Data

In this section we will briefly discuss the types of data that are available for dietary risk assessment for the pesticide registration process and how they are obtained.

1.3.1.1 Residue Levels

The EU framework for risk assessment of pesticides results in the collection of two types of residue level data related to human dietary risk assessment. Before approval is granted, notifiers have to provide supervised field trial data which are used in the risk assessment that is conducted as part of the DAR. Following approval, pesticide residue levels will be monitored in food products to determine any MRL exceedance and to indicate whether unauthorised pesticides have been applied.

Supervised Field Trial Data

For the authorisation of a new use, the only residue data available come from a number of supervised field trials. These trials are conducted to determine the mag- nitude of the pesticide residue in or on raw agricultural commodities (RACs) and are designed to reflect pesticide use patterns that lead to the highest possible residues under ‘Critical Good Agricultural Practice’ (cGAP). This is the GAP selected to represent the worst-case use scenario that produces the highest possible field residues on crop commodities. It usually includes the maximum use-rate, the maximum num- ber of applications and the minimum re-treatment and pre-harvest intervals (OECD, 2011a). Supervised field trial data are used to propose MRLs and to provide the Su- pervised Trial Median Residue (STMR) and Highest Residue (HR) values for use in intake assessments. Generally, composite samples consisting of several units of a raw agricultural commodity are obtained from a supervised field trial (OECD, 2009).

EC (1997) and OECD (2009) provide guidelines for supervised field trials and give an overview of a wide range of considerations that need to be taken into account when conducting them. Field trial characteristics include:

in advance of a preliminary evaluation of the trial results. Assuming compara- bility can be established between production areas (e.g. climate, application techniques, growing seasons, etc.), a minimum of eight trials representative of the proposed growing area is required for major crops. For minor crops normally four trials representative of the proposed growing area are required. If comparability cannot be established, more trials should be conducted to represent the variation in conditions.

Site Selection: Supervised field trials which are carried out in open fields should include data from four different sites in the same growing season. For appli- cations under glass, a single site is sufficient as the conditions are controlled. Trials should be conducted in regions where the crops are predominantly grown commercially and should reflect the main types of agricultural practice, espe- cially if this has a significant impact on residue levels. Furthermore, the sites should be chosen to reflect variations in weather conditions, different types of soil and the special characteristics of each crop.

Plot Size: The plot size depends on the crop but should be large enough to allow application of the test substance in a manner which reflects routine use and such that sufficient representative samples can be obtained.

Post-harvest Treatment: Records should be kept on post-harvest treatments and storage location conditions for those crops that are routinely treated or stored after harvesting (e.g. potatoes, seeds, etc.).

Application: Supervised field trials should be based on the highest proposed rate of application consistent with GAP. Test substance applications should not be made in strong wind, during rain or when rainfall is expected shortly af- ter application. The formulation should be the intended formulation of the product for the crop or commodity. The maximum proposed label rate, the maximum number of applications and minimum treatment interval should be used when applying the test substance. Application timing is determined by plant growth stage and/or the number of days prior to harvest. If a specific minimum pre-harvest interval is indicated on the label (e.g. ‘Do not apply

this product less than 14 days prior to harvest.’), it should be used in the field trials.

Sampling of RACs: For the purpose of MRL setting, samples taken from super- vised field trials should be of the whole RAC as it is used in the food supply chain. The residue level on the edible portion of the commodity needs to be obtained for use in dietary risk assessment (WHO, 1997). For plants or plant products with inedible skin (such as citrus, banana, kiwi, pineapple) a separate analysis of flesh and skin should be performed on some samples in order to provide data on the distribution of residues between flesh and skin (EC, 1997). For some crops, there may be more than one RAC (e.g. maize). Guidelines for the sampling strategy for RACs from supervised field trials are provided in EC (1997).

Monitoring Data

Residue level data may also be available from monitoring surveys. These surveys do not only focus on pesticides that have been approved but may also test for pes- ticides that have not been approved in order to assess compliance with approval regulations. EC Directive 2002/63/EC (EC, 2002) specifies sampling procedures for the official control of pesticide residues in and on products of plant and animal origin. The procedure is based on taking a representative sample from a ‘lot’. A ‘lot’ is defined as a quantity of a food material delivered at one time and presumed to have uniform characteristics such as origin, producer, variety, etc. The guidelines specify the quantity to sample, both in terms of the total weight and the number of units. The number of units do not necessarily correspond to the number of units that are sampled in supervised field trials: for example, in supervised field trials a composite sample of cucumbers will consist of 12 units whereas in monitoring sur- veys the number of units is at least 5. However, there is little information available on how commodities and pesticides should be selected for inclusion in monitor- ing programmes. EFSA (2011) states that many countries determine the sampling frequency of different commodities based on the results of previous monitoring pro- grammes (monitoring of similar crops to determine trends in residue levels), food

consumption figures and exceedances in previous years. Therefore, the extent of monitoring programmes varies between countries and different amounts of data will be available.

1.3.1.2 Consumption Data

For dietary intake assessments, consumption data is obtained from dietary surveys. The most basic survey is a food frequency survey in which participants record or recall the number of occasions each food was consumed over a specified period of time (Brandstetter et al., 1999). Another type of survey is a 24 hour recall study in which the quantities consumed are retrieved in the course of an interview. The interviewer may use appropriate memory aids (e.g. photographs of prepared dishes and/or calibrated portion sizes) and information on cooking methods, recipes and labels of industrially prepared foods may also be retrieved (Lallukka et al., 2001). A further type of survey is a dietary record survey which involves recording the amount of food consumed in a specified period of time. These surveys can either be based on weighing all foods prior to their consumption or comparing the food with photographs of calibrated portion sizes (Gregory et al., 2000; Hoare et al., 2004; Ock´e et al., 2007; VCP, 1998).

Figure 1.1 shows an overview of the general characteristics of dietary surveys and a few examples of surveys that have been conducted in EU countries. To obtain an EU-wide conservative intake estimate for dietary risk assessments, it is impor- tant to obtain a representative sample of consumption in each country as EU sub- populations may have different dietary habits.

Consumption Data UK NL Country • 1699 indiv. • Age: 4-18 y • 7 days • Weighed intakes • ... Gregory et al. (2000) NDNS Young People • 1724 indiv. • Age: 19-64 y • 7 days • Weighed intakes • ... Hoare (2004) NDNS-2001 • 6250 indiv. • Age: 1-97 y • 2 consecutive days • Dietary Record Survey • Estimated and/or weighed intakes • ... VCP (1998) VCP-3 • 452 indiv. • Age: 2-6 y • 2 non- consecutive days • Dietary Record Survey • Estimated and/or weighed intakes • ... Ocké et al. (2008) DNFCS Young Children • Number of participants • Age Group • Duration • Type o Measured (weighed) o Estimated (visual / standard measures) • ... Survey ...

Figure 1.1 – Examples of existing dietary survey data.

Figure 1.2 provides an overview of how information from dietary surveys are pro- cessed before they can be used in dietary risk assessments. For each person a daily record of which food items were consumed during various eating events (e.g. a pizza for dinner) is available. For dietary risk assessments, we need to estimate how many units of RACs were consumed and how much each of them weighs. Therefore, these data may have to be converted from a portion size to a weight-based amount (using photographs of food items of various portion sizes, e.g. if the portion consumed is similar to the photograph of a medium pizza, a weight of 300 grammes of pizza is assigned to the eating event). Processed food items will have to be converted into ingredients (e.g. tomato puree, mushroom slices), which then need to be converted into RACs (e.g. tomatoes, mushrooms). This is done using generic recipe databases and may depend on the food item’s brand. Conversion into RACs is necessary because residue data are collected at the RAC level.

Consumption Data

Recipe Database

Edible portion

Processing

Consumer 1 Consumer 2 Consumer ...

Body

Weight Day 1 Day ..

Body

Weight Day 1 Day ..

Eating Event 1 Eating Event 2 Eating Event .. Food Item 1 Food Item 2 Food Item .. Food Item 1 Food Item 2 Food Item .. Brand 1 Ingredient 1 Ingredient 2 RAC 1: Amount RAC 2: Amount RAC 1: No. of Units & Weights

RAC 2: No. of Units & Weights

Brand 2 Ingredient 1 Ingredient 3 RAC 1: Amount RAC 3: Amount RAC 1: No. of Units & Weights

RAC 3: No. of Units & Weights

RAC 1: Units & Weights

RAC 2: Units & Weights

RAC 3: Units & Weights

Figure 1.2 – Generic approach for modelling of consumption data in dietary risk assessments.