Computation of health impact indicators for agriculture

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The text on this page is taken from an equivalent page of the IEHIAS-project.

Health impact indicators are used in order to relate cause (concentration or exposure) to effects (human health effects) from various pollutants emitted from specific sources. The health impact indicators developed for the agriculture case study were: risk, attributable burden of disease and disability-adjusted life years (DALYs).

Risk is an expression of the likelihood (statistical probability) that harm will occur when a receptor (e.g. human or a part of an ecosystem) is exposed to a hazard. An example of a risk indicator is thelikelihood that a certain population (e.g. farmers) will have a certain level of cancer incidence after being exposed to a certain pollutant (e.g. pesticides). The burden of disease provides a comprehensive assessment of the health status of people and gives policy makers the information need to make decisions about health.

To describe and compare the health impact of various environmental exposures common indices like DALYs can be used. These give an indication of the potential number of healthy life years lost due to premature mortality or morbidity.

Risk from pesticides Active Substances (AS) based on toxicological data is given in the following equation:

Equation 1.

AB = R x P


  • P is the exposed population and
  • R is the risk from pesticides to human health that is calculated using equation 1a:

Equation 1a.

R = IR x (ERFASi)


  • ERFASi is the Exposure Response Function for each AS i (in (mg/kg/day)-1), and
  • IR is a yearly averaged intake rate (in μg/kg/day), defined in equation 1b

Equation 1b.

IR = (Ci x Qinh x texp) / BW


  • Ci is the average pesticide concentration in the exposure medium(in μg AS/m3) over the exposure period (texp),
  • Qinh is the daily average inhalation rate (in m3 air/d) for humans and
  • BW is the average body weight (assumed 75 kg)

For the purpose of this study the exposure period is a full year (i.e. texp=12 months).

Attributable burden (AB)

AB is the number of cases attributable to agricultural contaminants under land use change scenarios, can also be computed using the following basic formula (equation 2).

Equation 2.



  • RR is the relative risk
  • I is the background rate of disease (incidence or prevalence)
  • Pe is the exposed population

Baseline prevalence and incidence rates for health outcome and mortality rates were obtained from the Office of National Statistics in the UK, and the European Commission, DG Health and Consumer Protection for Greece.

Where exposure groups were defined (e.g. non-exposed vs exposed; or low, medium and high exposure tertiles for pesticides) equation 1 was computed once for each exposure category, then AB summed.

For particulates, a non-threshold linear relation was assumed between air pollution and all health outcomes, changing slightly the AB formula (equation 2) to that shown in equation 3. Here, for example we assume a RR mortality: 1.06 per 10µg/m3 agricultural-related PM10. The entire population comprises Pe.

Equation 3.



  • C is the concentration (e.g. µg/m3 agricultural-related PM10)
  • β is defined in Equation 3a (e.g. β per 1 µg/m3= 0.0058)

Equation 3a.



To calculate DALYs due to exposure to a specific health effect (e.g. respiratory health effect), the burden of disease (AB), the duration of the disease (D) and a severity weight (S), based on expert judgement, are combined in the following equation:

Equation 4.

DALYs = AB x D x S

The duration of a health effect describes the number of healthy life years lost or the time someone has the specific disease (morbidity), while the severity or disability weights varies from 0 (healthy) to 1 (death) and represents the consequences of relative severity of each disease. In the agriculture case study, DALYs were calcuated for particulates.

See also

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.
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Issue framing Formulating scenarios · Scenarios: Prescriptive Descriptive Predictive Probabilistic · Scoping · Building a conceptual model · Causal chain · Other frameworks · Selecting indicators
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