Estimating exposure-response functions: agriculture

From Opasnet
Jump to navigation Jump to search
The text on this page is taken from an equivalent page of the IEHIAS-project.

As part of the EU-funded INTARESE project, which contributed to the development of this Toolbox, a case study was carried out to assess the potential health effects of airborne exposures to pesticides, particulates and endotoxins (see full study report, downloadable below). As a basis for this assessment, exposure-response functions were derived for the exposures and health effects of interest.

Pesticides

For pesticides, evidence from both epidemiological and toxicological studies was used as a basis for deriving exposure-response functions.

Epidemiological evidence

In the absence of an authoritative and comprehensive systematic review providing exposure-response functions for pesticides, the initial intention was to conduct a purpose-designed review for the case study. An extensive literature review was therefore undertaken to identify candidate studies. This showed that existing studies of pesticides were extremely diverse: many related to specific active ingredients and to occupational exposures, and many were limited in terms of their generalisability. As a consequence, the validity of a systematic review was considered to be limited.

Instead, an approximation procedure was devised. This drew on a previous systematic review in Canada (Bassil et al. 2007, Sanborn et al. 2007) to identify relevant health outcomes. Using this as a guide, a subset of studies with relatively general health outcomes and exposure measures was then selected. From these, hypothetical relative risks (RRs) were derived for each health outcome for assumed low, medium and high exposure categories (with the low and high category defined as 10% lower and higher, respectively, than the medium). These were then used to represent indicative exposure-response functions for the broad pesticide groups.

Toxicological evidence

A wide range of studies have been conducted to assess the toxicology of pesticide. By their nature, these focus on individual active substances (ASs), mainly associated with carcinogenic health effects. Results from these studies were used to develop toxicological exposure-response relationships for specific ASs.

Data were sought on 84 ASs, identified as potentially toxic (carcinogenic or reproductive/developmental according to US EPA) by Karabelas et al. (2009). In each case, ideally, slope factors for measured relationships between exposure and health outcome were sought. The slope factor is defined as “an upper bound, approximating a 95% confidence limit, on the increased cancer risk from lifetime exposure to an agent” (US EPA Glossary 2008). This estimate is usually expressed in units of proportion (of a population) affected per mg/ kg/day. As an alternative, however, data on 'reference doses' were used. These represent estimates of the daily oral exposure to the human population (including sensitive subgroups) that is likely to be without an appreciable risk of deleterious effects. Reference doses derive from no-observed or lowest observed adverse effect levels (NOAEL or LOAEL) through the application of relevant uncertainty factors, and typically have an uncertainty spanning perhaps an order of magnitude.

Two main sources of information (both from the US Environmental Protection Agency) were used for these data: the IRIS database and The Reference Dose Tracking Report. Both databases provide data mainly relating to oral exposure routes, rather than inhalation or dermal routes, and the reference doses, for example, thus refer to Chronic Oral Exposure. For 30 of the target ASs, linear exposure–response relationships were available, thus providing ERFS for carcinogenicity; for 52 of the remainder only reference doses were available, so explicit exposure-response functions could not be derived.

Particulate matter

A large number of studies have been conducted on health effects of atmospheric particulates, and a number of systematic reviews and large multi-centre studies have been completed. In general, however, the focus has been on particulates derived from combustion sources (especially traffic), and the extent to which these are equally applicable to particles released by agricultural activities (much of which are probably crustal in origin) is uncertain.

Following an extensive literature review, exposure-response functions were obtained for PM10 and PM2.5 and respiratory and cardiovascular hospital admissions from three main sources (Le Tertre et al. 2002; Medina et al. 2005; Dominici et al. 2005). Although relative risks for PM10 are available for all ages, those for PM2.5 relate specifically to the elderly (>65 years old). The latter provide different relationships for COPD and respiratory tract infection hospital admissions.

Endotoxins

Emissions from animal husbandry include a variety of biological, microbial and inorganic particulates. The health effects of exposure to these materials is variable: while exposures to bioaerosols (endotoxins, bacteria, fungi, parasites, pollen etc) can have adverse health effects, several studies have indicated that exposure to endotoxins may have be protective, especially for children (Braun-Fahrlander et al. 2002, Downs et al. 2001, von Ehrenstein et al. 2000, Rennie et al. 2008). A literature review has been carried out in order to retrieve appropriate endotoxin exposure response relationships. According to Braun-Fahrlander et al. 2002, there is a strong inverse relationship between endotoxin exposure and sensitisation to common allergens and atopic diseases in school-age children. Moreover, farmers' children have lower prevalences of hay fever (adjusted odds ratio = 0.52, 95% CI 0.28–0.99), asthma (0.65, 0.39–1.09), and wheeze (0.55, 0.36–0.86) (von Ehrenstein et al. 2000). A significant nonlinear relationship between endotoxin exposure and sensitization has been also observed in adult farmers, where risk of sensitization strongly decreased with increasing exposure (Portengen et al. 2005).

References

Pesticides

Particulate matter

Endotoxins

  • Braun-Fahrlander, C., Riedler, J., Herz, U., Eder, W., Waser, M., Grize, L., Maisch, S., Carr, D., Florian, G., Bufe, A., Lauener, R.P., Schierl, R., Renz, H., Nowak, D. and von Mutius, E. 2002 Environmental exposure to endotoxin and its relation to asthma in school-age children. The New England Journal of Medicine 347(12), 869-877.
  • Downs, S.H., Marks, G.B., Mitakakis, T.Z., Leuppi, J.D., Car, N.G. and Peat, J.K. 2001 Having lived on a farm and protection against allergic diseases in Australia. Clinical and Experimental Allergy 31, 570-575.
  • Portengen, L., Preller, L., Tielen, M., Doekes, G. and Heederik, D. 2005 [www.jacionline.org/article/S0091-6749%2804%2903222-1/abstract Endotoxin exposure and atopic sensitization in adult pig farmers.] Journal of Allergy and Clinical Immunology 115(4), 797-802.
  • Rennie, D.C., Lawson, J.A., Kirychuk, S.P., Paterson, C., Willson, P.J., Senthilselvan, A. and Cockcroft, D.W. 2008 Assessment of endotoxin levels in the home and current asthma and wheeze in school-age children. Indoor Air 18(6), 447-53.
  • von Ehrenstein, O.S., von Mutius, E., Illi, S., Baumann, L., Boèhm O. and von Kries, R. 2000 [onlinelibrary.wiley.com/doi/10.1046/j.1365-2222.2000.00801.x/abstract Reduced risk of hay fever and asthma among children of farmers.] Clinical and Experimental Allergy 30, 187-193.

See also

File:Exposure and dose response functions PM-Endotoxins.pdf

Integrated Environmental Health Impact Assessment System
IEHIAS is a website developed by two large EU-funded projects Intarese and Heimtsa. The content from the original website was moved to Opasnet.
Topic Pages
Toolkit
Data

Boundaries · Population: age+sex 100m LAU2 Totals Age and gender · ExpoPlatform · Agriculture emissions · Climate · Soil: Degredation · Atlases: Geochemical Urban · SoDa · PVGIS · CORINE 2000 · Biomarkers: AP As BPA BFRs Cd Dioxins DBPs Fluorinated surfactants Pb Organochlorine insecticides OPs Parabens Phthalates PAHs PCBs · Health: Effects Statistics · CARE · IRTAD · Functions: Impact Exposure-response · Monetary values · Morbidity · Mortality: Database

Examples and case studies Defining question: Agriculture Waste Water · Defining stakeholders: Agriculture Waste Water · Engaging stakeholders: Water · Scenarios: Agriculture Crop CAP Crop allocation Energy crop · Scenario examples: Transport Waste SRES-population UVR and Cancer
Models and methods Ind. select · Mindmap · Diagr. tools · Scen. constr. · Focal sum · Land use · Visual. toolbox · SIENA: Simulator Data Description · Mass balance · Matrix · Princ. comp. · ADMS · CAR · CHIMERE · EcoSenseWeb · H2O Quality · EMF loss · Geomorf · UVR models · INDEX · RISK IAQ · CalTOX · PANGEA · dynamiCROP · IndusChemFate · Transport · PBPK Cd · PBTK dioxin · Exp. Response · Impact calc. · Aguila · Protocol elic. · Info value · DST metadata · E & H: Monitoring Frameworks · Integrated monitoring: Concepts Framework Methods Needs
Listings Health impacts of agricultural land use change · Health impacts of regulative policies on use of DBP in consumer products
Guidance System
The concept
Issue framing Formulating scenarios · Scenarios: Prescriptive Descriptive Predictive Probabilistic · Scoping · Building a conceptual model · Causal chain · Other frameworks · Selecting indicators
Design Learning · Accuracy · Complex exposures · Matching exposure and health · Info needs · Vulnerable groups · Values · Variation · Location · Resolution · Zone design · Timeframes · Justice · Screening · Estimation · Elicitation · Delphi · Extrapolation · Transferring results · Temporal extrapolation · Spatial extrapolation · Triangulation · Rapid modelling · Intake fraction · iF reading · Piloting · Example · Piloting data · Protocol development
Execution Causal chain · Contaminant sources · Disaggregation · Contaminant release · Transport and fate · Source attribution · Multimedia models · Exposure · Exposure modelling · Intake fraction · Exposure-to-intake · Internal dose · Exposure-response · Impact analysis · Monetisation · Monetary values · Uncertainty
Appraisal