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Lung Facts is updated regularly. The work builds on two previous editions of the European Lung White Book. These drew on data from the World Health Organization (WHO) and European Centre for Disease Prevention and Control. A key limitation of these previous publications was the differences in data resources available as well as data collection, which prevented an accurate comparison of the state of lung health between countries.
Lung Facts aims to go one step further by providing a systematic, uniform approach. By taking data from the GBD studies, Lung Facts can present a more uniform evaluation of the current state of lung health for seven respiratory disease areas.
What is the Global Burden of Disease (GBD) study?
The Global Burden of Disease study (GBD) brings together administrative data, and data from registration systems, disease registries, epidemiological surveillance systems and primary scientific studies, alongside survey data on self-reported health and health-related risk behaviours. This data is collected at regional, national and sub-national levels from across the globe and integrated into a single statistical model.
In using a single cohesive approach across the world, the GBD study brings together a huge volume of data and evidence in order to estimate disease-specific incidence, prevalence and mortality alongside a demographic model that allows the calculation of Years of Life Lost and Disability-Adjusted Life Years.
To combat issues with underdiagnosis, the GBD corrects for the underreporting of data. For example, if a country has very different rates of a health condition than similar neighbours, the model will assume there is some degree of reporting error, unless there is some other factor that can reasonably explain the discrepancy (e.g. much higher rates of smoking).
Lung Facts presents the incidence, prevalence, mortality, disability-adjusted life years (DALYs), and years of life lost (YLL) taken directly from the GBD. It also presents the societal cost (in the form of monetised DALYs) of each condition, calculated using GBD data and the monetary value of Gross Domestic Product (GDP) across countries and per country. All data are presented in chart format to build up a picture and usable reference for the burden of lung disease.
Lung Facts currently provides data on countries in the WHO European Region. This includes 53 countries: Albania, Andorra, Armenia, Austria, Azerbaijan, Belarus, Belgium, Bosnia and Herzegovina, Bulgaria, Croatia, Cyprus, Czech Republic, Denmark, Estonia, Finland, France, Georgia, Germany, Greece, Hungary, Iceland, Ireland, Israel, Italy, Kazakhstan, Kyrgyzstan, Latvia, Lithuania, Luxembourg, Malta, Moldova, Monaco, Montenegro, Netherlands, North Macedonia, Norway, Poland, Portugal, Romania, Russia, San Marino, Serbia, Slovakia, Slovenia, Spain, Sweden, Switzerland, Tajikistan, Turkey, Turkmenistan, Ukraine, United Kingdom, Uzbekistan.
Health metrics in the GBD
Incidence
Incidence looks at how frequently new cases of a disease occur within a population. Lung Facts reports an estimate of new cases per year as a total number for the country or region, and as a rate per 100,000 population. These figures can be used to understand the probability of a person developing a specific condition within the population.
Prevalence
Prevalence estimates the share of the population that has a given condition within a given time period. It includes all new and pre-existing cases within the time period and is reported in Lung Facts as estimated total numbers per country or region, and as estimated rates per 100,000 population per annum.
Mortality
Mortality is an estimate of the number of deaths from a particular condition. Total number of deaths per country or region, and death rate per 100,000 population per annum is used in Lung Facts.
Years of life lost (YLL)
YLL is a measure of premature death that takes into account both the rate of deaths (mortality) and the age at which it occurs. For example, if only mortality measurements are used, deaths at the age of 90 would be treated the same as a death at the age of 30. YLLs are calculated by looking at the total number of deaths multiplied by a global standard life expectancy at the age at which death occurs.
Disability-adjusted life years (DALYs)
DALYs are a measure combining length of life (YLL) and quality of life. They allow us to estimate the total number of healthy years lost due to specific conditions. A year in full health is one DALY. If one DALY is lost, it could mean that we have lost one year of life in full health. It could also mean that patients live for the same amount of time, but that their health is worse during that time. By multiplying the change to length of life (YLL) with the change to quality of life, an estimate of the number of DALYs saved or lost is made.
Societal cost : monetised DALYs
Within Lung Facts, the economic value of healthy years lost because of a condition is presented as the societal cost of a condition’s burden. This is calculated by applying a cost based on a country’s national wealth per citizen, referred to as the gross domestic product (GDP) per capita, to a metric of healthy years lost because of specific conditions and risk factors, referred to as disability-adjusted life-years (DALYs).
It is calculated as follows:
- DALYs x GDP per capita.
The societal cost of a condition’s burden is therefore based on when 1 DALY is valued at the GDP per capita for a specific country. Within Lung Facts, the societal cost is presented in international dollars, euros and countries own currency for the year 2022 (Int$2022) based on purchasing power parity (PPP). Purchasing power parity (PPP) is a theory which states that exchange rates between currencies are in equilibrium when their purchasing power is the same. As such, PPP-adjusted figures represented by international dollars (Int$) allows for a better comparison between countries.
These monetised DALY estimates can be interpreted in a few ways to aid negotiation and target setting with policy and decision makers. First, a total monetary value of that condition’s burden.
Other interpretations are dependent on if policymakers adopt the monetised DALY valuation as a decision rule to inform investment in averting DALYs within their country. For example, if policymakers were to adopt this valuation as a decision rule, then other interpretations could include:
- a potentially cost-effective upper limit on investment – anything spent up to this amount could be considered a cost-effective investment in terms of preventing DALYs
- To understand how much budget to allocate for a X% reduction in DALYs – for a 1% reduction you could use the calculation: GDP per capita*0.01*DALYs
- To understand how many DALYs should be prevented for a pre-specified allocated budget – for an example $5m budget you would use the calculation: 5,000,000/GDP per capita.
In essence, GDP per capita is used to scale the monetary value of the DALY to the resources available in each country to tackle the DALY burden. Thus, this societal cost is used as a reference point to suggest an amount which could be invested in lung care based on the equivalent potential societal cost of the lung condition burden.
Monetised DALYs based on GDP per capita are, by intention and design, a simplistic approach to valuing the health-related DALY metric. They are designed to be useful as a benchmark value to inform investment in healthcare relative to other sectors of the economy. However, they should not be viewed as an accurate measure of a population’s preference for spending on health (or the policymakers preference who work on behalf of the population) nor the potential value of health opportunity cost.
Please refer to the following published journal article for more detailed information about the theory, calculation, and use of these societal costs:
Franklin, M., Angus, C., Welte, T. et al. How Much Should be Invested in Lung Care Across the WHO European Region? Applying a Monetary Value to Disability-Adjusted Life-Years Within the International Respiratory Coalition’s Lung Facts. Appl Health Econ Health Policy 21, 547–558 (2023). https://doi.org/10.1007/s40258-023-00802-y
You can also download the data used to calculate the DALY societal cost for the latest edition of Lung Facts.
Non-GBD disease areas
Several respiratory conditions were not included within the GBD database or published literature. Or at least not in a way that we could extract data for a specific condition. Therefore, a systematic approach was taken to collect data for influenza, alpha-1-antitrypsin deficiency, bronchiectasis, cystic fibrosis, obstructive sleep apnoea and pulmonary vascular disease (2022 only).
For influenza, incidence and mortality data were taken from the GBD 2017 Influenza Collaborators paper*, which was identified through systematic searches for GBD studies conducted in January 2022.
*Collaborators GBDI. Mortality, morbidity, and hospitalisations due to influenza lower respiratory tract infections, 2017: an analysis for the Global Burden of Disease Study 2017. Lancet Respiratory Medicine 2019 ;7: 69-89.
Focused searches of bibliographic databases were used to find studies on alpha-1, bronchiectasis, cystic fibrosis, influenza, obstructive sleep apnoea and pulmonary vascular disease. Experts in the field were also consulted to identify any unpublished or registry data.
These conditions were split into two categories: commonly studied conditions (cystic fibrosis, influenza, obstructive sleep apnoea) and less-commonly studied conditions (alpha-1, bronchiectasis, pulmonary hypertension).
Searches for the commonly studied conditions sought to identify reviews and systematic reviews only. For the less-commonly studied conditions, all study designs were sought since it was anticipated that there would be a limited amount of literature available.
Initial searches took place in May 2022, and covered the period between January 2010 and May 2022, to be consistent with the 2010 limit of searches for the GBD diseases. Searches were updated in May 2024.
Contributors
Lung Facts Steering group
The Lung Facts Steering group is responsible for overseeing all decision about the Lung Facts:
- Guy Joos, Emeritus Professor at Ghent University and Pulmonologist, Ghent University Hospital
- Zorana Jovanovic Andersen, Professor in Environmental Epidemiology at the Department of Public Health, University of Copenhagen, Denmark
- Ane Johannessen, Professor of epidemiology at University of Bergen (UiB) and Head of Centre for interprofessional workplace learning (TVEPS)
- Barbara Hoffmann, Professor of Environmental Epidemiology at the Heinrich-Heine-University of Düsseldorf, Germany
- Joan Soriano, Associate Professor of Medicine, Hospital Universitario de la Princesa and Universidad Autónoma de Madrid
The Lung Facts team also wish to thank and remember the contributions of Professor Tobias Welte† – Chair, Professor of Pulmonary Medicine and Director of the Department of Pulmonary and Infectious Diseases at Hannover University School of Medicine, Hannover, Germany. Professor Welte sadly passed away in 2024.
Lung Facts Advisory Group
The Lung Facts Advisory group provided advice and support on the visualisation of the data into the Lung Fact website:
- Helena Backman, Associate Professor of Epidemiology and Public Health, at the OLIN-studies, Norrbotten County Council, and Department of Public Health and Clinical Medicine, Umeå University, Sweden.
- Robab Breyer-Kohansal, Associate Professor for Pulmonary Medicine at the Ludwig Boltzmann Institute for Lung Health and Head of the Department of Respiratory and Pulmonary Diseases, Clinic Hietzing, Vienna Austria
- Lies Lahousse, Associate Professor of Pharmacoepidemiology at Ghent University, Belgium and Erasmus Medical Center Rotterdam, the Netherlands.
- Lowie Vanfleteren, Associate Professor of Pulmonary Medicine at the University of Gothenburg and Pulmonologist at Sahlgrenska University Hospital.
- Stefan Karrasch, Physician and Scientist at LMU University Hospital, Munich, Germany
- James Allinson, Consultant Respiratory Physician at the Royal Brompton Hospital, London, UK and Honorary Senior Clinical Lecturer at the National Heart and Lung Institute, Imperial College London, UK.
ScHARR team
All data was collected and the economics calculated by a team from the School of Health and Related Research (ScHARR), University of Sheffield, UK:
- Sue Harnan, Senior Research Fellow
- Chris Carroll, Reader in Systematic Review and Evidence Synthesis
- Colin Angus, Senior Research Fellow
- Matthew Franklin, Senior Health Economist
- Emma Simpson, Senior Research Fellow
- Anthea Sutton, Senior Information Specialist
For more information on how this data has been visualised, please contact Pippa Powell and Lauren Anderson at the European Lung Foundation.