Quantifying reciprocal relationships between poverty and health: combining a causal loop diagram with longitudinal structural equation modelling.

BACKGROUND: This study takes on the challenge of quantifying a complex causal loop diagram describing how poverty and health affect each other, and does so using longitudinal data from The Netherlands. Furthermore, this paper elaborates on its methodological approach in order to facilitate replication and methodological advancement. METHODS: After adapting a causal loop diagram that was built by stakeholders, a longitudinal structural equation modelling approach was used. A cross-lagged panel model with nine endogenous variables, of which two latent variables, and three time-invariant exogenous variables was constructed. With this model, directional effects are estimated in a Granger-causal manner, using data from 2015 to 2019. Both the direct effects (with a one-year lag) and total effects over multiple (up to eight) years were calculated. Five sensitivity analyses were conducted. Two of these focus on lower-income and lower-wealth individuals. The other three each added one exogenous variable: work status, level of education, and home ownership. RESULTS: The effects of income and financial wealth on health are present, but are relatively weak for the overall population. Sensitivity analyses show that these effects are stronger for those with lower incomes or wealth. Physical capability does seem to have strong positive effects on both income and financial wealth. There are a number of other results as well, as the estimated models are extensive. Many of the estimated effects only become substantial after several years. CONCLUSIONS: Income and financial wealth appear to have limited effects on the health of the overall population of The Netherlands. However, there are indications that these effects may be stronger for individuals who are closer to the poverty threshold. Since the estimated effects of physical capability on income and financial wealth are more substantial, a broad recommendation would be that including physical capability in efforts that are aimed at improving income and financial wealth could be useful and effective. The methodological approach described in this paper could also be applied to other research settings or topics.

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.

The incremental healthcare cost associated with cancer in Belgium: A registry-based data analysis.

BACKGROUND: Similar to many countries, Belgium experienced a rapid increase in cancer diagnoses in the last years. Considering that a large part of cancer types could be prevented, our study aimed to estimate the annual healthcare burden of cancer per site, and to compare cost with burden of disease estimates to have a better understanding of the impact of different cancer sites in Belgium. METHODS: We used nationally available data sources to estimate the healthcare expenditure. We opted for a prevalence-based approach which measures the disease attributable costs that occur concurrently for 10-year prevalent cancer cases in 2018. Average attributable costs of cancer were computed via matching of cases (patients with cancer by site) and controls (patients without cancer). Years of life lost due to disability (YLD) were used to summarize the health impact of the selected cancers. RESULTS: The highest attributable cost in 2018 among the selected cancers was on average €15,867 per patient for bronchus and lung cancer, followed by liver cancer, pancreatic cancer, and mesothelioma. For the total cost, lung cancer was the most costly cancer site with almost €700 million spent in 2018. Lung cancer was followed by breast and colorectal cancer that costed more than €300 million each in 2018. CONCLUSIONS: In our study, the direct attributable cost of the most prevalent cancer sites in Belgium was estimated to provide useful guidance for cost containment policies. Many of these cancers could be prevented by tackling risk factors such as smoking, obesity, and environmental stressors.

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.

The increasing significance of disease severity in a burden of disease framework.

Recent estimates have reiterated that non-fatal causes of disease, such as low back pain, headaches and depressive disorders, are amongst the leading causes of disability-adjusted life years (DALYs). For these causes, the contribution of years lived with disability (YLD) - put simply, ill-health - is what drives DALYs, not mortality. Being able to monitor trends in YLD closely is particularly relevant for countries that sit high on the socio-demographic spectrum of development, as it contributes more than half of all DALYs. There is a paucity of data on how the population-level occurrence of disease is distributed according to severity, and as such, the majority of global and national efforts in monitoring YLD lack the ability to differentiate changes in severity across time and location. This raises uncertainties in interpreting these findings without triangulation with other relevant data sources. Our commentary aims to bring this issue to the forefront for users of burden of disease estimates, as its impact is often easily overlooked as part of the fundamental process of generating DALY estimates. Moreover, the wider health harms of the COVID-19 pandemic have underlined the likelihood of latent and delayed demand in accessing vital health and care services that will ultimately lead to exacerbated disease severity and health outcomes. This places increased importance on attempts to be able to differentiate by both the occurrence and severity of disease.

Estimating risk factor attributable burden - challenges and potential solutions when using the comparative risk assessment methodology.

BACKGROUND: Burden of disease analyses quantify population health and provide comprehensive overviews of the health status of countries or specific population groups. The comparative risk assessment (CRA) methodology is commonly used to estimate the share of the burden attributable to risk factors. The aim of this paper is to identify and address some selected important challenges associated with CRA, illustrated by examples, and to discuss ways to handle them. Further, the main challenges are addressed and finally, similarities and differences between CRA and health impact assessments (HIA) are discussed, as these concepts are sometimes referred to synonymously but have distinctly different applications. RESULTS: CRAs are very data demanding. One key element is the exposure-response relationship described e.g. by a mathematical function. Combining estimates to arrive at coherent functions is challenging due to the large variability in risk exposure definitions and data quality. Also, the uncertainty attached to this data is difficult to account for. Another key issue along the CRA-steps is to define a theoretical minimal risk exposure level for each risk factor. In some cases, this level is evident and self-explanatory (e.g., zero smoking), but often more difficult to define and justify (e.g., ideal consumption of whole grains). CRA combine all relevant information and allow to estimate population attributable fractions (PAFs) quantifying the proportion of disease burden attributable to exposure. Among many available formulae for PAFs, it is important to use the one that allows consistency between definitions, units of the exposure data, and the exposure response functions. When combined effects of different risk factors are of interest, the non-additive nature of PAFs and possible mediation effects need to be reflected. Further, as attributable burden is typically calculated based on current exposure and current health outcomes, the time dimensions of risk and outcomes may become inconsistent. Finally, the evidence of the association between exposure and outcome can be heterogeneous which needs to be considered when interpreting CRA results. CONCLUSIONS: The methodological challenges make transparent reporting of input and process data in CRA a necessary prerequisite. The evidence for causality between included risk-outcome pairs has to be well established to inform public health practice.

Qualitative modelling of social determinants of health using group model building: the case of debt, poverty, and health.

BACKGROUND: Social determinants of health (SDoH) are known to have a large impact on health outcomes, but their effects are difficult to make visible. They are part of complex systems of variables largely indirect effects on multiple levels, constituting so-called wicked problems. This study describes a participatory approach using group model building (GMB) with stakeholders, in order to develop a qualitative causal model of the health effects of SDoH, taking poverty and debt in the Dutch city of Utrecht as a case study. METHODS: With GMB we utilised the perspective of stakeholders who are directly involved in policy and practice regarding poverty, debt, and/or health. This was done using system dynamic modelling, in three interactive sessions lasting three hours each. In these sessions, they constructed a model, resulting in a system of variables with causal relationships and feedback loops. Subsequently, the results of these GMB sessions were compared to scientific literature and reviewed by a panel of researchers with extensive experience in relevant scientific fields. RESULTS: The resulting model contains 71 causal relationships between 39 variables, 29 of which are present in feedback loops. The variables of participation in society, stress, shame, social contacts and use of services/provisions appear to hold prominent roles in the model's mechanisms. Most of the relationships in the model are supported by scientific literature. The researchers reviewing the model in the scientific meeting agreed that the vast majority of relationships would concur with scientific knowledge, but that the model constructed by the stakeholders consists mostly of individual-level factors, while important conditions usually relate to systemic variables. CONCLUSIONS: Building a model with GMB helps grasp the complex situation of a wicked problem, for which it is unlikely that its interrelationships result in a fully intuitive understanding with linear mechanisms. Using this approach, effects of SDoH can be made visible and the body of evidence expanded. Importantly, it elicits stakeholders' perspectives on a complex reality and offers a non-arbitrary way of formulating the model structure. This qualitative model is also well suited to serve as conceptual input for a quantitative model, which can be used to test and estimate the relationships.

Exploring Health Trends Prior to State Pension Age for The Netherlands up to 2040.

BACKGROUND: In many Western countries, the state pension age is being raised to stimulate the extension of working lives. It is not yet well understood whether the health of older adults supports this increase. In this study, future health of Dutch adults aged 60 to 68 (i.e., the expected state pension age) is explored up to 2040. METHODS: Data are from the Dutch Health Interview Survey 1990-2017 (N ≈ 10,000 yearly) and the Dutch Public Health Monitor 2016 (N = 205,151). Health is operationalized using combined scores of self-reported health and limitations in mobility, hearing or seeing. Categories are: good, moderate and poor health. Based on historical health trends, two scenarios are explored: a stable health trend (neither improving nor declining) and an improving health trend. RESULTS: In 2040, the health distribution among men aged 60-68 is estimated to be 63-71% in good, 17-28% in moderate and 9-12% in poor health. Among women, this is estimated to be 64-69%, 17-24% and 12-14%, respectively. CONCLUSIONS: This study's explorations suggest that a substantial share of people will be in moderate or poor health and, thus, may have difficulty continuing working. Policy aiming at sustainable employability will, therefore, remain important, even in the case of the most favorable scenario.

Recommendations to plan a national burden of disease study.

BACKGROUND: The InfAct (Information for Action) project is a European Commission Joint Action on Health Information which has promoted the potential role of burden of disease (BoD) approaches to improve the current European Union-Health Information System (EU-HIS). It has done so by raising awareness of the concept, the methods used to calculate estimates and their potential implications and uses in policymaking. The BoD approach is a systematic and scientific effort to quantify and compare the magnitude of health loss due to different diseases, injuries, and risk factors with estimates produced by demographic characteristics and geographies for specific points in time. Not all countries have the resources to undertake such work, and may therefore start with a more restricted objective, e.g., a limited number of diseases, or the use of simple measures of population health such as disease prevalence or life expectancy. The main objective to develop these recommendations was to facilitate those countries planning to start a national burden of disease study. RESULTS: These recommendations could be considered as minimum requirements for those countries planning to start a BoD study and includes following elements: (1) Define the objectives of a burden of disease study within the context of your country, (2) Identify, communicate and secure the benefits of performing national burden of disease studies, (3) Secure access to the minimum required data sources, (4) Ensure the minimum required capacity and capability is available to carry out burden of disease study, (5) Establish a clear governance structure for the burden of disease study and stakeholder engagement/involvement, (6) Choose the appropriate methodological approaches and (7) Knowledge translation. These were guided by the results from our survey performed to identify the needs of European countries for BoD studies, a narrative overview from four European countries (Belgium, Germany, The Netherlands and Scotland) and the summary of a comparative study of country health profiles with national health statistics. CONCLUSIONS: These recommendations as minimum requirements would facilitate efforts by those European countries who intend to perform national BoD studies.

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.

Four normative perspectives on public health policy-making and their preferences for bodies of evidence.

Calls for evidence-informed public health policy-making often ignore that there are multiple, and often competing, bodies of potentially relevant evidence to which policy-makers have recourse in identifying policy priorities and taking decisions. In this paper, we illustrate how policy frames may favour the use of specific bodies of evidence. For the sixth Dutch Public Health Status and Foresight report (2014), possible future trends in population health and healthcare expenditure were used as a starting point for a deliberative dialogue with stakeholders to identify and formulate the most important societal challenges for the Dutch health system. Working with these stakeholders, we expanded these societal challenges into four normative perspectives on public health. These perspectives can be regarded as policy frames. In each of the perspectives, a specific body of evidence is favoured and other types of evidence are neglected. Crucial outcomes in one body may be regarded as irrelevant from other perspectives. Consequently, the results of research from a single body of evidence may not be helpful in the policy-making processes because policy-makers need to account for trade-offs between all competing interests and values. To support these policy processes, researchers need to combine qualitative and quantitative methodologies to address different outcomes from the start of their studies. We feel it is time for the research community to re-politicise the idea of evidence use and for policy-makers to demand research that helps them to account for all health-related policy goals. This is a prerequisite for real evidence-informed policy-making.

Effects of Dutch livestock production on human health and the environment.

Observed multiple adverse effects of livestock production have led to increasing calls for more sustainable livestock production. Quantitative analysis of adverse effects, which can guide public debate and policy development in this area, is limited and generally scattered across environmental, human health, and other science domains. The aim of this study was to bring together and, where possible, quantify and aggregate the effects of national-scale livestock production on 17 impact categories, ranging from impacts of particulate matter, emerging infectious diseases and odor annoyance to airborne nitrogen deposition on terrestrial nature areas and greenhouse gas emissions. Effects were estimated and scaled to total Dutch livestock production, with system boundaries including feed production, manure management and transport, but excluding slaughtering, retail and consumption. Effects were expressed using eight indicators that directly express Impact in the sense of the Drivers-Pressures-State-Impact-Response framework, while the remaining 14 express Pressures or States. Results show that livestock production may contribute both positively and negatively to human health with a human disease burden (expressed in disability-adjusted life years) of up to 4% for three different health effects: those related to particulate matter, zoonoses, and occupational accidents. The contribution to environmental impact ranges from 2% for consumptive water use in the Netherlands to 95% for phosphorus transfer to soils, and extends beyond Dutch borders. While some aggregation across impact categories was possible, notably for burden of disease estimates, further aggregation of disparate indicators would require normative value judgement. Despite difficulty of aggregation, the assessment shows that impacts receive a different contribution of different animal sectors. While some of our results are country-specific, the overall approach is generic and can be adapted and tuned according to specific contexts and information needs in other regions, to allow informed decision making across a broad range of impact categories.

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

[This corrects the article DOI: 10.1186/s13690-020-00433-y.].

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.

Reflections on key methodological decisions in national burden of disease assessments.

BACKGROUND: Summary measures of population health are increasingly used in different public health reporting systems for setting priorities for health care and social service delivery and planning. Disability-adjusted life years (DALYs) are one of the most commonly used health gap summary measures in the field of public health and have become the key metric for quantifying burden of disease (BoD). BoD methodology is, however, complex and highly data demanding, requiring a substantial capacity to apply, which has led to major disparities across researchers and nations in their resources to perform themselves BoD studies and interpret the soundness of available estimates produced by the Global Burden of Disease Study. METHODS: BoD researchers from the COST Action European Burden of Disease network reflect on the most important methodological choices to be made when estimating DALYs. The paper provides an overview of eleven methodological decisions and challenges drawing on the experiences of countries working with BoD methodology in their own national studies. Each of these steps are briefly described and, where appropriate, some examples are provided from different BoD studies across the world. RESULTS: In this review article we have identified some of the key methodological choices and challenges that are important to understand when calculating BoD metrics. We have provided examples from different BoD studies that have developed their own strategies in data usage and implementation of statistical methods in the production of BoD estimates. CONCLUSIONS: With the increase in national BoD studies developing their own strategies in data usage and implementation of statistical methods in the production of BoD estimates, there is a pressing need for equitable capacity building on the one hand, and harmonization of methods on the other hand. In response to these issues, several BoD networks have emerged in the European region that bring together expertise across different domains and professional backgrounds. An intensive exchange in the experience of the researchers in the different countries will enable the understanding of the methods and the interpretation of the results from the local authorities who can effectively integrate the BoD estimates in public health policies, intervention and prevention programs.

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.

Calculating incidence rates and prevalence proportions: not as simple as it seems.

BACKGROUND: Incidence rates and prevalence proportions are commonly used to express the populations health status. Since there are several methods used to calculate these epidemiological measures, good comparison between studies and countries is difficult. This study investigates the impact of different operational definitions of numerators and denominators on incidence rates and prevalence proportions. METHODS: Data from routine electronic health records of general practices contributing to NIVEL Primary Care Database was used. Incidence rates were calculated using different denominators (person-years at-risk, person-years and midterm population). Three different prevalence proportions were determined: 1 year period prevalence proportions, point-prevalence proportions and contact prevalence proportions. RESULTS: One year period prevalence proportions were substantially higher than point-prevalence (58.3 - 206.6%) for long-lasting diseases, and one year period prevalence proportions were higher than contact prevalence proportions (26.2 - 79.7%). For incidence rates, the use of different denominators resulted in small differences between the different calculation methods (-1.3 - 14.8%). Using person-years at-risk or a midterm population resulted in higher rates compared to using person-years. CONCLUSIONS: All different operational definitions affect incidence rates and prevalence proportions to some extent. Therefore, it is important that the terminology and methodology is well described by sources reporting these epidemiological measures. When comparing incidence rates and prevalence proportions from different sources, it is important to be aware of the operational definitions applied and their impact.

The Public Health Status and Foresight report 2014: Four normative perspectives on a healthier Netherlands in 2040.

Policy-oriented foresight reports aim to inform and advise decision-makers. In value-laden areas such as public health and healthcare, deliberative scenario methods are clearly needed. For the sixth Dutch Public Health Status and Forecasts-report (PHSF-2014), a new approach of co-creation was developed aiming to incorporate different societal norms and values in the description of possible future developments. The major future trends in the Netherlands were used as a starting point for a deliberative dialogue with stakeholders to identify the most important societal challenges for public health and healthcare. Four societal challenges were identified: 1) To keep people healthy as long as possible and cure illness promptly, 2) To support vulnerable people and enable social participation, 3) To promote individual autonomy and freedom of choice, and 4) To keep health care affordable. Working with stakeholders, we expanded these societal challenges into four corresponding normative scenarios. In a survey the normative scenarios were found to be recognizable and sufficiently distinctive. We organized meetings with experts to explore how engagement and policy strategies in each scenario would affect the other three societal challenges. Possible synergies and trade-offs between the four scenarios were identified. Public health foresight based on a business-as-usual scenario and normative scenarios is clearly practicable. The process and the outcomes support and elucidate a wide range of strategic discussions in public health.

[Environment and the "Health in All Policies" approach-an overview]. / Umwelt und der "Health-in-all-Policies"-Ansatz ­ ein Überblick.

BACKGROUND: One quarter of the global disease burden could be avoided with management strategies for environmental risk factors such as air and water pollution, food contamination, injuries and poor road safety. Many decisions influencing health are made outside the health sector; thus, the joint consideration and implementation of health and environmental factors in the relevant policies are becoming increasingly important. MATERIALS AND METHODS: By means of a selective literature search, we identified important policy documents and selected research articles as a basis for the introduction and current discussion of the Health in All Policies (HiAP) approach. Parallels with the Environment in All Policies (EIAP) approach are debated. RESULTS AND CONCLUSIONS: The consideration and reinforcement of environmental topics in HiAP and the link with health in the EiAP approach increase the chances of policies with mutually positive effects, especially with regard to the significance of social factors for health and the environment. The UN Sustainable Development Goals provide a good starting point for a joint strategy for reinforcing health and environmental aspects. Health and Environmental Impact Assessments are accepted procedures in many countries. The HiAP strategy implemented in South Australia provides a well-documented institutional approach to the integration and linkage of health and environmental issues. These examples can be used as well-established starting points for a definition of HiAP incorporating the equitable involvement of environmental issues. Barriers to this goal relate, for example, to the particular interests of the various participating sectors.