Ranking Preventive Interventions from Different Policy Domains: What Are the Most Cost-Effective Ways to Improve Public Health?

It is widely acknowledged that in order to promote public health and prevent diseases, a wide range of scientific disciplines and sectors beyond the health sector need to be involved. Evidence-based interventions, beyond preventive health interventions targeting disease risk factors and interventions from other sectors, should be developed and implemented. Investing in these preventive health policies is challenging as budgets have to compete with other governmental expenditures. The current study aimed to identify, compare and rank cost-effective preventive interventions targeting metabolic, environmental, occupational and behavioral risk factors. To identify these interventions, a literature search was performed including original full economic evaluations of Western country interventions that had not yet been implemented in the Netherlands. Several workshops were held with experts from different disciplines. In total, 51 different interventions (including 13 cost saving interventions) were identified and ranked based on their incremental cost-effectiveness ratio (ICER) and potential averted disability-adjusted life years (DALYs), resulting in two rankings of the most cost-effective interventions and one ranking of the 13 cost saving interventions. This approach, resulting in an intersectoral ranking, can assist policy makers in implementing cost-effective preventive action that considers not only the health sector, but also other sectors.

Unifying the functional diversity in natural and cultivated soils using the overall body-mass distribution of nematodes.

BACKGROUND: Sustainable use of our soils is a key goal for environmental protection. As many ecosystem services are supported belowground at different trophic levels by nematodes, soil nematodes are expected to provide objective metrics for biological quality to integrate physical and chemical soil variables. Trait measurements of body mass carried out at the individual level can in this way be correlated with environmental properties that influence the performance of soil biota. RESULTS: Soil samples were collected across 200 sites (4 soil types and 5 land-use types resulting in 9 combinations) during a long-term monitoring programme in the Netherlands and the functional diversity of nematode communities was investigated. Using three commonly used functional diversity indices applicable to single traits (Divergence, Evenness and Richness), a unified index of overall body-mass distribution is proposed to better illustrate the application of functional metrics as a descriptor of land use. Effects of land use and soil chemistry on the functional diversity of nematodes were demonstrated and a combination of environmental factors accounts for the low functional value of Scots Pine forest soils in comparison to the high functional value of heathland soils, whereas human factors account for the low functional and chemical values of arable fields. CONCLUSIONS: These findings show an unexpected high functional vulnerability of nematodes inhabiting clay-rich soils in comparison to sandy soils and support the notion that soil C:N ratio is a major driver of biodiversity. The higher the C:N ratio, the higher the overall diversity, as soil nematodes cope better with nutrient-poor agroecosystems under less intense fertilization. A trait-based way focusing on size distribution of nematodes is proposed to maintain environmental health by monitoring the overall diversity in soil biota, keeping agriculture and forestry sustainable.

Trend analysis from 1970 to 2008 and model evaluation of EDGARv4 global gridded anthropogenic mercury emissions.

The Emission Database for Global Atmospheric Research (EDGAR) provides a time-series of man-made emissions of greenhouse gases and short-lived atmospheric pollutants from 1970 to 2008. Mercury is included in EDGARv4.tox1, thereby enriching the spectrum of multi-pollutant sources in the database. With an average annual growth rate of 1.3% since 1970, EDGARv4 estimates that the global mercury emissions reached 1,287 tonnes in 2008. Specifically, gaseous elemental mercury (GEM) (Hg(0)) accounted for 72% of the global total emissions, while gaseous oxidised mercury (GOM) (Hg(2+)) and particle bound mercury (PBM) (Hg-P) accounted for only 22% and 6%, respectively. The less reactive form, i.e., Hg(0), has a long atmospheric residence time and can be transported long distances from the emission sources. The artisanal and small-scale gold production, accounted for approximately half of the global Hg(0) emissions in 2008 followed by combustion (29%), cement production (12%) and other metal industry (10%). Given the local-scale impacts of mercury, special attention was given to the spatial distribution showing the emission hot-spots on gridded 0.1°×0.1° resolution maps using detailed proxy data. The comprehensive ex-post analysis of the mitigation of mercury emissions by end-of-pipe abatement measures in the power generation sector and technology changes in the chlor-alkali industry over four decades indicates reductions of 46% and 93%, respectively. Combined, the improved technologies and mitigation measures in these sectors accounted for 401.7 tonnes of avoided mercury emissions in 2008. A comparison shows that EDGARv4 anthropogenic emissions are nearly equivalent to the lower estimates of the United Nations Environment Programme (UNEP)'s mercury emissions inventory for 2005 for most sectors. An evaluation of the EDGARv4 global mercury emission inventory, including mercury speciation, was performed using the GEOS-Chem global 3-D mercury model. The model can generally reproduce both spatial variations and long-term trends in total gaseous mercury concentrations and wet deposition fluxes.

Fine particles: from scientific uncertainty to policy strategy.

Gaps in our knowledge should not be a reason for not making policy decisions. How can we define robust policy strategies, given the various uncertainties in the sources, exposure, and causes of health effects? Which uncertainties are most important? What are its policy implications? This contribution will describe policy strategies for particulate matter (PM) abatement that are consistent with certain sets of assumptions, as well as the risks that are associated with such strategies. What is an optimal strategy assuming that the fine particles (PM2.5) are the main cause of health effects? And what would be the "mistake" of such a strategy, if "in the end" PM10 or carbonaceous particles prove to be the "real" cause? How can we make the policy strategy more robust and minimise its financial risks and health risks? This contribution describes a systematic way of dealing with the knowledge gaps in the policy process.