity in their BoD estimates. Ignoring multimorbidity can lead to inaccuracies in BoD estimations, particularly in ageing populations that include large proportions of persons with two or more health conditions. The objective of this study is to improve BoD estimates for the Netherlands by accounting for multimorbidity. For this purpose, we analyzed different methods for 1) estimating the prevalence of multimorbidity and 2) deriving Disability Weights (DWs) for multimorbidity by using existing data on single health conditions.

Methods

We included 25 health conditions from the Dutch Burden of Disease study that have a high rate of prevalence and that make a large contribution to the total number of Years Lived with a Disability (YLD). First, we analyzed four methods for estimating the prevalence of multimorbid conditions (i.e. independent, independent age- and sex-specific, dependent, and dependent sex- and age-specific). Secondly, we analyzed three methods for calculating the Combined Disability Weights (CDWs) associated with multimorbid conditions (i.e. additive, multiplicative and maximum limit). A combination of these two approaches was used to recalculate the number of YLDs, which is a component of the Disability-Adjusted Life Years (DALY).

Results

This study shows that the YLD estimates for 25 health conditions calculated using the multiplicative method for Combined Disability Weights are 5 % lower, and 14 % lower when using the maximum limit method, than when calculated using the additive method. Adjusting for sex- and age-specific dependent co-occurrence of health conditions reduces the number of YLDs by 10 % for the multiplicative method and by 26 % for the maximum limit method. The adjustment is higher for health conditions with a higher prevalence in old age, like heart failure (up to 43 %) and coronary heart diseases (up to 33 %). Health conditions with a high prevalence in middle age, such as anxiety disorders, have a moderate adjustment (up to 13 %).

Conclusions

We conclude that BoD calculations that do not account for multimorbidity can result in an overestimation of the actual BoD. This may affect public health policy strategies that focus on single health conditions if the underlying cost-effectiveness analysis overestimates the intended effects. The methodology used in this study could be further refined to provide greater insight into co-occurrence and the possible consequences of multimorbid conditions in terms of disability for particular combinations of health conditions.

[Living longer, with more disease and less disability; trends in public health 2000-2030]

The Dutch Public Health Status and Foresight report 2014 explores the future of public health in the Netherlands, using a trend scenario and four future scenarios. The trend scenario provides projections until 2030, based on the trends over the last decades and assuming the policy stays the same. After many years the unfavourable trends in lifestyle seem to have ended: the percentage of smokers is decreasing and the percentage of people who are overweight is no longer increasing. Life expectancy will continue to increase, but the differences between socioeconomic groups will not become smaller. Demographic changes (rise in the ageing population) and improvements in health care will contribute to an increase in the number of chronically ill which will increase from 5.3 million in 2011 to 7 million in 2030. However, most people with a chronic disease feel healthy, have no disabilities and participate fully in society. Health care expenditures rose from 9.5% of the GDP in 2000 to 14% in 2012. How this growth will continue in the next years is uncertain.